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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

GRUMDN: A Multi-Task Model for Predicting Human Patterns-of-Life from Stay Transition Data

Understanding human patterns-of-life (PoL) is essential towards ensuring safe and secure indoor facility environment as well as outdoor urban environment. Prediction of human movement in between places of interest is vital in understanding human PoL. Movement between spaces maybe represented and detected in one of the two forms: 1) trajectories: locations measured at regular time intervals by mobile sensors, bluetooth or GPS sensors; or 2) stay transitions: semantic PoI (points of interest) and stay duration data measurable by eventbased sensors that collect data when a check-in or check-out event is detected. Stay transition data provides a more compressed data format compared to trajectories data, especially in situations with longer stay durations, while preserving the information necessary for PoL analysis. Now as introduced briefly in the paper, our deployed end application (Digital Twin of a facility with non-player characters, besides the interactive user in virtual reality) needed a well-performing and validated AI/ML model for simulating high quality stay transitions behavior. In this study we thus primarily present our findings with developing and validating that model, which is a multi-task neural network for stay transition prediction. The neural network consists of two heads, for corresponding two tasks of stay category prediction and stay duration prediction. We evaluated gated recurrent units and multi-layer perceptrons of varying network sizes for stay category prediction; while mixture density networks, noisy generator-only networks, and generative adversarial networks of varying network sizes for stay duration prediction. We have then evaluated four multi-task models, constructed by combining these specialized models, on their ability to predict stay transition data. We tested our models on datasets from two different cases: 1) a simulation-generated dataset of indoor movement within the HFIR (high flux isotope reactor) nuclear reactor facility at Oak Ridge National Laboratory (ORNL); and 2) the GeoLife human mobility dataset of outdoor urban movement available in literature. Our results indicate that GRUMDN, which combines gated recurrent units (GRU) for stay category prediction task, and mixture density networks (MDN) for stay duration prediction task, did overall outperform other multitask models and the current state-of-the-art.

Gunaratne, Chathika [ORNL] (ORCID:0000000225088745↗
DOE OSTI2023

Addressing APC Data Sparsity in Predicting Occupancy and Delay of Transit Buses: A Multitask Learning Approach

Public transit is a vital mode of transportation in urban areas, and its efficiency is crucial for the daily commute of millions of people. To improve the reliability and predictability of transit systems, researchers have developed separate single-task learning models to predict the occupancy and delay of buses at the stop or route level. However, these models provide a narrow view of delay and occupancy at each stop and do not account for the correlation between the two. We propose a novel approach that leverages broader generalizable patterns governing delay and occupancy for improved prediction. We introduce a multitask learning toolchain that takes into account General Transit Feed Specification feeds, Automatic Passenger Counter data, and contextual temporal and spatial information. The toolchain predicts transit delay and occupancy at the stop level, improving the accuracy of the predictions of these two features of a trip given sparse and noisy data. We also show that our toolchain can adapt to fewer samples of new transit data once it has been trained on previous routes/trips as compared to state-of-the-art methods. Finally, we use actual data from Chattanooga, Tennessee, to validate our approach. We compare our approach against the state-of-the-art methods and we show that treating occupancy and delay as related problems improves the accuracy of the predictions. We show that our approach improves delay prediction significantly by as much as 4% in F1 scores while producing equivalent or better results for occupancy.

Zulqarnain, Ammar Bin↗
DOE OSTI2025

Superstructural phase transitions in polymer-grafted nanooctahedra

Superlattices of polyhedral nanocrystals exhibit emergent properties defined by their structural arrangements, but native nanocrystal ligands often limit their programmability. Polymeric ligands address this limitation by enabling tunable nanocrystal softness through modifications of polymer molecular weight and grafting density. Here, we investigate phase transitions in polymer-grafted nanooctahedra by varying polymer length, nanocrystal size, truncation, and ligand density. In two-dimensional superlattices, longer polymers or smaller nanooctahedra induce a transition from orientationally ordered to hexagonal rotator lattices. In three-dimensional superlattices, increasing polymer length drives transitions from Minkowski to body-centered cubic and plastic hexagonal close-packed phases, while higher grafting densities further enable transitions to simple hexagonal phases. Polymer brush and thermodynamic perturbation theories, supported by Monte Carlo simulations, uncover the entropic and enthalpic forces that govern these transitions. This work highlights the versatility of polymer-grafted anisotropic nanocrystals as building blocks for designing hierarchical superstructures and metamaterials with customizable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Revealing systematic changes in the transcriptome during the transition from exponential growth to stationary phase

ABSTRACT The composition of bacterial transcriptomes is determined by the transcriptional regulatory network (TRN). The TRN regulates the transition from one physiological state to another. Here, we use independent component analysis to monitor the composition of the transcriptome during the transition from the exponential growth phase to the stationary phase. With Escherichia coli K-12 MG1655 as a model strain, we trigger the transition using carbon, nitrogen, and sulfur starvation. We find that (i) the transition to the stationary phase accompanies common transcriptome changes, including increased stringent responses and reduced production of cellular building blocks and energy regardless of the limiting element; (ii) condition-specific changes are strongly associated with transcriptional regulators ( e.g. , Crp, NtrC, CysB, Cbl) responsible for metabolizing the limiting element; and (iii) the shortage of each limiting element differentially affects the production of amino acids and extracellular polymers. This study demonstrates how the combination of genome-scale datasets and new data analytics reveals the fundamental characteristics of a key transition in the life cycle of bacteria. IMPORTANCE Nutrient limitations are critical environmental perturbations in bacterial physiology. Despite its importance, a detailed understanding of how bacterial transcriptomes are adjusted has been limited. By utilizing independent component analysis (ICA) to decompose transcriptome data, this study reveals key regulatory events that enable bacteria to adapt to nutrient limitations. The findings not only highlight common responses, such as the stringent response, but also condition-specific regulatory shifts associated with carbon, nitrogen, and sulfur starvation. The insights gained from this work advance our knowledge of bacterial physiology, gene regulation, and metabolic adaptation.

Lim, Hyun Gyu (ORCID:0000000204692388)↗
DOE OSTI2020

Transition energy measurements of the X-ray lines of neon-like europium

Here, we report the measurements of the n = 3 → n = 2 L-shell X-ray transitions of neon-like Eu 53+ . These include all seven allowed electric dipole (E1) transitions, five electric quadrupole (E2) transitions, and one magnetic quadrupole (M2) transition. The measurements were carried out at the EBIT-I electron beam ion trap facility at Livermore using an X-ray calorimeter. The measured values agree with many-body perturbation theory calculations within the experimental uncertainties. This includes the transitions that involve a 2s electron and that are, therefore, strongly affected by quantum electrodynamical effects.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Exploring baryon resonances with transition generalized parton distributions: status and perspectives

QCD gives rise to a rich spectrum of excited baryon states. Understanding their internal structure is important for many areas of nuclear physics, such as nuclear forces, dense matter, and neutrino-nucleus interactions. Generalized parton distributions (GPDs) are an established tool for characterizing the QCD structure of the ground-state nucleon. They are used to create 3D tomographic images of the quark/gluon structure and quantify the mechanical properties such as the distribution of mass, angular momentum, and forces in the system. Transition GPDs extend these concepts to N → N* transitions and can be used to characterize the 3D structure and mechanical properties of baryon resonances. They can be probed in high-momentum-transfer exclusive electroproduction processes with resonance transitions e + N → e' + M + N*, such as deeply-virtual Compton scattering (M = γ) or meson production (M = π, K, etc.), and in related photon/hadron-induced processes. This White Paper describes a research program aiming to explore baryon resonance structure with transition GPDs. This includes the properties and interpretation of the transition GPDs, theoretical methods for structures and processes, first experimental results from JLab 12 GeV, future measurements with existing and planned facilities (JLab detector and energy upgrades, COMPASS/AMBER, EIC, EicC, J-PARC, LHC ultraperipheral collisions), and the theoretical and experimental developments needed to realize this program.

Experimental Nuclear Physics↗
DOE OSTI2023

Data-Driven Transition Path Analysis Yields a Statistical Understanding of Sudden Stratospheric Warming Events in an Idealized Model

Abstract Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecasting) and characterizing the statistics of events of a given severity (the risk climatology). Each event has a different duration and spatial structure, making it hard to define an objective “average event.” We argue here that transition path theory (TPT), a stochastic process framework, is an appropriate tool for the task. We demonstrate TPT’s capacities on a wave–mean flow model of sudden stratospheric warmings (SSWs) developed by Holton and Mass, which is idealized enough for transparent TPT analysis but complex enough to demonstrate computational scalability. Whereas a recent article (Finkel et al. 2021) studied near-term SSW predictability, the present article uses TPT to link predictability to long-term SSW frequency. This requires not only forecasting forward in time from an initial condition, but also backward in time to assess the probability of the initial conditions themselves. TPT enables one to condition the dynamics on the regime transition occurring, and thus visualize its physical drivers with a vector field called the reactive current . The reactive current shows that before an SSW, dissipation and stochastic forcing drive a slow decay of vortex strength at lower altitudes. The response of upper-level winds is late and sudden, occurring only after the transition is almost complete from a probabilistic point of view. This case study demonstrates that TPT quantities, visualized in a space of physically meaningful variables, can help one understand the dynamics of regime transitions.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Capturing Travel Mode Adoption in Designing On-Demand Multimodal Transit Systems

This paper studies how to integrate rider mode preferences into the design of on-demand multimodal transit systems (ODMTSs). It is motivated by a common worry in transit agencies that an ODMTS may be poorly designed if the latent demand, that is, new riders adopting the system, is not captured. This paper proposes a bilevel optimization model to address this challenge, in which the leader problem determines the ODMTS design, and the follower problems identify the most cost efficient and convenient route for riders under the chosen design. The leader model contains a choice model for every potential rider that determines whether the rider adopts the ODMTS given her proposed route. To solve the bilevel optimization model, the paper proposes an exact decomposition method that includes Benders optimal cuts and no-good cuts to ensure the consistency of the rider choices in the leader and follower problems. Moreover, to improve computational efficiency, the paper proposes upper and lower bounds on trip durations for the follower problems, valid inequalities that strengthen the no-good cuts, and approaches to reduce the problem size with problem-specific preprocessing techniques. The proposed method is validated using an extensive computational study on a real data set from the Ann Arbor Area Transportation Authority, the transit agency for the broader Ann Arbor and Ypsilanti region in Michigan. The study considers the impact of a number of factors, including the price of on-demand shuttles, the number of hubs, and access to transit systems criteria. The designed ODMTSs feature high adoption rates and significantly shorter trip durations compared with the existing transit system and highlight the benefits of ensuring access for low-income riders. Finally, the computational study demonstrates the efficiency of the decomposition method for the case study and the benefits of computational enhancements that improve the baseline method by several orders of magnitude. Funding: This research was partly supported by National Science Foundation [Leap HI Proposal NSF-1854684] and the Department of Energy [Research Award 7F-30154].

Operations Research & Management Science↗
DOE OSTI2021

Phase transition dynamics in one-dimensional halide perovskite crystals

Triiodide perovskites CsPbI 3 , CsSnI 3 , and FAPbI 3 (where FA is formamidinium) are highly promising materials for a range of optoelectronic applications in energy conversion. However, they are thermodynamically unstable at room temperature, preferring to form low-temperature (low-T) non-perovskite phases with one-dimensional anisotropic crystal structures. While such thermodynamic behavior represents a major obstacle toward realizing high-performance devices based on their high-temperature (high-T) perovskite phases, the underlying phase transition dynamics are still not well understood. In this work, we use in situ optical micro-spectroscopy to quantitatively study the transition from the low-T to high-T phases in individual CsSnI 3 and FAPbI 3 nanowires. We reveal a large blueshift in the photoluminescence (PL) peak (~38 meV) at the low-T/high-T two-phase interface of partially transitioned FAPbI 3 wire, which may result from the lattice distortion at the phase boundary. Compared to the experimentally derived activation energy of CsSnI 3 (~1.93 eV), the activation energy of FAPbI 3 is relatively small (~0.84 eV), indicating a lower kinetic energy barrier when transitioning from a face-sharing octahedral configuration to a corner-sharing one. Further, the phase propagation rate in CsSnI 3 is observed to be relatively high, which may be attributed to a high concentration of Sn vacancies. Our results could not only facilitate a deeper understanding of phase transition dynamics in halide perovskites with anisotropic crystal structures, but also enable controllable manipulation of optoelectronic properties via local phase engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The iron spin transition of deep nitrogen-bearing mineral Fe3N1.2 at high pressure

Abstract Nitrogen is an essential element for life, one of the most abundant volatiles in the atmosphere, and an important component in the Earth’s interior, where iron nitride is an essential host of deep nitrogen. Here, we investigate the pressure-induced electronic spin-pairing transition of iron in siderazot (Fe3N1.2) at pressures up to 45.8 GPa at room temperature, using diamond-anvil cell techniques coupled with synchrotron X-ray emission spectroscopy. The integrated intensity of the satellite emission peak (K′β) decreases upon compression but remains unchanged at pressures greater than 30.5 GPa. In other words, the high-spin to low-spin transition of iron in Fe3N1.2 starts immediately at very low pressures and completes at ~30.5 GPa. The iron spin transition completion pressures increase with the nitrogen concentration of hexagonal close-packed iron nitrides (i.e., Fe3N1.2, Fe7N3, and Fe2N). Moreover, the identity and concentration of light elements in binary iron-rich compounds such as Fe3N, Fe3C, Fe3P, Fe3S, Fe7C3, and Fe7N3, together with their crystal structure, could affect the iron spin transition pressures. The spin transition of iron-rich alloys could alter the bonding nature and the physical properties, including the thermal and electrical conductivity, thereby influencing the thermal state and evolution of planetary interiors.

Geochemistry & Geophysics↗
DOE OSTI2020

Coupling of Laminar-Turbulent Transition with RANS Computational Fluid Dynamics

This project combines several new concepts to create a boundary layer transition prediction capability that is suitable for analyzing modern hypersonic flight vehicles. The first new concept is the use of ''optimization'' methods to detect the hydrodynamic instabilities that cause boundary layer transition; the use of this method removes the need for many limiting assumptions of other methods and enables quantification of the interactions between boundary layer instabilities and the flow field imperfections that generate them. The second new concept is the execution of transition analysis within a conventional hypersonics CFD code, using the same mesh and numerical schemes for the transition analysis and the laminar flow simulation. This feature enables rapid execution of transition analysis with less user oversight required and no interpolation steps needed.

42 ENGINEERING↗
DOE OSTI2026

Quantum enabled precision measurements of the 229Th nuclear isomer transition (final report)

The existence of the nuclear isomer transition in thorium-229 was first inferred from keV lines in the gamma spectrum of uranium-233 decay more than 40 years ago. Over the years, the value of the transition energy has been refined with indirect measurements using nuclear physics techniques, and the current evidence points to transition energy in the laser-accessible vacuum ultra-violet region of the spectrum. At the start of this project, the two best measurements of the transition energy were 7.8±0.5 eV and 8.28±0.17 eV from high precision gamma ray spectroscopy and kinetic energy of internal conversion electrons, respectively. This project aimed to reduce the uncertainty in the transition energy to 10 meV using direct calorimetric measurements of the decay energy with superconducting nanowire single photon detectors (SNSPDs). Specifically, the method that was pursued was to generate thorium-229 in the excited isomer state by the alpha decay of uranium-233, embed the excited state thorium into an SNSPD, then detect the energy released when the isomer deexcites.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

HATS-71b: A Giant Planet Transiting an M3 Dwarf Star in TESS Sector 1

We report the discovery of HATS-71b, a transiting gas giant planet on a P=3.7955 day orbit around a G=15.35 mag M3 dwarf star. HATS-71 is the coolest M dwarf star known to host a hot Jupiter. The loss of light during transits is 4.7%, more than in any other confirmed transiting planet system. The planet was identified as a candidate by the ground-based HATSouth transit survey. It was confirmed using ground-based photometry, spectroscopy, and imaging, as well as space-based photometry from the NASA Transiting Exoplanet Survey Satellite mission (TIC 234523599). Combining all of these data, and utilizing Gaia DR2, we find that the planet has a radius of 1.024±0.018 R{sub J} and mass of 0.37 ±0.24 M{sub J} (95% confidence upper limit of <0.80 M{sub J}), while the star has a mass of 0.4861±0.0060 M{sub ⊙} and a radius of 0.4783±0.0060 R{sub ⊙}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

TESS Hunt for Young and Maturing Exoplanets (THYME). II. A 17 Myr Old Transiting Hot Jupiter in the Sco-Cen Association

We present the discovery of a transiting hot Jupiter orbiting HIP 67522 (T {sub eff} ∼ 5650 K; M {sub *} ∼ 1.2M {sub ⊙}) in the 10–20 Myr old Sco-Cen OB association. We identified the transits in the TESS data using our custom notch filter planet search pipeline and characterize the system with additional photometry from Spitzer; spectroscopy from SOAR/Goodman, SALT/HRS, LCOGT/NRES, and SMARTS/CHIRON; and speckle imaging from SOAR/HRCam. We model the photometry as a periodic Gaussian process with transits to account for stellar variability and find an orbital period of 6.9596{sub −0.000015}{sup +0.000016} days and radius of 10.02{sub −0.53}{sup +0.54} R {sub ⊕}. We also identify a single transit of an additional candidate planet with radius 8.01{sub −0.71}{sup +0.75} R {sub ⊕} that has an orbital period of ≳23 days. The validated planet HIP 67522b is currently the youngest transiting hot Jupiter discovered and is an ideal candidate for transmission spectroscopy and radial velocity follow-up studies, while also demonstrating that some young giant planets either form in situ at small orbital radii or else migrate promptly from formation sites farther out in the disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

TOI-811b and TOI-852b: New Transiting Brown Dwarfs with Similar Masses and Very Different Radii and Ages from the TESS Mission

We report the discovery of two transiting brown dwarfs (BDs), TOI-811b and TOI-852b, from NASA’s Transiting Exoplanet Survey Satellite mission. These two transiting BDs have similar masses but very different radii and ages. Their host stars have similar masses, effective temperatures, and metallicities. The younger and larger transiting BD is TOI-811b at a mass of M {sub b} = 59.9 ± 13.0M {sub J} and radius of R {sub b} = 1.26 ± 0.06R {sub J}, and it orbits its host star in a period of P = 25.16551 ± 0.00004 days. We derive the host star’s age of 93{sub −29}{sup +61} Myr from an application of gyrochronology. The youth of this system, rather than external heating from its host star, is why this BD’s radius is relatively large. This constraint on the youth of TOI-811b allows us to test substellar mass–radius evolutionary models at young ages where the radius of BDs changes rapidly. TOI-852b has a similar mass at M {sub b} = 53.7 ± 1.4M {sub J} but is much older (4 or 8 Gyr, based on bimodal isochrone results of the host star) and is also smaller with a radius of R {sub b} = 0.83 ± 0.04R {sub J}. TOI-852b’s orbital period is P = 4.94561 ± 0.00008 days. TOI-852b joins the likes of other old transiting BDs that trace out the oldest substellar mass–radius evolutionary models where contraction of the BD’s radius slows and approaches a constant value. Both host stars have a mass of M {sub ⋆} = 1.32M {sub ⊙} ± 0.05 and differ in their radii, T {sub eff}, and [Fe/H], with TOI-811 having R {sub ⋆} = 1.27 ± 0.09R {sub ⊙}, T {sub eff} = 6107 ± 77 K, and [Fe/H] = + 0.40 ± 0.09 and TOI-852 having R {sub ⋆} = 1.71 ± 0.04R {sub ⊙}, T {sub eff} = 5768 ± 84 K, and [Fe/H] = + 0.33 ± 0.09. We take this opportunity to examine how TOI-811b and TOI-852b serve as test points for young and old substellar isochrones, respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Relativistic Hybrid Stars with Sequential First-order Phase Transitions in Light of Multimessenger Constraints

In this work, we consider the properties of compact stars in which quark matter has low- and high-density phases that are separated by a first-order phase transition. Thus, unlike the commonly considered case of a single phase transition from hadronic to quark matter, our models of hybrid stars contain sequential phase transitions from hadronic matter to low- and then to high-density quark matter phases. We extend our previous study of the parameter space of hybrid stars with a single phase transition to those with sequential phase transitions, taking into account the constraints on the mass and radius of neutron stars from the NICER experiment, the experimental inferences of the neutron skin thickness of the lead nucleus by the PREX-II experiment, and constraints on the tidal deformability from the gravitational-wave event GW170817. We determine the range of the masses for which both twin and triplet configurations, i.e., identical-mass stars with two and three different values of radii, arise.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Regional Analysis for an Economically and Environmentally Viable Transition to Heavy-Duty Vehicles with Alternative Powertrains

The transportation sector is responsible for a significant portion of greenhouse gas emissions. Within the sector, truck freight is responsible for a third of the associated emissions. Alternative powertrains are seen as a viable approach to significantly reduce these emissions. Prior to making a large-scale transition, it is important to consider the following questions: will the power grid support a transition to alternative powertrains?; will the transition truly reduce carbon emissions?; and will the transition impose an unnecessary economic burden on companies within the industry? The answer to these questions, however, can vary by geography, maturity/capacity of the energy distribution network or predicted vehicle load. We focus on the latter two questions, investigating the variation in estimated total cost of ownership and carbon emissions across the United States at the zip code level for both heavy-duty battery electric vehicles and heavy-duty fuel cell electric vehicles. As a benchmark, we compare estimated emissions and costs of alternative powertrain vehicles to that of conventional heavy-duty vehicles powered by diesel internal combustion engines. This work highlights areas with electric grids primed for a transition to alternative powertrain vehicles, such as the Pacific Northwest, and areas that require further infrastructure investment in renewables, such as many of the Mountain states, Missouri, and Florida. Additionally, this work illustrates the current advantages in carbon emissions of battery electric vehicles compared to fuel-cell electric vehicles, while providing insights into required regional investments for narrowing the gap.

Goulet, Nate [ORNL] (ORCID:0000000237314965)↗
NASA NTRS1971

Calculation of compressible nonadiabatic boundary layers in laminar, transitional and turbulent flow by the method of integral relations

A computer program was developed to do the calculations for two-dimensional or axisymmetric configurations from low speeds to hypersonic speeds with arbitrary streamwise pressure, temperature, and Mach number distributions. Options are provided for obtaining initial conditions either from experimental information or from a theoretical similarity solution. The transition region can be described either by an arbitrary distribution of intermittency or by a function based on Emmons' probability theory. Correlations were developed for use in estimating the parameters of the theoretical intermittency function. Correlations obtained from other sources are used for estimating the transition point. Comparisons were made between calculated and measured boundary layer quantities for laminar, transitional, and turbulent flows on flat plates, cones, cone flares, and a waisted body of revolution. Excellent agreement was obtained between the present theory and two other theories based on the method of finite differences. The intermittency required to reproduce some experimental heat transfer results in hypersonic flow was found to be quite different from the theoretical function. It is suggested that the simple probability theory of Emmons may not be valid for representing the intermittency of hypersonic transitional boundary layers and that the program could be useful as a tool for detailed study of the intermittency of the transition region.

Kuhn, G. D.↗