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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design and Development of a Fixtureless, Pass-through Machine Tool for Extrusion Machining

The aerospace, construction/architecture, and transportation manufacturing industries rely heavily on the mass production of near-net shape metallic and composite extrusions. While the production of raw extrusions is a relatively fast process, adding functional features such as holes and slots require additional time, cost, and energy to produce. To compensate for the inherent flexibility of extrusions, conventional machining requires rigid purpose-built fixtures for operations such as trimming, drilling and thinning. This approach requires that the machine tools be as large or larger than the parts themselves. This results in the need for excess shop floor space, energy for auxiliary equipment and motion systems, and significant capital expenditure. Considerable engineering expense and time involved in the designing, building, and proving out of part-specific fixtures for holding the components in specific configurations while machining add to the overall manufacturing cost. The primary objective of the technical collaboration between Oak Ridge National Laboratory and Fairmount Technologies (FT) is to improve the XM-3, a fixtureless CNC milling machine designed by FT. The machine was developed to trim, drill, and thin extrusions without part specific fixturing to make the manufacturing process more efficient and flexible. Dynamic measurements of the existing structure were collected, and modeling efforts were made to evaluate optimal machining parameters for the current system. Areas of improvement to increase the system stiffness, manufacturability, and machining efficiency were evaluated and highlighted for the next generation design. The impact of this effort may enable agile manufacturing across the commercial and defense aerospace industries, and other industries where extrusions are utilized like in the construction, architecture, and transportation industries.

42 ENGINEERING↗
DOE OSTI2025

Design and Development of a Fixtureless, Pass-through Machine Tool for Extrusion Machining

The aerospace, construction/architecture, and transportation manufacturing industries rely heavily on the mass production of near-net shape metallic and composite extrusions. While the production of raw extrusions is a relatively fast process, adding functional features such as holes and slots require additional time, cost, and energy to produce. To compensate for the inherent flexibility of extrusions, conventional machining requires rigid purpose-built fixtures for operations such as trimming, drilling and thinning. This approach requires that the machine tools be as large or larger than the parts themselves. This results in the need for excess shop floor space, energy for auxiliary equipment and motion systems, and significant capital expenditure. Considerable engineering expense and time involved in the designing, building, and proving out of part-specific fixtures for holding the components in specific configurations while machining add to the overall manufacturing cost. The primary objective of the technical collaboration between Oak Ridge National Laboratory and Fairmount Technologies (FT) is to improve the XM-3, a fixtureless CNC milling machine designed by FT. The machine was developed to trim, drill, and thin extrusions without part specific fixturing to make the manufacturing process more efficient and flexible. Dynamic measurements of the existing structure were collected, and modeling efforts were made to evaluate optimal machining parameters for the current system. Areas of improvement to increase the system stiffness, manufacturability, and machining efficiency were evaluated and highlighted for the next generation design. The impact of this effort may enable agile manufacturing across the commercial and defense aerospace industries, and other industries where extrusions are utilized like in the construction, architecture, and transportation industries.

42 ENGINEERING↗
DOE OSTI2024

Generating synthetic signaling networks for in silico modeling studies

Predictive models of signaling pathways have proven to be difficult to develop. Reasons include the uncertainty in the number of species, the complexity in species’ interactions, and the sparseness and uncertainty in experimental data. Traditional approaches to developing mechanistic models rely on collecting experimental data and fitting a single model to that data. This approach works for simple systems but has proven unreliable for complex systems such as biological signaling networks. For example, uncertainty and sparseness of the data often result in overfitted models that have little predictive value beyond recapitulating the experimental data itself. Thus, there is a need to develop new approaches to create predictive mechanistic models of complex systems. However, to determine the effectiveness of any new algorithm, a baseline model is needed to test its performance. To meet this need, we developed a method for generating artificial synthetic networks that are reasonably realistic and thus can be treated as ground truth models. These synthetic models can then be used to generate synthetic data for developing and testing algorithms designed to recover the underlying network topology and associated parameters. Here, we describe a simple approach for generating synthetic signaling networks that can be used for this purpose.

42 ENGINEERING↗
DOE OSTI2026

Deformation of the $0^+_{1,2}$ states in 110 Cd from low-energy Coulomb excitation

Electromagnetic properties of 110 Cd were studied via low-energy Coulomb excitation with 32 S and 14 N beams. Magnitudes and relative signs of eight E2 matrix elements, including quadrupole moments of the $2^+_1$ and $2^+_2$ states, were determined using the least-squares code GOSIA. From those, quadrupole deformation parameters of the $0^+_{1,2,3}$ states were inferred, providing for the first time conclusive evidence for the non-axial character of the ground state in 110 Cd. The experimental results were compared with new calculations using the general quadrupole collective Bohr Hamiltonian model with SLy4 and UNEDF0 interactions. The non-axiality of the ground state is reproduced by the present calculations, independently of the interaction used.

Collective models↗
DOE OSTI2026

1994 SEMCOG Household-Based Person Trip Survey

The Southeast Michigan Council of Governments contracted with the Applied Management & Planning Group to conduct a travel behavior survey of 7,361 households from March 28, 1994, to June 10, 1994. The primary purpose of this study was to provide the council with a new database of travel behavior to assist in updating the region's transportation models. This data collection includes demographic, socioeconomic, travel, and mobile source emissions models for projecting future patterns of development, travel, congestion, and air pollution. Information about household characteristics and travel was collected using a one-day, activity-focused diary and a separate household survey. In an activity diary, respondents recorded 65,535 trips during the assigned the day.

1Hz data↗
DOE OSTI2026

Simplifying Geospatial Workflows with GeoGridFusion

Growing demands to understand PV deployment and reliability across an expanding range of climates, along with increasing computational power, are driving the need for simplified computing tools that support large-scale analysis and geospatial workflows. While existing open-source libraries and PV system modeling tools offer extensive collections of empirical and physical models, they often lack the ability to scale to large geospatial datasets. The tool presented here, GeoGridFusion, enables PV modelers to store and utilize gridded geospatial data from sources such as NSRDB, PVGIS, and others. GeoGridFusion harmonizes diverse datasets, taxonomies, and nomenclatures, and includes utilities that support intuitive geospatial area selection.

14 SOLAR ENERGY↗
DOE OSTI2026

Optimization and stabilization of Fermilab Booster using hybrid Bayesian/RL framework

PIPII project will raise Fermilab Booster intensity and ramp rate. Beam losses will limit average power and are hard to simulate. Presently, Booster uses operator-guided empirical tuning. This task is challenging due to high dimensionality, multiple objectives, critical safety constraints, and drifts. We developed a synergistic suite of Bayesian optimization (BO) and reinforcement learning (RL) tools to optimize and stabilize beam losses. First, active learning was used to build a rough model. Data was collected parasitically using two novel safety constraint types – nonlinear input space restrictions (based on optics model), and uncertainty constraints (to stop bad steps/beam aborts). We then applied online multi-objective BO with scalarized objectives and fitting to improve/rebalance losses, increasing safety margins by 25%. Using BO model as a safety veto, we tried several on/off-policy RL agents for long term stabilization; SAC had best performance. We found that adding contextual (state) information further improved performance, eventually integrating key knobs like linac phase and temperature into the parameter space. Long term testing is ongoing to enable operational use.

Kuklev, Nikita [Fermilab]↗
DOE OSTI2026

Machine Learning Based Metamodel for Faster Life Cycle Assessment of Large Portfolio of Buildings

Managing a large portfolio of buildings involves decisions on reuse, retrofit, renovation, rehabilitation, and new construction, influenced by trade-offs between performance metrics such as cost, time, and operational flexibility over the building's life cycle. Traditional life cycle assessment tools for evaluating these metrics can be labor- and compute-intensive, requiring extensive data and modeling for each building. Metamodels (or surrogate models) using machine learning have been explored as faster alternatives, but training these models has been hindered by the limited availability of comprehensive data on key life cycle metrics. Recent advancements in machine learning, particularly deep learning techniques like zero-shot and few-shot learning, allow models to learn from sparse or limited data. We propose a machine learning-based metamodel that leverages these techniques for rapid estimation of key building life cycle metrics. This presentation will cover the model architecture, data collection, training, and validation processes, along with an ongoing case study applied to a large portfolio of buildings. We will discuss the model's performance in terms of accuracy, compute time, limitations, and its potential for expanding to additional life cycle metrics. This data-driven approach offers a promising direction for the rapid evaluation of large building portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Juvenile Salmon and Their Habitats in the Columbia River Estuary: A Review and Synthesis of Knowledge Development 2000–2025

[This is a 90% discussion draft.] This is the third Synthesis Memorandum funded by the U.S. Army Corps of Engineers and developed for the Columbia Estuary Ecosystem Restoration Program (CEERP) on the topic of habitat restoration in the Columbia River Estuary (CRE) from Bonneville Dam to the river mouth. While the first two were developed by PNNL and NOAA without the benefit of stakeholder participation, for the current memo, two key activities were initiated: (1) review, by the Expert Regional Technical Group (ERTG), of status and trends monitoring and action effectiveness monitoring funded by CEERP, and (2) a workshop including representatives of the Bonneville Power Administration and the U.S. Army Corps of Engineers (the action agencies [AAs]), the National Oceanic and Atmospheric Administration (NOAA), major research agencies contributing to CEERP, and sponsors who implement CEERP restoration actions. A systematic literature review was conducted using ClarivateTM Web of ScienceTM database. The topics of interest for CRE relevant research included salmon ecology, physical processes, and wetland habitats, and therefore required the use of broad search terms. Our final search criteria included a combination of Boolean operators and an approach to combine different sets of search terms. The final search result yielded 669 records. The records were classified by groups and assigned to the relevant disciplinary expert for review. The review identified substantive advances in understanding the provision of salmon habitat functions through spatiotemporally dynamic physical and ecological processes, and the use of CRE habitats by numerous stocks of juvenile salmon. It also uncovered heretofore unincorporated historical documentation of riparian habitats across the CRE. The characterization of the structural components of floodplain habitat including plant associations and channel networks has advanced considerably, together with the understanding of seasonal changes and long-term trends. The relative influence of salmon-habitat location in the CRE as compared with temporal factors, mainly season, has been well described, which affects the prioritization of restoration. Stressors on the ecosystem and fish, and the drivers of these stressors, have been more carefully elucidated and predictive models are in various stages of development. The vision, aims, and design of restoration projects have advanced together with methods of data collection, analysis, and modeling that have seen substantial improvements. Experiments intended to inform the design of restoration projects are underway or have been completed. An important outstanding area of research that has lagged behind the advances in fundamental understanding of the ecosystem and salmon habitat functions remains the peer-reviewed documentation of the outcomes of restoration for both habitats and fish functions.

estuary↗
DOE OSTI2025

Selection function of clusters in Dark Energy Survey year 3 data from cross-matching with South Pole Telescope detections

Context. Galaxy clusters selected based on overdensities of galaxies in photometric surveys provide the largest cluster samples. However, modeling the selection function of such samples is complicated by noncluster members projected along the line of sight (projection effects) and the potential detection of unvirialized objects (contamination). Aims. We empirically constrained the magnitude of these effects by cross-matching galaxy clusters selected in the Dark Energy Survey data with the redMaPPer algorithm with significant detections in three South Pole Telescope surveys (SZ, pol-ECS, pol-500d). Methods. For matched clusters, we augmented the redMaPPer catalog with the SPT detection significance. For unmatched objects we used the SPT detection threshold as an upper limit on the SZe signature. Using a Bayesian population model applied to the collected multiwavelength data, we explored various physically motivated models to describe the relationship between observed richness and halo mass. Results. Our analysis reveals a clear preference for models with an additional skewed scatter component associated with projection effects over a purely log-normal scatter model. We rule out significant contamination by unvirialized objects at the high-richness end of the sample. While dedicated simulations offer a well-fitting calibration of projection effects, our findings suggest the presence of redshift-dependent trends that these simulations may not have captured. Our findings highlight that modeling the selection function of optically detected clusters remains a complicated challenge that requires a combination of simulation and data-driven approaches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Towards Better Modeling the Probability of Hydrogen Ignition

It is paramount to accurately access the risk of facilities and machinery that use hydrogen. Towards this effort, this report surveys and compares existing models for the ignition of unintended hydrogen releases, typically leaks. These models are primarily formed on expert experience and perhaps a few points of data. As such, this report provides suggestions for improvement in ignition probability modeling, both in terms of experimentation and incident collection as well as modeling.

08 HYDROGEN↗
DOE OSTI2026

OC6 Project Phase IV: Validation of Numerical Models for Novel Floating Offshore Wind Support Structures

The fourth phase of the Offshore Code Comparison, Collaboration, Continued, with Correlation and unCertainty (OC6) aims to assess the ability of the tools to model a novel floating wind design. The design that was selected for this project is the TetraSpar designed by Stiesdal Offshore Technologies. The platform is a unique design that features a spar like stability with a very low center of gravity, but does not require deep-water ports. This combination is achieved with a system made of two separate steel structures, a hull at the water’s surface that supports the wind turbine tower, and a keel that is suspended below the main body. This lower keel has a very high density and drives the total platform’s low center of gravity. Scaled model tests of the TetraSpar design were performed in 2018-2019 by the University of Maine. The tests were performed with 1:43 Froude scaling. The data collected in the model tests provide a detailed description of the response of the platform in various controlled and relatively well understood conditions. Comparison with these data provides a good opportunity for validation of numerical models. The OC6 Phase IV work will focus on the specific parameters used in these scaled model tests. The load cases (LC) considered in this project are as follows: LC 1.X - Equilibrium and Static Offset Tests LC 2.X - Platform Free Decays LC 3.X - Turbine Thrust (Wind Only) LC 4.X - Regular and Irregular Waves (Wave only) LC 5.X - Combined Wind and Wave Loading

17 WIND ENERGY↗
DOE OSTI2026

Enhanced HLW Glass Property-Composition Models – Phase 2

As a continuation of the Phase 1 HLW model development work as part of a phased approach to enhance and expand HLW glass property-composition models, additional data were collected for the HLW glass dataset and used to revise the models developed during Phase 1. These data are for glasses that are collectively referred to as ORP-2014 glasses. The sources of additional data for the Phase 2 work included: (i) actively designed glasses formulated to support various glass studies at VSL since the completion of Phase 1; and (ii) glasses from two statistically designed matrices to supplement the existing HLW compositional space. The Phase 2 matrix design was intended to augment and improve the coverage in the high aluminum region.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Simulating the Phonon Collection Efficiency in KIPMDs

Kinetic inductance phonon-mediated (KIPM) detectors are superconducting microcalorimeters that use microwave kinetic inductance detectors (MKIDs) to read out phonon signals in the device substrate. In order to improve the design of these detectors, we need to understand the effect of various detector design elements on the physical processes that take place within the detector through simulation efforts. One figure of merit for KIPM detectors is the phonon collection efficiency, $\eta_{ph]$, defined as the ratio of phonon energy detected by the sensitive element in the detector and the energy deposited by incident phonons in the substrate. Comparing the phonon collection efficiency obtained in simulation and in experiment for the same detector geometry provides insight to physical processes in the detector, such as phonon absorption at substrate-sensor interfaces and phonon loss to non-sensitive detector elements. This work models the phonon collection efficiency in two KIPM detectors with different geometries, one located at the Fermi National Accelerator Laboraory, the other located at the SLAC National Accelerator Laboratory.

Dang, Stella Q.↗
DOE OSTI2024

Street-level temperature estimation using graph neural networks: Performance, feature embedding and interpretability

Estimating street-level air temperature is a challenging task due to the highly heterogeneous urban surfaces, canyon-like street morphology, and the diverse physical processes in the built environment. Though pioneering studies have embarked on investigations via data-driven approaches, many questions remain to be answered. Here, in this study, we leveraged an innovative framework and redefined the street-level temperature estimation problem using Graph Neural Networks (GNN) with spatial embedding techniques. The results showed that GNN models are more capable and consistent of estimating street-level temperature among tested locations, benefiting from its unique strength in handling extensive data over unstructured graph topology. In addition, we conducted in-depth analysis of feature importance to enhance the model interpretability. Among the urban features analyzed in this study, the time-variant canopy density and meter-level land use data emerge as crucial factors. Our findings highlight GNN 's high potential in capturing the complex dynamics between urban elements and their impacts on microclimate, thus offering valuable insights for comprehensive urban data collection and urban climate modeling in general. Collectively, this study also contributes to urban planning and policy by providing avenues to enhance city resilience against climate change, thereby advancing the agenda for environmental stewardship and urban sustainability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Review of neutral naturalness

The hierarchy between the mass parameter of the Higgs boson and larger mass scales becomes ever more puzzling as experiments explore higher energies. Neutral naturalness is the umbrella term for symmetry-based explanations for these hierarchies whose quark symmetry partners are not charged under the SU(3) c color gauge group of the Standard Model. Though the first manifestations of this idea predate the physics runs of the Large Hadron Collider, since the Higgs discovery this paradigm has grown and developed to include a wide variety of concrete realizations with connections to intriguing collider signals. Determining the phenomenology of such models often requires the characterization—typically relying on lattice calculations—of a new confining gauge symmetry. This presents additional motivation to further develop our understanding of nonperturbative field theory as well as to pursue specific lattice studies. The wide range of suggested hidden sectors also produces a variety of dark matter candidates, intersections with astrophysics and cosmology, and ties to neutrinos and flavor. In this review, we orient the reader within both this growing collection of specific models and the physical phenomena they produce. We also survey the often less familiar dynamics of hidden-sector glueballs and quirks. In addition to providing a guide to past efforts, we reveal interesting directions for further study.

Batell, Brian [Univ. of Pittsburgh, PA (United Sta↗
DOE OSTI2026

Modeling and Experimental Validation of a Direct-Contact Counter-Flow Fluidized Bed Heat Exchanger for Thermal Energy Storage (TES) Applications

Particle-based thermal energy storage (TES) systems are an emerging energy storage technology. The technological advances have reduced costs, making TES more competitive and reliable in the marketplace but an efficient and reliable operation is heavily dependent on coherent heat transfer between air to particles or vice versa. The particle-based TES technologies provide an intermediate system that can store energy for short (0-10 h), long (10-200 h) and seasonal (> 200 h) timescales. The TES systems store energy by converting electricity to thermal energy; electricity can be directly sourced intermittent generation technologies and/or the grid, helping manage peak loads and other mismatches in supply and demand. The overall efficiency of the TES system depends on the performance of system components (particle storage silos and particle transfer mechanism etc.). The particle heat exchanger is one of the key system components that affects the system efficiency. The pressurized fluidized bed heat exchanger (PFB HX) performance is challenging to predict due to the chaotic behavior of particle and fluid interaction. This research presents a computational study of a novel direct-contact, counter-flow and air-to-particles PFB HX, that contributes in advancing the particle-based long-duration TES technologies. For the current analysis an unsteady Eulerian-Eulerian CFD model was developed and validated against experiments performed at the National Laboratory of the Rockies for two particle sizes (600 ..mu..m and 825 ..mu..m ). Following validation, parametric simulations were conducted to evaluate the effects of interphase drag models (Syamlal-O'Brien and Gidaspow), particle size, bed height and the influence of a frictional-viscosity term on hydrodynamics and heat transfer between the air & particles. The key findings from the analysis are: (1) for the studied operating window Syamlal-O'Brien provides superior agreement with measured gas temperatures (errors generally < 10%) while Gidaspow shows large deviations for the coarse particle case; (2) model predictions are most sensitive in the lower 0.2 m above the air distributor where bubble initiation and local mixing dominate interphase heat transfer; (3) representation of the distributor (number of inlet ports) materially affects predicted local mixing and temperature stratification; and (4) the Eulerian-Eulerian framework reproduces bulk thermal trends but shows regime dependent limitations for coarse particles, motivating mesoscale informed closures for scale-up analysis for future studies. These results provide validated guidance for drag selection and distributor design in particle-based thermal energy storage applications. Collectively, the validated model and parametric results quantify key drivers of PHB-HX performance and provide practical guidance for design and optimization. The results provide confidence in the model predictability and provide a step forward to improve on heat exchange performance. The demonstrated performance and modeling approach support the deployment and further development of this novel PHB-HX concept for robust, particle-based long-duration thermal energy storage systems.

25 ENERGY STORAGE↗