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DOE OSTI2018

Longitudinal Beam-Shaping Simulation for Enhanced Transformer Ratio in Beam-Driven Accelerators

A beam-driven structure wakefield accelerator (SWFA) is currently under consideration for future multi-user Xray free-electron-laser (FEL) light sources. One of the challenges associated with SWFA is the efficient energy transfer from the drive to the main bunch that can be enhanced via a precise control over the drive-bunch current profile. This paper discusses the development and initial beam-dynamics simulation of the drivebunch longitudinal dynamics using the fast-tracking program TWICE. This code, written in PYTHON, allows for rapid prototyping of the beam shaping process while taking into account the collective effects using simplified models. This paper describes the algorithm implementation and its capabilities of including collective effects into both forward and backward tracking. Initial results of optimizing beam shape with a conventional linac to produce a drive beam with a shape optimized for SFWA are presented.

43 PARTICLE ACCELERATORS↗

DOE OSTI2017

Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and upper bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.

14 SOLAR ENERGY↗

DOE OSTI2017

CXSFIT Code Application to Process Charge-Exchange Recombination Spectroscopy Data at the T-10 Tokamak

The applicability of the CXSFIT code to process experimental data from Charge-eXchange Recombination Spectroscopy (CXRS) diagnostics at the T-10 tokamak is studied with a view to its further use for processing experimental data at the ITER facility. The design and operating principle of the CXRS diagnostics are described. The main methods for processing the CXRS spectra of the 5291-Å line of C{sup 5+} ions at the T-10 tokamak (with and without subtraction of parasitic emission from the edge plasma) are analyzed. The method of averaging the CXRS spectra over several shots, which is used at the T-10 tokamak to increase the signal-to-noise ratio, is described. The approximation of the spectrum by a set of Gaussian components is used to identify the active CXRS line in the measured spectrum. Using the CXSFIT code, the ion temperature in ohmic discharges and discharges with auxiliary electron cyclotron resonance heating (ECRH) at the T-10 tokamak is calculated from the CXRS spectra of the 5291-Å line. The time behavior of the ion temperature profile in different ohmic heating modes is studied. The temperature profile dependence on the ECRH power is measured, and the dynamics of ECR removal of carbon nuclei from the T-10 plasma is described. Experimental data from the CXRS diagnostics at T-10 substantially contribute to the implementation of physical programs of studies on heat and particle transport in tokamak plasmas and investigation of geodesic acoustic mode properties.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Changing temperature profiles and the risk of dengue outbreaks

As temperatures change worldwide, the pattern and competency of disease vectors will change, altering the global distribution of both the burden of infectious disease and the risk of the emergence of those diseases into new regions. To evaluate the risk of potential summer dengue outbreaks triggered by infected travelers under various climate scenarios, we develop an SEIR-type model, run numerical simulations, and conduct sensitivity analyses under a range of temperature profiles. Our model extends existing theoretical frameworks for studying dengue dynamics by introducing temperature dependence of two key parameters: the mosquito extrinsic incubation period and the lifespan of mosquitoes, which empirical data suggests are both highly temperature dependent. We find that changing temperature significantly alters dengue risk in an inverted U-shape, with temperatures in the range 27-31°C producing the highest risk. As temperatures increase beyond 31°C, the determinants of dengue risk begin to shift from mosquito biting rate and carrying capacity to the duration of the human infectious period, suggesting that changing temperatures not only alter dengue risk but also the potential efficacy of control measures. To illustrate the role of spatial and temporal temperature heterogeneity, we select five US cities where the primary dengue vector, the mosquito Aedes aegypti , has been observed, and which have had dengue cases in the past: Los Angeles, Houston, Miami, Brownsville, and Phoenix. Our analysis suggests that an increase of 3°C leads to an approximate doubling of the risk of dengue in Los Angeles and Houston, but a reduction of risk in Miami, Brownsville, and Phoenix due to extreme heat.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

FK COMAE BERENICES, KING OF SPIN: THE COCOA-PUFS PROJECT

COCOA-PUFS is an energy-diverse, time-domain study of the ultra-fast spinning, heavily spotted, yellow giant FK Comae Berenices (FK Com: HD117555; G4 III). This single star is thought to be a recent binary merger, and is exceptionally active by measure of its intense ultraviolet (UV) and X-ray emissions, and proclivity to flare. COCOA-PUFS was carried out with the Hubble Space Telescope in the UV (1200–3000 Å), using mainly its high-performance Cosmic Origins Spectrograph, but also high precision Space Telescope Imaging Spectrograph; Chandra X-ray Observatory in the soft X-rays (0.5–10 keV), utilizing its High-Energy Transmission Grating Spectrometer; together with supporting photometry and spectropolarimetry in the visible from the ground. This is an introductory report on the project. FK Com displayed variability on a wide range of timescales over all wavelengths during the week-long main campaign, including a large X-ray flare; “super-rotational broadening” of the far-ultraviolet “hot lines” (e.g., Si iv 1393 Å; 8 × 10{sup 4} K) together with chromospheric Mg ii 2800 Å and C ii 1335 Å (1–3 × 10{sup 4} K); large Doppler swings suggestive of bright regions alternately on advancing and retreating limbs of the star; and substantial redshifts of the epoch-average emission profiles. These behaviors paint a picture of a highly extended, dynamic, hot (∼10 MK) coronal magnetosphere around the star, threaded by cooler structures perhaps analogous to solar prominences and replenished continually by surface activity and flares. Suppression of angular momentum loss by the confining magnetosphere could temporarily postpone the inevitable stellar spindown, thereby lengthening this highly volatile stage of coronal evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Multi-fluid Modeling of Magnetosonic Wave Propagation in the Solar Chromosphere: Effects of Impact Ionization and Radiative Recombination

In order to study chromospheric magnetosonic wave propagation including, for the first time, the effects of ion–neutral interactions in the partially ionized solar chromosphere, we have developed a new multi-fluid computational model accounting for ionization and recombination reactions in gravitationally stratified magnetized collisional media. The two-fluid model used in our 2D numerical simulations treats neutrals as a separate fluid and considers charged species (electrons and ions) within the resistive MHD approach with Coulomb collisions and anisotropic heat flux determined by Braginskiis transport coefficients. The electromagnetic fields are evolved according to the full Maxwell equations and the solenoidality of the magnetic field is enforced with a hyperbolic divergence-cleaning scheme. The initial density and temperature profiles are similar to VAL III chromospheric model in which dynamical, thermal, and chemical equilibrium are considered to ensure comparison to existing MHD models and avoid artificial numerical heating. In this initial setup we include simple homogeneous flux tube magnetic field configuration and an external photospheric velocity driver to simulate the propagation of MHD waves in the partially ionized reactive chromosphere. In particular, we investigate the loss of chemical equilibrium and the plasma heating related to the steepening of fast magnetosonic wave fronts in the gravitationally stratified medium.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Developing Fuel Cell Electric Powertrain Architectures for Commercial Vehicles

Here, this article addresses the architecture development for a commercial vehicle fuel cell electric powertrain by establishing a clear multi-step formalized workflow that employs a unique technoeconomic solution for architecture selection. The power capability of the fuel cell, the energy capacity and chemistry of the electrical energy storage (battery), the DC-DC converter (including the input current rating and isolation resistance requirements), the traction drive solution, the on-board hydrogen storage solution, and the real-time power-split management of the fuel cell and the battery are all considered and developed in this effort. The methods were used to select architecture for Class 8 urban, regional, and line haul applications. When compared to traditional load-following power-split controllers, an energy management power-split controller can increase system energy efficiency by up to 19.5%. The energy-efficient power-split controller may increase the required battery capacity for an equivalent life by up to 2.6 times. The impact on the total cost of ownership (TCO) for a variety of financial cases demonstrates that high C-rate capable batteries have the potential to provide better TCO solutions over a six-year vehicle life than low C-rate capable batteries. To achieve TCO parity with the 600 A non-isolated DC-DC converter case, the specific choice of the fuel cell DC-DC converter to achieve a target power output based on current levels (from 500 A to 2400 A) shows that efficiency decreases and cost increases due to the higher current, requiring fuel cell prices to decrease by $50–$100/kW, $60–$110/kW, and $100–$220/kW for urban, regional, and line haul applications, respectively. Key recommendations for powertrain system architectures are provided, with specifics based on vehicle dynamics, mission and application characteristics, end customer use-case profile, critical powertrain component costs, and architecture selection cost function. This study rigorously demonstrates the interplay of the above parameters, with a focus on TCO, and provides application decision-makers with a mechanism and well-defined set of impact factors to consider as part of their architecture selection process.

25 ENERGY STORAGE↗

DOE OSTI2019

Fast domain-aware neural network emulation of a planetary boundary layer parameterization in a numerical weather forecast model

Abstract. Parameterizations for physical processes in weather and climate models are computationally expensive. We use model output from the Weather Research Forecast (WRF) climate model to train deep neural networks (DNNs) and evaluate whether trained DNNs can provide an accurate alternative to the physics-based parameterizations. Specifically, we develop an emulator using DNNs for a planetary boundary layer (PBL) parameterization in the WRF model. PBL parameterizations are used in atmospheric models to represent the diurnal variation in the formation and collapse of the atmospheric boundary layer – the lowest part of the atmosphere. The dynamics and turbulence, as well as velocity, temperature, and humidity profiles within the boundary layer are all critical for determining many of the physical processes in the atmosphere. PBL parameterizations are used to represent these processes that are usually unresolved in a typical climate model that operates at horizontal spatial scales in the tens of kilometers. We demonstrate that a domain-aware DNN, which takes account of underlying domain structure (e.g., nonlocal mixing), can successfully simulate the vertical profiles within the boundary layer of velocities, temperature, and water vapor over the entire diurnal cycle. Results also show that a single trained DNN from one location can produce predictions of wind speed, temperature, and water vapor profiles over nearby locations with similar terrain conditions with correlations higher than 0.9 when compared with the WRF simulations used as the training dataset.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Autonomous Navigation and Control of UGVs' in Nuclear Power Plants - 20381

The purpose of the husky A200 ground robot is to autonomously navigate through the places where it is very hazardous for human beings to reach and operate, like nuclear power plants, chemical industries. The aim is to navigate the ground robot autonomously with an Arm mounted on the robot along with the different sensors as camera, and Lidar. The autonomous motion of the robot is controlled by the controller which uses path planner for trajectory generation of the robot. The mission planner uses the current position of the husky A200, given the way points of the initial and the destination it would extract a best possible route based on the current events provided using GMapping. The global reference frame is used for planning the way points. Creating the appropriate path and the actions required to follow the path are given by the motion planner. The motion planner depends on the active sensor data such as obstacles, lanes, based on the sensor data feasible path is generated. Feasibility of the path is determined by the dynamics of the husky and a series of points generated with certain velocity and acceleration profile. The controller adjusts the lateral, longitudinal and yaw motion of the husky to command the behaviors. The kinematic model is developed for kinematic motion of the husky and the dynamic model is developed for transient and steady state characteristics. The images and other type of data captured by the camera are processed through the computational framework used to build machine learning models. TensorFlow will be used for deep learning and to identify and classify different objects around the husky. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Combined TDLAS and chemiluminescence imaging in a flat flame burner operated with NH3/H2 blends

Ammonia is a promising hydrogen carrier due to its favorable storage and transport characteristics. However, its direct use in combustion systems is limited by low flammability and potential for high nitrogen oxide emissions. To better understand ammonia combustion, researchers conducted experiments using a flat flame burner and measured species profiles using tunable-diode-laser-absorption-spectroscopy and chemiluminescence imaging. They tested three flame conditions with different ammonia-hydrogen blends and oxygen levels. The results were compared to simulations using various kinetic mechanisms, including one that accounts for excited species chemistry. The goal is to provide direct information about species profiles in a simple system, isolating chemical kinetics from fluid dynamic effects, which can inform the development of more efficient and low-emission combustion systems using ammonia.

ammonia combustion↗

DOE OSTI2026

Will cities keep getting hotter? The interplay of urban expansion and greening reshapes future urban heat trajectories

Urban heat islands (UHIs) pose growing risks to public health, infrastructure, and resilience. While often assumed to intensify with urban growth, dynamic changes in urban expansion and vegetation greenness complicate UHI trajectories, which remain poorly understood. This study investigated the interplay of urban expansion and greenness change on UHI spatial profile across 36 Chinese megacities during 2003–2018 using multiple satellite products. We introduce a framework that classifies urban areas into four dynamic development pathways based on impervious surface area (ISA) and enhanced vegetation index (EVI) trends: urbanized-greening, urbanized-browning, urbanizing-greening (UingG), and urbanizing-browning (UingB). While most urbanized centers exhibited greening driven by targeted initiatives and urbanizing suburbs showed browning due to vegetation loss, about 30% urban areas showed the reverse pattern, revealing overlooked complexity in urban development. Urban expansion and browning strengthened UHI in suburban areas, whereas greening initiatives mitigated UHI in urban center and mitigated UHI enhancement in suburban areas. Slowed warming in urban centers together with accelerated warming in suburban areas flattened the temperature gradient between urban centers and suburbs. This dynamic expanded the spatial extent of elevated temperatures and reshaped the classic urban-to-rural UHI profile into a flatter form. In UingB areas, UHI intensification was jointly driven by increase in ISA, vegetation loss, and their interaction, while in UingG areas, EVI increases and a negative interaction together offset over half of the warming driven by urban expansion. These findings reveal that UHI evolution is not unidirectional but depends on localized urbanization and greening dynamics, offering pathways for strategic heat mitigation.

greening initiative↗

DOE OSTI2026

Influence of conical wire array geometry on plasma flow and temperature profiles of radiatively cooled jets

The influence of conical wire array geometry on the formation and dynamics of pulsed-power driven plasma jets is investigated. In the experiments, the jet becomes isolated from the inflows as it passes through an aperture, allowing the study of its intrinsic evolution for different conical angles. Here, our results show that, regardless of the array opening angle, the jets are supersonic, highly collisional, and exhibit an exponential axial density decay with a characteristic scale length of 𝐿 𝑛 ≈ 3 mm, significantly shorter than the overall length of the jet. In contrast, axial velocity systematically increases with larger array opening angles. The near invariance of the density profile is attributed to a compensating mechanism between geometric divergence and axial acceleration, consistent with an asymptotically steady flow regime. Additionally, temperature measurements reveal ion-electron thermal decoupling near the base of the jet, with equilibration downstream. Analysis of radiative cooling and collisional energy exchange timescales indicates that the plasma evolves in a radiatively stable regime and that the two-temperature profile is fully described by the competition between both methods. These findings provide valuable information into the internal structure and evolution of pulsed-power plasma jets in regimes dominated by geometric shaping and radiative cooling, demonstrating experimental control over flow acceleration and collimation relevant to both laboratory and astrophysical contexts.

Physics - Plasma physics↗

DOE OSTI2020

Scaling Turbulent Combustion Fields in Explosions

We considered the topic of explosions from spherical high-explosive (HE) charges. We studied how the turbulent combustion fields scale. On the basis of theories of dimensional analysis by Bridgman and similarity theories of Sedov and Barenblatt, we found that all fields scaled with the explosion length scale r0. This included the blast wave, the mean and root mean squared (RMS) profiles of thermodynamic variables, combustion variables, velocities, vorticity, and turbulent Reynolds stresses. This was a consequence of the formulation of the problem and our numerical method, which both satisfied the similarity conditions of Sedov. We performed numerical simulations of 1 g charges and 1 kg charges; the solutions were identical (within roundoff error) when plotted in scaled variables. We also explored scaling laws related to three-phase pyrotechnic explosions. We show that although the scaling formally broke down, the fireball still essentially scaled with the explosion length scale r0. However, the discrete Lagrange particles (DLP) (phase 2) and the heterogeneous continuum model (HCM) of the DLP wakes (phase 3) did not scale with r0, and mean and RMS profiles could differ by a factor of 10 in some regions. This was because the DLP particles and wakes introduced an additional scale that broke the similarity conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Cuticular wax profiling of Populus trichocarpa and P. balsamifera reveals surface similarities with underlying differences

Cuticular waxes are a mixture of hydrophobic components protecting plant tissues from the environment. Populus trichocarpa and P. balsamifera are closely-related tree species with broad North American distribution; however, variation in their cuticular wax composition across their range remained poorly understood. To address this gap, stem and leaf waxes from both species across three developmental stages were profiled by gas chromatography-mass spectrometry. A core set of compounds shared across tissues, accessions, and developmental stages was detected, as well as tissue- or species-specific constituents such as phenolics and alkenes. Phenolic-derived compounds were more prevalent at early stages of development compared to the predominantly aliphatic composition of mature tissues. Moreover, early stage leaves also showed enhanced protection from desiccation and oxidative stress in a subset of accessions. Alkenes, found exclusively in leaves, segregated the poplar accessions into alkene-producing and alkene-lacking phenotypes. GWAS analysis of 174 P. trichocarpa accessions identified a region on chromosome 10 containing a tandem cluster of ketoacyl CoA synthases associated with alkene accumulation in P. trichocarpa , which was not significantly associated in 133 P. balsamifera individuals examined. These findings reveal dynamic, developmentally regulated, and species-specific variation in poplar wax profiles. Understanding these chemical traits offers new opportunities to develop Populus varieties with enhanced environmental resilience and adaptive potential.

GWAS↗

DOE OSTI2024

Quantitative time-resolved diagnostics of electric field dynamics during individual plasma breakdown events using burst laser pulse electric field induced second harmonic generation

In plasma discharges, the acceleration of electrons by a fast varying electric field and the subsequent collisional electron energy transfer determines the plasma dynamics, chemical reactivity, and breakdown. Current in situ electric field measurements require reconstruction of the temporal profile over many observations. However, such methods are unsuitable for non-repetitive and unstable plasmas. Here, in this paper, we present a method for creating “movies” of dynamic electric fields in a single acquisition at sample rates of 500 × 10 6 fps. This ultrafast diagnostic was demonstrated in radio frequency electric fields between two parallel plates in air, as well as in Ar nanosecond-pulsed single-sided dielectric barrier discharges.

42 ENGINEERING↗

DOE OSTI2023

Uncovering dark matter density profiles in dwarf galaxies with graph neural networks

Dwarf galaxies are small, dark-matter-dominated galaxies, some of which are embedded within the Milky Way. Their lack of baryonic matter (e.g., stars and gas) makes them perfect test beds for probing the properties of dark matter—understanding the spatial dark matter distribution in these systems can be used to constrain microphysical dark matter interactions that influence the formation and evolution of structures in our Universe. Here, we introduce a new method that leverages simulation-based inference and graph-based machine learning in order to infer the dark matter density profiles of dwarf galaxies from observable kinematics of stars gravitationally bound to these systems. Our approach aims to address some of the limitations of established methods based on dynamical Jeans modeling. We show that this novel method can place stronger constraints on dark matter profiles and, consequently, has the potential to weigh in on some of the ongoing puzzles associated with the small-scale structure of dark matter halos, such as the core-cusp discrepancy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Pulsed radio frequency power modulation for profile control in cryogenic reactive ion etching of silicon gratings

Cryogenic silicon etching with SF 6 /O 2 plasmas enables vertical sidewalls and smooth surfaces for high–aspect-ratio structures, yet precise control of etched profiles (sidewall angle, lateral etching, and linewidth retention) remains challenging under continuous-wave excitation due to coupling among radical fluxes, ion energy distributions, and in situ passivation dynamics. In this work, we investigated pulsed radio frequency bias delivery as a process knob for profile control during cryogenic silicon etching. Systematic experiments on 500 nm-wide, 1 μm-pitch gratings etched to 0.8–1.1 μm depth at 0.5–2 kHz pulsing frequency and 25%–75% duty cycle revealed strong dependencies of etch rate, linewidth, and sidewall angle on modulation conditions. We proposed a conceptual kinetic picture combined with feature-scale electrostatic analysis to understand the alternation of ion-driven etching and passivation recovery between on/off segments and local electric field shaping and modulation of ion trajectories within the trench. Moderate duty cycles (50%–75%) near 1 kHz achieved a balance between anisotropy and etch rate. These results demonstrate pulsed-bias modulation can be utilized to tune directionality and sidewall preservation in cryogenic SF 6 /O 2 etching, which are relevant to photonic, metrology, and quantum device fabrication.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗