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DOE OSTI2021

Time-resolved Rotational Velocities in the Upper Atmosphere of WASP-33 b

While steady empirical progress has been made in understanding the structure and composition of hot-planet atmospheres, direct measurements of velocity signatures, including winds, rotation, and jets, have lagged behind. Quantifying atmospheric dynamics of hot planets is critical for a complete understanding of their atmospheres, and such measurements may even illuminate other planetary properties, such as magnetic field strengths. In this manuscript we present the first detection of the Balmer lines Hα and Hβ in the atmosphere of the ultra-hot Jupiter WASP-33 b. Using atmospheric models that include the effects of atmospheric dynamics, we show that the shape of the average Balmer line transmission spectrum is consistent with rotational velocities in the planet’s thermosphere of v{sub rot}=10.1{sub −1.0}{sup +0.8} km s{sup −1}. We also measure a low-significance day- to nightside velocity shift of −4.6{sub −3.4}{sup +3.4} km s{sup −1} in the transmission spectrum, which is naturally explained by a global wind across the planet’s terminator. In a separate analysis the time-resolved velocity centroids of individual transmission spectra show unambiguous evidence of rotation, with a best-fit velocity of 10.0{sub −2.0}{sup +2.4} km s{sup −1}, consistent with the value of v {sub rot} derived from the shape of the average Balmer line transmission spectrum. Our observations and analysis confirm the power of time-resolved transmission spectra with a high signal-to-noise ratio to measure the velocity structures in exoplanet atmospheres. The high rotational and wind velocities we measure highlight the need for more detailed 3D global climate simulations of the rarefied upper atmospheres of ultra-hot gas giants.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Dynamic Linking of Upstream Energy and Freight Demands for Bio and Fossil Energy Pathways in the Global Change Analysis Model

Comprehensive study of the environmental impacts associated with demand for an energy resource or carrier in any one sector requires a full consideration of the direct and indirect impacts on the rest of the regional and global energy system. It is important to consider the energy that is consumed in producing primary energy resources and energy consumed in transporting these energy resources internationally and domestically in order to produce a complete picture of these impacts. Biofuels are especially complex since they have feedbacks not just to the energy system but also to regional and global crop markets. Different modeling and analysis strategies have been applied to consider these impacts, which occur “upstream” of final energy consumption, with some success. Traditional life cycle models allow for rich technological detail in linking upstream impacts of energy demand with downstream final consumption; however, they cannot by themselves represent dynamic economic feedbacks across multiple sectors and regions over time. Computable general equilibrium (CGE) modeling does account for economic feedback among all sectors and regions; however, CGE modeling does not lend itself to physical representation of technological detail. Partial equilibrium (PE) modeling is a heterogeneous category describing economic models that focus on a subset of the economy, and they differ in coverage and ease in incorporating more sectors and economic links. In this study, we present a strategy for dynamically including the direct and indirect impacts of energy demand with physical and technology detail by explicitly adding these upstream energy and transportation links to GCAM, a PE model of global energy, land use, and emissions. We incorporate the following inter-sectoral linkages: energy inputs to crop production, energy inputs to fossil resource production, and freight transport requirements of energy and agricultural commodities. We assess the implications of explicitly including these links by measuring the global impacts of increased corn ethanol demand in the United States with and without these links included. Although the net global impact of the upstream links on energy and emissions are relatively modest in the scenarios we studied, the inclusion of these links illustrates interesting trade-offs in energy and transportation demand among fossil fuel and agriculture sectors. These sectoral interactions suggest that this level of modeling detail could be important in evaluating future analytical questions.

Sampedro Martinez de Estivariz, Jon↗

DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗

DOE OSTI2015

Application configuration selection for energy-efficient execution on multicore systems

Balanced performance and energy consumption are incorporated in the design of modern computer systems. Several runtime factors, such as concurrency levels, thread mapping strategies, and dynamic voltage and frequency scaling (DVFS) should be considered in order to achieve optimal energy efficiency fora workload. Selecting appropriate run-time factors, however, is one of the most challenging tasks because the run-time factors are architecture-specific and workload-specific. And while most existing works concentrate on either static analysis of the workload or run-time prediction results, we present a hybrid two-step method that utilizes concurrency levels and DVFS settings to achieve the energy efficiency configuration for a worldoad. The experimental results based on a Xeon E5620 server with NPB and PARSEC benchmark suites show that the model is able to predict the energy efficient configuration accurately. On average, an additional 10% EDP (Energy Delay Product) saving is obtained by using run-time DVFS for the entire system. An off-line optimal solution is used to compare with the proposed scheme. Finally, the experimental results show that the average extra EDP saved by the optimal solution is within 5% on selective parallel benchmarks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Connected Traffic Signal Coordination Optimization Framework through Network-Wide Adaptive Linear Quadratic Regulator–Based Control Strategy

Traffic congestion in metropolitan areas causes several significant challenges, such as longer travel times, decreased productivity, increased fuel consumption and vehicle emissions, and even severe injuries during crashes. Traffic signal control is a management approach to reduce traffic congestion and allocate the appropriate right of way for safety and mobility efficiency, both in temporal and spatial domains. Here, this study proposes a network-wide adaptive signal control coordination optimization framework based on the linear quadratic regulator algorithm. The traffic flow conditions driven by signal control inputs are formulated based on their network-wide state-space representation. After modeling traffic control regulation constraints, an adaptive linear quadratic regulator algorithm is designed to maximize the network-wide total throughput under the current conditions. Optimal signal control split time durations for multiple intersections in the network are derived by solving the algebraic Riccati equation. Furthermore, the recursive least square parameter estimation method is employed to quantify dynamic traffic condition changes. To verify the effectiveness of this proposed signal control framework, both simulation and real-world experimental tests are conducted for multiple intersections in downtown Chattanooga, Tennessee, United States. In preparation for real-world experimental tests, pipelines for real-time data processing implementation and historical traffic flow data analysis are conducted. The test results demonstrate that the proposed control framework achieves a decrease in travel time by up to 19.4%, total time spent (TTS) by up to 11.9%, and relative queue balance (RQB) by up to 15.6%. The research findings indicate that the proposed signal control framework can be generalized to handle large scale signal control optimization network-wide.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

ASGARD: A LARGE SURVEY FOR SLOW GALACTIC RADIO TRANSIENTS. I. OVERVIEW AND FIRST RESULTS

Searches for slow radio transients and variables have generally focused on extragalactic populations, and the basic parameters of Galactic populations remain poorly characterized. We present a large 3 GHz survey performed with the Allen Telescope Array (ATA) that aims to improve this situation: ASGARD, the ATA Survey of Galactic Radio Dynamism. ASGARD observations spanned two years with weekly visits to 23 deg{sup 2} in two fields in the Galactic plane, totaling 900 hr of integration time on science fields and making it significantly larger than previous efforts. The typical blind unresolved source detection limit was 10 mJy. We describe the observations and data analysis techniques in detail, demonstrating our ability to create accurate wide-field images while effectively modeling and subtracting large-scale radio emission, allowing standard transient-and-variability analysis techniques to be used. We present early results from the analysis of two pointings: one centered on the microquasar Cygnus X-3 and one overlapping the Kepler field of view (l = 76 Degree-Sign , b = +13. Degree-Sign 5). Our results include images, catalog statistics, completeness functions, variability measurements, and a transient search. Out of 134 sources detected in these pointings, the only compellingly variable one is Cygnus X-3, and no transients are detected. We estimate number counts for potential Galactic radio transients and compare our current limits to previous work and our projection for the fully analyzed ASGARD data set.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Solidification and fcc to metastable hcp phase transition in krypton under variable compression rates

In this work, we present time-resolved synchrotron x-ray diffraction measurements to study kinetics associated with the liquid-solid and solid-solid high-pressure phase transitions in Kr under dynamic loading in a dynamic-diamond anvil cell. The results show a strong compression-rate dependence of the solidification/melting process in liquid Kr. The analysis of the compression-rate dependent melting/solidification, using an Avrami equation with the parameter n=1, indicates a spontaneous nucleation and one-dimensional growth mechanism. In contrast, the face-centered-cubic to metastable hexagonal close-packed transition in solid Kr occurs rapidly at ~0.8 GPa near the melting line, which has negligible compression-rate dependence within the range of compression rates studied (0.004–13 GPa/s).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2013

Dynamics of Nano-Confined Water under Pressure

We report a study of the effects of pressure on the diffusivity of water molecules confined in single- wall carbon nanotubes (SWNT) with average mean pore diameter of 16 A. The measurements were carried out using high-resolution neutron scattering, over the temperature range 220 T 260 K, and at two pressure conditions: ambient and elevated pressure. The high pressure data were collected at constant volume on cooling, with P varying from 1.92 kbar at temperature T = 260 K to 1.85 kbar at T = 220 K. Analysis of the observed dynamic structure factor S(Q, E) reveals the presence of two relaxation processes, a faster diffusion component (FC) associated with the motion of caged or restricted molecules, and a slower component arising from the free water molecules diffusing within the SWNT matrix. While the temperature dependence of the slow relaxation time exhibits a Vogel-Fulcher-Tammann law and is non-Arrhenius in nature, the faster component follows an Arrhenius exponential law at both pressure conditions. The application of pressure remarkably slows down the overall molecular dynamics, in agreement with previous observations, but most notably affects the slow relaxation. The faster relaxation shows marginal or no change with pressure within the experimental conditions.

Confined Water↗

DOE OSTI2020

Effects of nitrogen enrichment on tree carbon allocation: A global synthesis

Aim: Increased atmospheric nitrogen deposition may have profound effects on tree carbon allocation dynamics. However, a comprehensive understanding of how nitro-gen (N) enrichment influences carbon (C) allocation across plant functional processes and tree organs in individual trees remains elusive. Location: Global forest ecosystems. Time period: 1990–2018. Major taxa studied: Trees. Methods: We compiled data from 75 N addition experiments and conducted a meta-analysis to evaluate the responses of C source (photosynthesis), sinks (growth and respiration) and storage (non-structural carbohydrate concentrations) in different tree organs (foliage, above-ground wood and roots) to N enrichment. Results: N enrichment significantly enhanced C supply via photosynthesis (+39.6%, n = 128). C allocation to growth (biomass increment/production) significantly in-creased in foliage (+15.9%, n = 68) and above-ground wood (+31.8%, n = 64; bole, branch, stem and/or twig) with increasing N availability, but not in roots, whereas allocation increased in roots via increasing fine root turnover rate (+22.6%, n = 11). N fertilization significantly increased C allocation to respiration in above-ground wood (+46.6%, n = 12) and roots (+5.5%, n = 57), but not in foliage. N addition decreased non-structural carbohydrate (NSC) concentrations in foliage (-5.4%, n = 16) and roots (-5.0%, n = 21), but increased NSC in above-ground wood (+6.1%, n = 22). In addition, N enrichment effects were strongly affected by moderator variables. Main conclusions: Our results demonstrate that N addition increased C allocation to growth and respiration more strongly than C allocation to NSC storage, and increased C allocation to above-ground parts more strongly than to below-ground parts. Our results are useful for better understanding the response of tree functional processes at organ level to N enrichment. The existing data also reveal that more long-term ex-perimental studies on mature trees in tropical and boreal forests are urgently needed to provide a basis for forecasting tree responses to N enrichment at the global scale.

Li, Weibin↗

DOE OSTI2025

A split ribozyme system for in vivo plant RNA imaging and genetic engineering

RNA plays a central role in plants, governing various cellular and physiological processes. Monitoring its dynamic abundance provides a discerning understanding of molecular mechanisms underlying plant responses to internal (developmental) and external (environmental) stimuli, paving the way for advances in plant biotechnology to engineer crops with improved resilience, quality and productivity. In general, traditional methods for analysis of RNA abundance in plants require destructive, labour-intensive and time-consuming assays. To overcome these limitations, we developed a transformative innovation for in vivo RNA imaging in plants. Specifically, we established a synthetic split ribozyme system that converts various RNA signals to orthogonal protein outputs, enabling in vivo visualisation of various RNA signals in plants. We demonstrated the utility of this system in transient expression experiments (i.e., leaf infiltration in Nicotiana benthamiana ) to detect RNAs derived from transgenes and tobacco rattle virus, respectively. Also, we successfully engineered a split ribozyme-based biosensor in Arabidopsis thaliana for in vivo visualisation of endogenous gene expression at the cellular level, demonstrating the feasibility of multi-scale (e.g., cellular and tissue level) RNA imaging in plants. Furthermore, we developed a platform for easy incorporation of different protein outputs, allowing for flexible choice of reporters to optimise the detection of target RNAs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Memoirs of Mass Accretion: Probing the Edges of Intracluster Light in Simulated Galaxy Clusters

The diffuse starlight extending throughout massive galaxy clusters, known as intracluster light (ICL), has the potential to be read as a memoir of mass accretion: informative, individual, and yet imperfect. Here, we combine dark-matter-only zoom-in simulations from the Symphony suite with the Nimbus “star-tagging” model of the stellar halo to assess how much information about the mass assembly of an individual galaxy cluster can be gleaned from idealized measurements of ICL outskirts. We show that the edges of a cluster’s stellar profile—the primary (R sp⋆,1 ) and secondary (R sp⋆,2 ) stellar “splashback” radii—are sensitive to both continuous mass accretion histories (MAHs) and discrete merger events, making them potentially powerful probes of a cluster’s past. We find that R sp⋆,1 strongly correlates with the cluster’s mass ∼1 dynamical time ago, while R sp⋆,2 traces more recent MAH to a slightly lesser degree. In combination, these features can further distinguish between clusters that have and have not undergone a major merger within the past dynamical time. We use both to predict realistic cluster MAHs with the MultiCAM framework. These outer ICL features are significantly more sensitive to mass accretion and merger histories than the stellar mass gap and halo concentration, and perform comparably to the commonly used X-ray-based tracer of relaxedness, x off . While our analysis is idealized, the relevant ICL features are potentially detectable in next-generation deep imaging of nearby clusters. This work highlights the promise of ICL measurements and lays the groundwork for more detailed forecasts of their power.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Unraveling the discontinuous plastic flow of a Co-Cr-Fe-Ni-Mo multiprincipal-element alloy at deep cryogenic temperatures

We report an analysis of the discontinuous plastic flow of a multiprincipal-element alloy, Co 17.5 Cr 12.5 Fe 55 Ni 10 Mo 5 (atomic percent, at. %), in the temperature range of 0.5–4.2 K showing serrated deformation curves. Using the analytical techniques, we studied the statistics of the stress drops associated with the unstable plastic flow. The analysis showed that the complexity and heterogeneity of a discontinuous plastic flow were reduced when the temperature was lowered. This behavior was associated with the effects of dynamic recovery and adiabatic heating on the dislocation-density evolution.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Dynamic Stabilization of Metal Oxide–Water Interfaces

The interaction of water with metal oxide surfaces plays a crucial role in the catalytic and geochemical behavior of metal oxides. In a vast majority of studies, the interfacial structure is assumed to arise from a relatively static lowest energy configuration of atoms, even at room temperature. Using hematite (α-Fe 2 O 3 ) as a model oxide, we show through a direct comparison of in situ synchrotron X-ray scattering with density functional theory-based molecular dynamics simulations that the structure of the ($1\bar{10}2 $) termination is dynamically stabilized by picosecond water exchange. Simulations show frequent exchanges between terminal aquo groups and adsorbed water in locations and with partial residence times consistent with experimentally determined atomic sites and fractional occupancies. Frequent water exchange occurs even for an ultrathin adsorbed water film persisting on the surface under a dry atmosphere. The resulting time-averaged interfacial structure consists of a ridged lateral arrangement of adsorbed water molecules hydrogen bonded to terminal aquo groups. Surface pK a prediction based on bond valence analysis suggests that water exchange will influence the proton-transfer reactions underlying the acid/base reactivity at the interface. Our findings provide important new insights for understanding complex interfacial chemical processes at metal oxide–water interfaces.

58 GEOSCIENCES↗

DOE OSTI2011

ORBITAL MOTION OF HR 8799 b, c, d USING HUBBLE SPACE TELESCOPE DATA FROM 1998: CONSTRAINTS ON INCLINATION, ECCENTRICITY, AND STABILITY

HR 8799 is currently the only multiple-planet system that has been detected with direct imaging, with four giant planets of masses 7-10 M{sub Jup} orbiting at large separations (15-68 AU) from this young late A star. Orbital motion provides insight into the stability and possible formation mechanisms of this planetary system. Dynamical studies can also provide constraints on the planets' masses, which help calibrate evolutionary models, yet measuring the orbital motion is a very difficult task because the long-period orbits (50-500 yr) require long time baselines and high-precision astrometry. This paper studies the three planets HR 8799b, c, and d in the archival data set of HR 8799 obtained with the Hubble Space Telescope (HST) NICMOS coronagraph in 1998. The detection of all three planets is made possible by a careful optimization of the Locally Optimized Combination of Images algorithm, and we used a statistical analysis of a large number of reduced images. This work confirms previous astrometry for planet b and presents new detections and astrometry for planets c and d. These HST images provide a ten-year baseline with the discovery images from 2008, and therefore offer a unique opportunity to constrain their orbital motion now. Recent dynamical studies of this system show the existence of a few possible stable solutions involving mean motion resonances (MMRs), where the interaction between c and d plays a major role. We study the compatibility of a few of these stable scenarios (1d:1c, 1d:2c, or 1d:2c:4d) with the new astrometric data from HST. In the hypothesis of a 1d:2c:4b MMR our best orbit fit is close to the stable solution previously identified for a three-planet system and involves low eccentricity for planet d (e{sub d} = 0.10) and moderate inclination of the system (i = 28.0 deg), assuming a coplanar system, circular orbits for b and c, and exact resonance with integer period ratios. Under these assumptions, we can place strong constraints on the inclination of the system (27.3-31.4 deg) and on the eccentricity for d e{sub d} < 0.46. Our results are robust to small departures from exact integer period ratios and consistent with previously published results based on dynamical studies for a three-planet system prior to the discovery of the fourth planet.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Performance modeling of microsecond scale biological molecular dynamics simulations on heterogeneous architectures

Performance improvements in biomolecular simulations based on molecular dynamics (MD) codes are widely desired. Unfortunately, the factors, which allowed past performance improvements, particularly the microprocessor clock frequencies, are no longer increasing. Hence, novel software and hardware solutions are being explored for accelerating performance of widely used MD codes. In this paper, we describe our efforts on porting, optimizing and tuning of Large-scale Atomic/Molecular Massively Parallel Simulator, a popular MD framework, on heterogeneous architectures: multi-core processors with graphical processing unit (GPU) accelerators. Our implementation is based on accelerating the most computationally expensive non-bonded interaction terms on the GPUs and overlapping the computation on the CPU and GPUs. This functionality is built on top of message passing interface that allows multi-level parallelism to be extracted even at the workstation level with the multi-core CPUs and allows extension of the implementation on GPU-enabled clusters. We hypothesize that the optimal benefit of heterogeneous architectures for applications will come by utilizing all possible resources (for example, CPU-cores and GPU devices on GPU-enabled clusters). Benchmarks for a range of biomolecular system sizes are provided, and an analysis is performed on four generations of NVIDIA's GPU devices. On GPU-enabled Linux clusters, by overlapping and pipelining computation and communication, we observe up to 10-folds application acceleration in multi-core and multi-GPU environments illustrating significant performance improvements. Detailed analysis of the implementation is presented that allows identification of bottlenecks in algorithm, indicating that code optimization and improvements on GPUs could allow microsecond scale simulation throughput on workstations and inexpensive GPU clusters, putting widely desired biologically relevant simulation time-scales within reach of a large user community. In order to systematically optimize simulation throughput and to enable performance prediction, we have developed a parameterized performance model that will allow developers and users to explore the performance potential of future heterogeneous systems for biological simulations.

Agarwal, Pratul K.↗

DOE OSTI2014

Design and development of permanent magnet based focusing lens for J-Band Klystron

Applying permanent magnet technology to beam focusing in klystrons can reduce their power consumption and increase their reliability of operation. Electromagnetic design of the beam focusing elements, for high frequency travelling wave tubes, is very critical. The magnitude and profile of the magnetic field need to match the optics requirement from beam dynamics studies. The rise of the field from cathode gun region to the uniform field region (RF section) is important as the desired transition from zero to peak axial field must occur over a short axial distance. Confined flow regime is an optimum choice to minimize beam scalloping but demands an axial magnetic field greater than 2 - 3 times the Brillouin flow field. This necessitates optimization in the magnet design achieve high magnetic field within given spatial constraints. Electromagnetic design and simulations were done using 3D Finite element method (FEM) analysis software. A permanent magnet based focusing lens for a miniature J-Band klystron has been designed and developed at Control Instrumentation Division, BARC. This paper presents the design, simulation studies, beam transmission and RF tests results for J Band klystron with permanent magnet focusing lens. (author)

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

Lake and reservoir surface areas are an important proxy for freshwater availability. Advancements in machine learning (ML) techniques and increased accessibility of remote sensing data products have enabled the analysis of waterbody surface area dynamics on broad spatial scales. However, interpreting the ML results remains a challenge. While ML provides important tools for identifying patterns, the resultant models do not include mechanisms. Thus, the “black-box” nature of ML techniques often lacks ecological meaning. Using ML, we characterized temporal patterns in lake and reservoir surface area change from 1984 to 2016 for 103,930 waterbodies in the contiguous United States. We then employed knowledge-guided machine learning (KGML) to classify all waterbodies into seven ecologically interpretable groups representing distinct patterns of surface area change over time. Many waterbodies were classified as having “no change” (43%), whereas the remaining 57% of waterbodies fell into other groups representing both linear and nonlinear patterns. This analysis demonstrates the potential of KGML not only for identifying ecologically relevant patterns of change across time but also for unraveling complex processes that underpin those changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Using Knowledge-Guided Machine Learning To Assess Patterns of Areal Change in Waterbodies across the Contiguous United States

58 GEOSCIENCES↗