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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Functionalized Porous Polymer Networks as High-Performance PFAS Adsorbents

Toxic per- and polyfluoroalkyl substances (PFAS) are now found in nearly every water source on the planet. Exposure to these molecules can have negative health consequences, but the low concentration of PFAS relative to other solutes in water makes their removal challenging. Adsorbents offer a promising treatment route, but often exhibit low selectivities and removal capacities, as well as slow kinetics. The performance in these metrics can be improved by chemically optimizing PFAS binding sites and maximizing PFAS-adsorbent interactions. To explore how to achieve this, a porous polymer network solid (PPN-6, also known as PAF-1) was postsynthetically modified with various chemical moieties capable of leveraging unique combinations of electrostatic, hydrogen-bonding, hydrophobic, and fluorophilic interactions with PFAS molecules. Batch adsorption experiments and computational studies revealed that electrostatic and hydrogen-bonding interactions drive short-chain PFAS adsorption, while hydrophobic and fluorophilic interactions improve long-chain PFAS adsorption. In complex water matrices, a combination of electrostatic and fluorophilic interactions led to the greatest total PFAS removal. The best-performing material, functionalized with a fluorinated alkylammonium (PPN-6-FNDMB), selectively adsorbs PFAS with high capacity (up to 4.0 mmol/g) and rapid kinetics (equilibrium reached in <30 s). Furthermore, PPN-6-FNDMB outperforms several commercial adsorbents, achieving near-complete removal of 21 different PFAS from a groundwater sample collected at a US Air Force base. The PFAS could subsequently be desorbed from PPN-6-FNDMB, concentrating them by a factor of over 50 times. The recycled PPN-6-FNDMB could then be reused with minimal losses in long-chain PFAS adsorption capacity over four cycles.

Pezoulas, Ethan R↗
DOE OSTI2021

Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer

In this work, we develop a novel data-driven approach to modeling the atmospheric boundary layer. This approach leads to a nonlocal, anisotropic synthetic turbulence model which we refer to as the deep rapid distortion (DRD) model. Our approach relies on an operator regression problem that characterizes the best fitting candidate in a general family of nonlocal covariance kernels parameterized in part by a neural network. This family of covariance kernels is expressed in Fourier space and is obtained from approximate solutions to the Navier–Stokes equations at very high Reynolds numbers. Each member of the family incorporates important physical properties such as mass conservation and a realistic energy cascade. The DRD model can be calibrated with noisy data from field experiments. After calibration, the model can be used to generate synthetic turbulent velocity fields. To this end, we provide a new numerical method based on domain decomposition which delivers scalable, memory-efficient turbulence generation with the DRD model as well as others. We demonstrate the robustness of our approach with both filtered and noisy data coming from the 1968 Air Force Cambridge Research Laboratory Kansas experiments. Using these data, we witness exceptional accuracy with the DRD model, especially when compared to the International Electrotechnical Commission standard.

17 WIND ENERGY↗
DOE OSTI2026

Flood Estimation under Snowmelt and Rain-on-Snow Processes in Alaska: A Military Installation Perspective

Accurate flood estimation in snow-dominated and high-latitude regions remains challenging due to complex interactions among rainfall, snowmelt, and rain-on-snow (ROS) processes, which are not captured in conventional precipitation-based intensity-duration-frequency (PREC-IDF) curves. This study evaluates the Next-Generation IDF (NG-IDF) framework, an extension of PREC-IDF that incorporates total water available for runoff (precipitation minus changes in snow water equivalent), in two contrasting Alaskan watersheds of Department of Defense (DoD) significance: the Little Chena River Basin (LCRB) in interior Alaska, a tributary of the Chena River that flows through Fort Wainwright and near Eielson Air Force Base, and the Upper Ship Creek Basin (USCB), which drains Joint Base Elmendorf-Richardson near Anchorage. Using long-term SNOTEL observations and event-based rainfall-runoff modeling, NG-IDF and PREC-IDF flood estimates were compared against observation-based flood frequency analyses. Results show that NG-IDF consistently reduces flood-estimation bias by 15–20% relative to PREC-IDF, particularly for snowmelt- and ROS-dominated events. In the interior LCRB, permafrost conditions can substantially amplify flood responses during snowmelt events, an effect not explicitly represented in standard design tools. These findings demonstrate that NG-IDF provides a more physically consistent and transferable framework for flood estimation in cold regions, with potential relevance to mission-critical DoD installation resilience. Projected increases in ROS frequency and permafrost degradation across Alaska further emphasize the need to integrate physics-based hydrologic models that explicitly represent snow and permafrost processes to enhance design resilience and operational readiness for military and other critical infrastructure.

Yan, Hongxiang (ORCID:000000022387403X)↗
DOE OSTI2023

Anthropogenic uranium signatures in turtles, tortoises, and sea turtles from nuclear sites

Chelonians (turtles, tortoises, and sea turtles) grow scute keratin in sequential layers over time. Once formed, scute keratin acts as an inert reservoir of environmental information. For chelonians inhabiting areas with legacy or modern nuclear activities, their scute has the potential to act as a time-stamped record of radionuclide contamination in the environment. Here, we measure bulk (i.e., homogenized scute) and sequential samples of chelonian scute from the Republic of the Marshall Islands and throughout the United States of America, including at the Barry M. Goldwater Air Force Range, southwestern Utah, the Savannah River Site, and the Oak Ridge Reservation. We identify legacy uranium ( 235 U and 236 U) contamination in bulk and sequential chelonian scute that matches known nuclear histories at these locations during the 20th century. Our results confirm that chelonians bioaccumulate uranium radionuclides and do so sequentially over time. This technique provides both a time series approach for reconstructing nuclear histories from significant past and present contexts throughout the world and the ability to use chelonians for long-term environmental monitoring programs (e.g., sea turtles at Enewetok and Bikini Atolls in the Republic of the Marshall Islands and in Japan near the Fukushima Daiichi reactors).

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Multiscale Electrothermal Design of a Modular Multilevel Converter for Grid-Tied Applications

As a key feature of modular multilevel converters (MMCs), a large number of semiconductor devices are employed in the converter and distributed over a stack of submodules. Each submodule has a strict temperature limit that imposes constraints on the operating range of the converter. Different loading conditions/losses in the submodules lead to unavoidable temperature variations inside the MMC, which consequently affect the system-level performance and reliability. This paper is focused on the electrothermal analysis and design of a medium-voltage silicon carbide (SiC)-based MMC system, from submodule power semiconductors to the overall MMC system integration of multiple submodules. Loss calculations are performed to estimate the cooling requirements and aid thermal design at different levels. The performance of forced-air cooling approach is analyzed within a numerical modeling framework. Maximum temperature of the SiC power modules is predicted using numerical tools. Thermal design of the MMC cabinet with various arrangement of air inlet(s) and outlet(s) is investigated and compared from a cooling performance perspective.

CFD↗
DOE OSTI2022

Optics-Free Chip-Scale Intraoperative Imaging Using NIR-Excited Upconverting Nanoparticles

Here we present an optics-free CMOS image sensor that incorporates a novel time-gated dual-photodiode pixel design to allow filter- and lens-less image acquisition of near-infrared-excited (NIR-excited) upconverting nanoparticles. Recent biomedical advances have highlighted the benefits of NIR excitation, but NIR interaction with silicon has remained a challenge, even with high-performance optical blocking filters. Using a secondary diode and a dual-photodiode design, this sensor is able to remove the 100s of mV of NIR background on pixels and bring it down to single-digit mV level, nearing its noise floor of 2.2 mV rms, not achievable with any optical filter. Non-linear effects of background cancellation using the diode pair has been mitigated using an initial one-time pixel-level curve fitting and calibration in a post-processing setting. This imager comprises a highly linear 11 fF metal-oxide-metal (MOM) capacitor and includes integrated angle-selective gratings to reject oblique light and enhance sharpness. Each pixel also includes two distinct correlated double sampling schemes, to remove low frequency flicker noise and systematic offset in the datapath. We demonstrate the performance of this imager using pulsed NIR-excited upconverting nanoparticles on standard United-States-Air-Force (USAF) resolution targets and achieve an SNR of 15 dB, while keeping NIR background below 6 mV. This 36-by-80-pixel array measures only 2.3 mm by 4.8 mm and can be thinned down to 25 µm, allowing it to become surgically compatible with intraoperative instruments and equipment, while remaining optics-free.

42 ENGINEERING↗
DOE OSTI2023

Multiscale Electrothermal Design of a Modular Multilevel Converter for Medium-Voltage Grid-Tied Applications

As a key feature of modular multilevel converters (MMCs), a large number of semiconductor devices are employed in the converter and distributed over a stack of submodules. Each submodule has a strict temperature limit that imposes constraints on the operating range of the converter. Different loading conditions/losses in the submodules lead to unavoidable temperature variations inside the MMC, which consequently affect the system-level performance and reliability. This paper is focused on the electrothermal analysis and design of a medium-voltage silicon carbide (SiC)-based MMC system, from submodule power semiconductors to the overall MMC system integration of multiple submodules, for grid-connected applications. Loss calculations are performed to estimate the cooling requirements and aid thermal design at different levels. The performance of a forced-air cooling approach is analyzed within a numerical modeling framework. Maximum temperature of the SiC power modules is predicted using numerical tools. Thermal design of the MMC cabinet with various arrangements of air inlet(s) and outlet(s) is investigated and compared from a cooling performance perspective. A fully resolved model of the arrangement that yields optimal results is developed to accurately predict the temperature profile of the essential components in the submodules.

computational fluid dynamics↗
DOE OSTI2021

Measured influence of overhead HVAC on exposure to airborne contaminants from simulated speaking in a meeting and a classroom

Tracer gas experiments were conducted in a 158 m 3 room with overhead supply diffusers to study dispersion of contaminants from simulated speaking in physically distanced meeting and classroom configurations. The room was contained within a 237 m 3 cell with open plenum return to the HVAC system. Heated manikins at desks and a researcher operating the tracer release apparatus presented 8-9 thermal plumes. Experiments were conducted under conditions of no forced air and neutral, cooled, or heated air supplied at 980-1100 cmh, and with/out 20% outdoor air. CO 2 was released at the head of one manikin in each experiment to simulate small (< 5 µm diameter) respiratory aerosols. The metric of exposure relative to perfectly mixed (ERM) is introduced to quantify impacts, based on measurements at manikin heads and at three heights in the center and corners of the room. Chilled or neutral supply air provided good mixing with ERMs close to one. Thermal stratification during heating produced higher ERMs at most manikins: 25% were ≥ 2.5 and the highest were > 5× perfectly mixed conditions. Operation of two within-zone air cleaners together moving ≥400 cmh vertically in the room provided enough mixing to mitigate elevated exposure variations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Calculation of Nuclear Reactor Cooling Tower Performance With Limited Data Streams

Monitoring of cooling tower performance in a nuclear reactor facility is necessary to ensure safe operation; however, instrumentation for measuring performance characteristics can be difficult to install and may malfunction or break down over long duration experiments. This paper describes employing a thermodynamic approach to quantify cooling tower performance, the Merkel model, which requires only five parameters, namely, inlet water temperature, outlet water temperature, liquid mass flowrate, gas mass flowrate, and wet bulb temperature. Using this model, a general method to determine cooling tower operation for a nuclear reactor was developed in situations when neither the outlet water temperature nor gas mass flowrate are available, the former being a critical piece of information to bound the Merkel integral. Furthermore, when multiple cooling tower cells are used in parallel (as would be in the case of large-scale cooling operations), only the average outlet temperature of the cooling system is used as feedback for fan speed control, increasing the difficulty of obtaining the outlet water temperature for each cell. To address these shortcomings, this paper describes a method to obtain individual cell outlet water temperatures for mechanical forced-air cooling towers via parametric analysis and optimization. In this method, the outlet water temperature for an individual cooling tower cell is acquired as a function of the liquid-to-gas ratio (L/G). Leveraging the tight tolerance on the average outlet water temperature, an error function is generated to describe the deviation of the parameterized L/G to the highly controlled average outlet temperature. The method was able to determine the gas flowrate at rated conditions to be within 3.9% from that obtained from the manufacturer’s specification, while the average error for the four individual cooling cell outlet water temperatures were 1.6 °C, -0.5 °C, -1.0 °C, and 0.3 °C.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Thermal Management System of an Outer-Rotor-Motor-Based Traction Drive With Integrated Power Electronics in its Central Cavity

Increasing power densities of electric vehicle traction drive systems necessitates combining the electric motor and the power electronics into one unit. A compact, integrated traction drive unit with fewer components also drives production costs down, enabling wider adoption of electric vehicles. However, the integration of power electronics in the electric machine is associated with challenges of designing an effective thermal management solution for the combined traction drive system. This paper focuses on the thermal management approach selected for Oak Ridge National Laboratory’s outer-rotor-motor-based integrated traction drive and evaluates its potential performance. The outer-rotor-motor configuration provided an opportunity for integration of the six-phase inverter in the available space in the central cavity of the internal stator. A cylindrical inverter enclosure with integrated coolant (water-ethylene glycol) channels in its walls was designed to enable heat removal from the power electronics. Numerical thermal-fluid modeling and initial channel/fin optimization results for the cylindrical heat sink are presented here. As permanent magnets are integrated in a high-speed (20 000 RPM) outer rotor, forced air convection provides cooling for the magnets. The magnets were segmented axially to mitigate the eddy current losses. Heat generated in the stator windings and laminations is removed by water-ethylene glycol coolant circulating in interpolar T-shape ceramic heat exchangers inserted between windings. General design concepts and numerical thermal-fluid simulations illustrating the electric motor thermal management solution are also presented.

Kekelia, Bidzina↗
DOE OSTI2021

Application of machine learning to estimate fireball characteristics and their uncertainty from infrared spectral data

Experiments or events involving high explosives (HE) can be monitored remotely by infrared (IR) sensors to gather information about the configuration or materials involved in the device. Researchers at the Air Force Institute of Technology (AFIT) developed a phenomenological model for HE fireball spectra in the IR range that allows for parameters to be extracted from Fourier transform infrared (FTIR) data. This model includes parameters tied to physical characteristics of the fireball: temperature, size, soot, and gas concentrations. Previous works have sought to recover these parameters by the fitting of either whole spectra or select wavenumber bands to this phenomenological model. Difficulties arise due to the complex relationships between the parameters to be fit. Uncertainty quantification of the estimated fireball parameters is also problematic since HE experiments do not have any ground truth information on the parameters. It is suggested that artificial neural network (ANN) based approaches may be well suited to this problem, because of their ability to capture complex and highly nonlinear relationships. As such, this work seeks to explore the efficacy of deep artificial neural networks (DNNs) for this problem of parameter recovery from spectra and to also investigate the uncertainty of recovering the fireball parameters from FTIR data. Networks are designed using the hyperparameter optimization tool Hyperopt and trained/tested on artificial data generated using the phenomenological model developed by AFIT. The results of applying the network to the artificial data set are compared to a physics-based band approach that uses a selected number of bands based on their physical properties. Information on the uncertainty of estimating parameters from remotely sensed experimental data is obtained by treating the accuracy of the DNN model on artificial data as an upper bound and by examining the impact of emissivity due to soot on parameter estimation error; the results for artificial data are likely to be optimistic as compared to recovering parameters from experimental data.

42 ENGINEERING↗
DOE OSTI2020

Synthetic Ancillary Service Generator (SynAS) v1

The balance of demand and supply in the electric power grid is a crucial element to grid reliability. While balancing is typically provided by conventional power plants, with spinning generators, distributed energy resources (DER) and especially electric vehicles (EVs) pose a great potential to provide such service. This project conducted a field demonstration at the Los Angeles Air Force Base (LA-AFB) where a fleet of mixed-use bi-directional EVs were actively participating in the California Independent System Operator (CAISO) market for frequency regulation. While participation in regulation markets is promising, a major drawback in designing control systems and assessing potential revenue is the lack of example frequency regulation signals. This project introduces an open-source dataset for 143 days of four-second regulation data, and the SynAS Python module to synthetically generate frequency regulation signals of arbitrary length.

Black, DouglasR↗
DOE OSTI2023

Modeling Exhaust-Generated Aerodynamic Pressure Loads on Airfield Matting Repair Systems

Airfield matting systems are commonly used for rapid repair of damaged runways to facilitate continuity of critical operations. Under normal service conditions, matting repair systems are subject not only to wheel loads exerted by airfield traffic but also to aerodynamic pressure loads resulting from high-speed, turbulent exhaust plumes produced by jets during taxi and take-off. Matting systems employed by the U.S. Air Force have been tested with respect to wheel loads, but probabilities of failure because of pressure loads produced by jet exhaust have not yet been established. This study presents a numerical approach for preliminary estimation of worst-case matting anchor forces resulting from exhaust-generated pressure loads. Using a two-dimensional computational fluid dynamics model, system behavior is evaluated by means of a parametric study of six system variables, of which the most significant are: (1) distance between engine and matting, (2) depth of cavity openings at matting edges, and (3) engine exhaust velocity. The results demonstrate that matting systems are likely to experience net uplift in typical service scenarios, driven by the combined effects of flow separation and cavity pressurization. Worst-case anchor pull-out forces, computed according to a tributary-area approach, are estimated to fall in the range of 130 lb (581 N) to 979 lb (4,350 N), depending on assumed load-sharing behavior among anchors and the size of the repair site. Field testing of instrumented matting systems during jet taxi and take-off sequences is recommended as the best next step toward understanding system behavior.

Engineering↗
DOE OSTI2026

Dynamic Transmission Line Switching Amid Wildfire-Prone Weather Under Decision-Dependent Uncertainty

During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multistage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for decision-dependent uncertainty, where line survival probabilities depend on usage, we employ distributionally robust optimization to model uncertainty in line survival distributions. We adapt the stochastic nested decomposition algorithm and derive a deterministic upper bound for its finite convergence. To enhance computational efficiency, we exploit the Lagrangian dual problem structure for a faster generation of Lagrangian cuts. Using realistic data from the California transmission grid, we demonstrate the superior performance of dynamic response policies against two-stage alternatives through a comprehensive case study. In addition, after solving the multistage formulation, we construct easy-to-implement policies that significantly reduce computational burden while maintaining good performance in real-time deployment. History: Accepted by Russell Bent, Area Editor for Network Optimization: Algorithms and Applications. Funding: This work was supported by the U.S. Department of Energy, Office of Electricity [Grant DE-AC02-05CH11231]. The work of R. Jiang was supported in part by the U.S. National Science Foundation, Division of Electrical, Communications and Cyber Systems [Grant ECCS-1845980] and the U.S. Air Force Office of Scientific Research [Grant FA9550-23-1-0323]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1210 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1210 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Estrada-Garcia, Juan-Alberto↗
DOE OSTI2021

Visualizing bleb mass dynamics in single cells using quantitative phase microscopy

Understanding biological responses to directed energy (DE) is critical to ensure the safety of personnel within the Department of Defense. At the Air Force Research Laboratory, we have developed or adapted advanced optical imaging systems that quantify biophysical responses to DE. One notable cellular response to DE exposure is the formation of blebs, or semi-spherical protrusions of the plasma membrane in living cells. In this work, we demonstrate the capacity of quantitative phase imaging (QPI) to both visualize and quantify the formation of membrane blebs following DE exposure. QPI is an interferometric imaging tool that uses optical path length as a label-free contrast mechanism and is sensitive to the non-aqueous mass density, or dry mass, of living cells. Blebs from both CHO-K1 and U937 cells were generated after exposure to a series of 600 ns, 21.2 kV/cm electric pulses. These blebs were visualized in real time, and their dry mass relative to the rest of the cell body was quantified as a function of time. It is our hope that this system will lead to an improved understanding of both DE-induced and apoptotic blebbing.

Steelman, Zachary A.↗
DOE OSTI2020

NNSA GenScen 2.1 Methodology

Nuclear weapons stockpile planning is a complex process. The Non-Proliferation Treaty,' New START Treaty,2 DOE/NNSA, STRATCOM, Navy, Air Force, and Executive-Branch all have objectives that drive requirements for the types and quantities of nuclear weapons, which in turn drive how nuclear weapons are designed, manufactured, tested, maintained, deployed, transported, stored, retired, and ultimately dismantled. An estimated 200 distinct individuals contribute to the development, completion, and approval of this plan. And once that plan is completed, herein called the N NSA Program of Record (POR), ensuring that the plan is feasible — that the stockpile work can get done — ensures that the Nuclear Security Enterprise (NSE) can deliver the intended nuclear force posture.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Remote Handled Hot Cell Facility and Other Research Transuranic Waste (Debris)

This acceptable knowledge (AK) Summary Report has been prepared for the Central Characterization Program (CCP) for remote-handled (RH) transuranic (TRU) waste generated and managed by Sandia National Laboratories/New Mexico (SNL/NM) in Albuquerque, New Mexico. The waste described in this report was predominately generated in the SNL/NM Hot Cell Facility (HCF) during the removal and packaging of experimental material and decontamination operations in Building 6580 at Technical Area (TA)-V. The waste stream also includes a very small amount of waste (estimated at less than 1 gram of fuel similar to that used for research at the HCF) originating from classified research at TA-I. In addition, the waste also includes secondary waste termed by SNL/NM as process generated waste (PGW), created during repackaging operations for this waste at the Auxiliary Hot Cell Facility (AHCF). The waste has been stored at the Sandia Pulsed Reactor (SPR) Dense Pack Storage Facility within TA-V or the Manzano Bunkers located at Manzano Base within Kirtland Air Force Base. All of the waste is being repackaged at the AHCF. This report was prepared in accordance with CCP-TP-005, CCP Acceptable Knowledge Documentation (Reference 1), to implement the AK requirements of DOE/WIPP-02-3214, Remote-Handled TRU Waste Characterization Program Implementation Plan (WCPIP) (Reference 2); Waste Isolation Pilot Plant Hazardous Waste Facility Permit, Waste Analysis Plan (WIPP-WAP) (Reference 3); and DOE/WIPP-02-3122, Transuranic Waste Acceptance Criteria for the Waste Isolation Pilot Plant (WIPP-WAC) (Reference 4).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Maximizing the Use of Ductless Mini-Splits in Homes with Existing Central or Zonal Heating and Cooling Equipment

In the residential retrofit application, ductless mini-split heat pumps (DHP) are often reported to hold high-energy savings potential, depending on the system they are supplementing or replacing. However, of late, there have been a number of studies and analyses indicating these energy savings are not being achieved. The primary goal of this project was to determine the most cost effective (lowest cost for the most energy saved) and persistent (e.g. automated, hard to change, etc.) solution for controlling a ductless heat pump in an existing home with central forced air furnace. Various control strategies were tested at the Pacific Northwest National Laboratory Lab Homes to compare the energy savings between the different energy efficient control strategies. A maximum of 40% energy savings was realized by using the ductless mini-split as the primary heat source with the central air conditioning unit as the secondary source.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗