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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-Based Sensors

Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.

data processing↗
DOE OSTI2024

Multiport Converter based Auxiliary Power Supply for Heavy Duty Fuel Cell Power Train

This paper presents a multiport converter (MPC) based power supply to charge the 12 V and 24 V auxiliary batteries in heavy duty (HD) fuel cell (FC) electric vehicle (EV) power train. Compared to conventional auxiliary power supply architectures, the proposed architecture shares the power electronic components of the main power train yet preserves the isolation and all other desirable features of auxiliary power supplies. The proposed auxiliary power supply architecture reduces the requirements of the devices, gate drivers and thermal requirements thereby having potential benefits towards improving the power density, cost and weight of the overall power train. The topology, design parameters and control methodology are discussed, and results are presented to validate the proposed architecture.

Mukherjee, Subho↗
DOE OSTI2025

A Novel Secondary Frequency Regulation with Optimal Priority Selection of AGC Contributions

Automatic generation control (AGC) is used to maintain acceptable frequencies during operation owing to fluctuations in load and variable resources. In conventional industry applications, the AGC signal is allocated to each generator according to the predispatched frequency regulation capacity or the order of economic efficiency. However, with the increasing integration of inverter-based resources (IBRs), the retirement of conventional synchronous generators (SGs) has posed new challenges to frequency control schemes because fewer of them are optional for AGC regulation. In this paper, we propose a novel model predictive control (MPC)-based frequency regulation model to reduce control cost and ensure stability, by considering different critical dynamic factors when optimally selecting the AGC units. The proposed control model – developed in a general form – comprehensively embeds characteristics such as generator ramping rates, reserve capacity, and operation cost. The model predictive control–based two-timescale AGC scheme enhances the capability of immunizing the power disturbance from types of resources by coordinating the control signals between faster IBRs and slower SGs. The case study’s proposed model is verified to be effective in synergistically enforcing different dynamic properties of AGC units into the frequency regulation scheme.

Jiang, Sufan [The University of North Carolina at ↗
DOE OSTI2025

Coordination of Energy Storage and Distributed Generation for Voltage Control and Peak-valley Filling

The increasing penetration of distributed energy resources (DERs) in distribution network (DN) poses challenges on voltage control. In addition, the growing integration of DERs also reshapes the traditional load profile. To comprehensively address the voltage control and peak-valley filling in DN, this paper proposes a model predictive control (MPC) based optimization framework. The proposed method can achieve coordinated voltage control and peak-valley filling by adjusting the reactive power output from distributed generations (DGs) and the charging/discharging of energy storage systems (ESS). The performance of the proposed method is demonstrated by simulations on a modified IEEE-123 bus system.

Zhang, Zhengfa [University of Tennessee, Knoxville↗
DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗
DOE OSTI2025

Flexible Resource Scheduler for FAST-DERMS (FRS-FASTDERMS) v0.9

The Flexible Resource Scheduler is a hierarchical controller that manages the distributed energy resources in a distribution substation or distribution feeder to provide a firm commitment of power flow at the substation or feeder head to be scheduled in transmission-level markets as an aggregated demand resource. It is the reference controller for the FAST-DERMS Architecture, developed in tandem with the architecture under the DOE FAST-DERMS project. It is comprised of a day-ahead stochastic optimization, which schedules substation power flow and reserves, a intra-hour MPC, which generates dispatch base points for DER, and a real-time PID controller maintaining that dispatches DER to maintain the substation power around the base points. The repository also includes a representative aggregator controller, and all of the necessary components to run a simulation using PNNL's GridAPPS-D software with the controller.

MacDonald, Jason [Lawrence Berkeley National Labor↗
DOE OSTI2026

Spectral broadening and compression of picosecond pulses in air using a multi-pass cell

We report the spectral broadening and post-compression of picosecond pulses using a multi-pass cell (MPC) operating in air. A 2 m-long bi-concave cavity with 41 reflections and 96.4% transmission was designed and implemented, optimized for the compression of 5.5 ps, 4.5 mJ pulses from a Yb:YAG laser operating at 1030 nm. A 19.3-fold spectral broadening was obtained, increasing the bandwidth from 0.3 nm to 5.8 nm, which enabled pulse compression down to 547 fs with a symmetric temporal profile close to the transform limit. These results demonstrate the feasibility of using open-air MPCs for high-energy picosecond pulse post-compression, without the need for sealed chambers, while preserving high mode quality and transmission. Scaling to pulse higher energy is discussed.

Zaldivar Escola, F. [Univ. of Buenos Aires (Argent↗
DOE OSTI2025

Establishing an Early CO 2 Storage Complex in Kemper County, Mississippi: Project ECO 2 S (Phase III) (Final Progress Report)

“Establishing an Early CO 2 Storage Complex in Kemper County, Mississippi (Project ECO 2 S)” is an early mover project within the U.S. Department of Energy (DOE) and National Energy Technology Laboratory’s Carbon Storage Assurance Facility Enterprise, or CarbonSAFE, initiative. Phase III of Project ECO2S advanced the foundational work of Phase II, which confirmed the potential for safely, permanently, and economically storing commercial volumes of carbon dioxide (CO 2 ) in the regionally significant saline reservoir system near Mississippi Power Company’s (MPC) Kemper County Energy Facility. The primary objective of Phase III was to complete detailed site characterization necessary to obtain an Underground Injection Control (UIC) Class VI Permit to Construct from the U.S. Environmental Protection Agency. This involved transitioning from regional geologic assessments to high-resolution site-specific analyses.

03 NATURAL GAS↗
DOE OSTI2026

Community Resilience Through Rapid Restoration Leveraging Distributed Energy Resources (DERs) and Low-Cost Sensors

Equitable and automated bottoms-up power restoration following an extreme event will be demonstrated at a site in Puerto Rico. To do so, the team will develop enhanced grid situational awareness techniques integrating behind-the-meter (BTM) distributed energy resources (DER) discovery, impedance sweeping based outage boundary detection, and feasible restoration path identification algorithms. Resilience metric will be developed and incorporated along with situational awareness information in a distributed Model Predictive Control (MPC)-based restoration optimization algorithm to control and mobilize grid assets. These algorithms will be validated through power hardware-in-the-loop experiments and ultimately, a site demonstration to show that outage recovery time and total recovered load could be improved by >20% over the baseline.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations

We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the Illustris-TNG suite. We create an HOD mock with Illustris-like correlations using our method, constraining the associated IA model parameters, with the $\mathcal{X}$$^{2}_{dof}$ between our model’s correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation–position and orientation–orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to 0.1 $\mathcal{h}$ –1 Mpc. We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Computing Nonlinear Power Spectra Across Dynamical Dark Energy Model Space with Neural ODEs

I show how to compute the nonlinear power spectrum across the entire $w(z)$ dynamical dark energy model space. Using synthetic ΛCDM data, I train a neural ordinary differential equation (ODE) to infer the evolution of the nonlinear matter power spectrum as a function of the background expansion and mean matter density across ∼9 Gyr of cosmic evolution. After training, the model generalises to any dynamical dark energy model parameterised by $w(z)$. With little optimisation, the neural ODE is accurate to within 4% up to $k = 5\, h\, {\mathrm Mpc}^{−1}$. Unlike simulation rescaling methods, neural ODEs naturally extend to summary statistics beyond the power spectrum that are sensitive to the growth history.

cosmology↗
DOE OSTI2026

Constraining the Stellar-to-Halo Mass Relation with Galaxy Clustering and Weak Lensing from DES Year 3 Data

We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing measurements. We model a wide range of scales, roughly from $\sim 100 \; {\rm kpc}$ to $\sim 100 \; {\rm Mpc}$, using a theoretical framework based on the Halo Occupation Distribution and data from Year 3 of the Dark Energy Survey (DES) dataset. The new advances of this work include: 1) the generation and validation of a new stellar mass-selected galaxy sample in the range of $\log M_\star/M_\odot \sim 9.6$ to $\sim 11.5$; 2) the joint-modeling framework of galaxy clustering and galaxy-galaxy lensing that is able to describe our stellar mass-selected sample deep into the 1-halo regime; and 3) stellar-to-halo mass relation (SHMR) constraints from this dataset. In general, our SHMR constraints agree well with existing literature with various weak lensing measurements. We constrain the free parameters in the SHMR functional form $\log M_\star (M_h) = \log(εM_1) + f\left[ \log\left( M_h / M_1 \right) \right] - f(0)$, with $f(x) \equiv -\log(10^{αx}+1) + δ[\log(1+\exp(x))]^γ/ [1+\exp(10^{-x})]$, to be $\log M_1 = 11.506^{+0.325}_{-0.404}$, $\log ε= -1.632^{+0.306}_{-0.181}$, $α= -1.638^{+0.108}_{-0.099}$, $γ= 0.596^{+0.251}_{-0.210}$ and $δ= 3.810^{+2.045}_{-1.811}$. The inferred average satellite fraction is within $\sim 5-35\%$ for our fiducial results and we do not see any clear trends with redshift or stellar mass. Furthermore, we find that the inferred average galaxy bias values follow the generally expected trends with stellar mass and redshift. Our study is the first SHMR in DES in this mass range, and we expect the stellar mass sample to be of general interest for other science cases.

Zacharegkas, G. [Argonne; Chicago U., KICP] (ORCID↗
DOE OSTI2024

Filaments of the Slime Mold Cosmic Web and How They Affect Galaxy Evolution

Abstract We present a novel approach for identifying cosmic web filaments within theDisPerSEstructure identification framework, using cosmic density field estimates from the Monte Carlo Physarum Machine (MCPM), inspired by the slime mold organism. We apply our method to the IllustrisTNG (TNG100) cosmological simulations and investigate the impact of filaments on galaxies. The MCPM density field is superior to the Delaunay tessellation field estimator in tracing the true underlying matter distribution and allows filaments to be identified with higher fidelity, finding more low-prominence/diffuse filaments. Using our new filament catalogs, we find that ≳90% of galaxies are located within ∼1.5 Mpc of a filamentary spine, with little change in the median star formation activity with distance to the nearest filament. Instead, we uncover a differential effect of the local filament line density, Σ fil (MCPM)—the total MCPM overdensity per unit length along a filament segment—on galaxy formation: most galaxies are quenched and gas-poor near high-line density filaments atz≤ 1. At earlier times, the filamentary environment appears to have no effect on galactic gas supply and quenching. Atz= 0, quenching in log ( M * / M ⊙ ) ≳ 10.5 galaxies is mainly driven by mass, while lower-mass galaxies are significantly affected by the filament line density. Satellites are far more susceptible to filaments than centrals. The local environments of massive halos are not sufficient to account for the effect of filament line density on gas removal and quenching. Our new approach holds great promise for observationally identifying filaments from galaxy surveys such as SDSS and DESI.

Astronomy & Astrophysics↗
DOE OSTI2024

The SAGA Survey. III. A Census of 101 Satellite Systems around Milky Way–mass Galaxies

We present Data Release 3 (DR3) of the Satellites Around Galactic Analogs (SAGA) Survey, a spectroscopic survey characterizing satellite galaxies around Milky Way (MW)-mass galaxies. The SAGA Survey DR3 includes 378 satellites identified across 101 MW-mass systems in the distance range of 25–40.75 Mpc, and an accompanying redshift catalog of background galaxies (including about 46,000 taken by SAGA) in the SAGA footprint of 84.7 deg 2 . The number of confirmed satellites per system ranges from zero to 13, in the stellar mass range of 10 6−10 M ⊙ . Based on a detailed completeness model, this sample accounts for 94% of the true satellite population down to M ⋆ = 10 7.5 M ⊙ . We find that the mass of the most massive satellite in SAGA systems is the strongest predictor of satellite abundance; one-third of the SAGA systems contain LMC-mass satellites, and they tend to have more satellites than the MW. The SAGA satellite radial distribution is less concentrated than the MW's, and the SAGA quenched fraction below 10 8.5 M ⊙ is lower than the MW's, but in both cases, the MW is within 1σ of SAGA system-to-system scatter. SAGA satellites do not exhibit a clear corotating signal as has been suggested in the MW/M31 satellite systems. Although the MW differs in many respects from the typical SAGA system, these differences can be reconciled if the MW is an older, slightly less massive host with a recently accreted LMC/SMC system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine Learning and Simulations

We introduce the DaRk mattEr and Astrophysics with Machine learning and Simulations (DREAMS) project, an innovative approach to understanding the astrophysical implications of alternative dark matter (DM) models and their effects on galaxy formation and evolution. The DREAMS project will ultimately comprise thousands of cosmological hydrodynamic simulations that simultaneously vary over DM physics, astrophysics, and cosmology in modeling a range of systems—from galaxy clusters to ultra-faint satellites. Such extensive simulation suites can provide adequate training sets for machine-learning-based analyses. This paper introduces two new cosmological hydrodynamical suites of warm dark matter (WDM), each comprising 1024 simulations generated using the arepo code. One suite consists of uniform-box simulations covering a ${(25\,{h}^{-1}\,{\rm{Mpc}})}^{3}$ volume, while the other consists of Milky Way zoom-ins with sufficient resolution to capture the properties of classical satellites. For each simulation, the WDM particle mass is varied along with the initial density field and several parameters controlling the strength of baryonic feedback within the IllustrisTNG model. We provide two examples, separately utilizing emulators and convolutional neural networks, to demonstrate how such simulation suites can be used to disentangle the effects of DM and baryonic physics on galactic properties. The DREAMS project can be extended further to include different DM models, galaxy formation physics, and astrophysical targets. In this way, it will provide an unparalleled opportunity to characterize uncertainties on predictions for small-scale observables, leading to robust predictions for testing the particle physics nature of DM on these scales.

cosmological parameters↗
DOE OSTI2025

The NGC 3109 Satellite System: The First Systematic Resolved Search for Dwarf Galaxies Around an SMC-mass Host

We report the results of the deepest search to date for dwarf galaxies around NGC 3109, a barred spiral galaxy with a mass similar to that of the Small Magellanic Cloud (SMC), using a semiautomated search method. Using the Dark Energy Camera, we survey a region covering a projected distance of ∼70 kpc of NGC 3109 (D = 1.3 Mpc, R vir ∼ 90 kpc, M ∼ 10 8 M*) as part of the MADCASH and DELVE-DEEP programs. We introduce a newly developed semiresolved search method, used alongside a resolved search, to identify crowded dwarf galaxies around NGC 3109. Using both approaches, we successfully recover the known satellites Antlia and Antlia B. We identified a promising candidate, which was later confirmed to be a background dwarf through deep follow-up observations. Our detection limits are well defined, with the sample ∼80% complete down to M V ∼ −8.0, and include detections of dwarf galaxies as faint as M V ∼ −6.0. This is the first comprehensive study of a satellite system through resolved stars around an SMC mass host. Our results show that NGC 3109 has more bright (M V ∼ −9.0) satellites than the mean predictions from cold dark matter models, but well within the host-to-host scatter. A larger sample of LMC/SMC-mass hosts is needed to test whether or not the observations are consistent with current model expectations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DELVE-DEEP Survey: The Faint Satellite System of NGC 55

We report the first comprehensive census of the satellite dwarf galaxies around NGC 55 (2.1 Mpc) as a part of the DECam Local Volume Exploration DEEP (DELVE-DEEP) survey. NGC 55 is one of four isolated, Magellanic analogs in the Local Volume around which DELVE-DEEP aims to identify faint dwarfs and other substructures. We employ two complementary detection methods: one targets fully resolved dwarf galaxies by identifying them as stellar overdensities, while the other focuses on semiresolved dwarf galaxies, detecting them through shredded unresolved light components. As shown through extensive tests with injected galaxies, our search is sensitive to candidates down to M V ≲ −6.6 and surface brightness μ ≲ 28.5 mag arcsec 2 , and ∼80% complete down to M V ≲ −7.8. We do not report any new confirmed satellites beyond two previously known systems, ESO 294–010 and NGC 55-dw1. We construct the satellite luminosity function of NGC 55 and find it to be consistent with the predictions from cosmological simulations. As one of the first complete luminosity functions for a Magellanic analog, our results provide a glimpse of the constraints on low-mass-host satellite populations that will be further explored by upcoming surveys, such as the Vera C. Rubin Observatory’s Legacy Survey of Space and Time.

Medoff, Jonah [Univ. of Chicago, IL (United States↗