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At least 775 records · Page 43

Photon structure studied at an electron ion collider

We report that a future electron ion collider (EIC) will be able to provide collisions of polarized electrons with protons and heavy ions over a wide range of center-of-mass energies (20 GeV to 140 GeV) at an instantaneous luminosity of 10 33 - 10 34 cm -2 s -1 . One of its promising physics programs is the study of the partonic structure of quasireal photons. Measuring dijets in quasireal photoproduction events, one can effectively access the underlying parton dynamics of the photons. In this paper, we discuss the feasibility of tagging resolved photon processes and measuring the dijet cross section as a function of jet transverse momentum in the range of 0.01 < x$rec\atop{γ}$ < 1 at an EIC. Finally, it will be shown that both unpolarized and polarized parton distributions in the photon can be extracted, and that the flavor of the parton can be tagged at an EIC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Approximating Trajectory Constraints With Machine Learning – Microgrid Islanding With Frequency Constraints

Here, we introduce deep earning aided constraint encoding to tackle the frequency-constraint microgrid scheduling problem. The nonlinear function between system operating condition and frequency nadir is approximated by using a neural network, which admits an exact mixed-integer formulation (MIP). This formulation is then integrated with the scheduling problem to encode the frequency constraint. With the stronger representation power of the neural network, the resulting commands can ensure adequate frequency response in a realistic setting in addition to islanding success. The proposed method is validated on a modified 33-node system. Successful islanding with a secure response is simulated under the scheduled commands using a detailed three-phase model in Simulink. The advantages of our model are particularly remarkable when the inertia emulation functions from wind turbine generators are considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗

AWARE: The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) performed comprehensive meteorological and aerosol measurements and ground-based atmospheric remote sensing at two Antarctic stations using the most advanced instrumentation available. A suite of cloud research radars, lidars, spectral and broadband radiometers, aerosol chemical and microphysical sampling equipment, and meteorological instrumentation was deployed at McMurdo Station on Ross Island from December 2015 through December 2016. A smaller suite of radiometers and meteorological equipment, including radiosondes optimized for surface energy budget measurement, was deployed on the West Antarctic Ice Sheet between 4 December 2015 and 17 January 2016. AWARE provided Antarctic atmospheric data comparable to several well-instrumented high Arctic sites that have operated for many years and that reveal numerous contrasts with the Arctic in aerosol and cloud microphysical properties. These include persistent differences in liquid cloud occurrence, cloud height, and cloud thickness. Antarctic aerosol properties are also quite different from the Arctic in both seasonal cycle and composition, due to the continent’s isolation from lower latitudes by Southern Ocean storm tracks. Antarctic aerosol number and mass concentrations are not only non-negligible but perhaps play a more important role than previously recognized because of the higher sensitivities of clouds at the very low concentrations caused by the large-scale dynamical isolation. Antarctic aerosol chemical composition, particularly organic components, has implications for local cloud microphysics. The AWARE dataset, fully available online in the ARM Program data archive, offers numerous case studies for unique and rigorous evaluation of mixed-phase cloud parameterization in climate models.

54 ENVIRONMENTAL SCIENCES↗

Perovskite Sorbent Oxygen Separation Modeling with MFiX

This document chronicles the development and implementation of computational kinetic rate models that capture absorption and desorption characteristics of the National Energy Technology Laboratory (NETL) developed perovskite, Sr 1-x Ca x FeO 3-δ . Two paths to create accurate kinetic rates were followed: (1) an isothermal rate approach where thermogravimetric (TGA) data are recast as oxygen capacities through a pseudo-second order Lagergren equation (He et al., 2009); and (2) a more traditional Arrhenius approach where experimental data are fit with a power law model to derive associate activation energies (Bulfin et al., 2020a). For reference, the mathematics and associate experimental strategies that support these derivations are included in this report. In addition, computational fluid dynamics (CFD) models were developed to utilize both kinetic rate formulations and applied to simulate oxygen uptake and release in small scale scenarios. The program Multiphase Flow with interphase eXchanges (MFiX) was used to create: (1) discrete element method (DEM) simulations of a single tube of granular perovskite experiencing isothermal O 2 -absorption; and desorption and (2) two-fluid-model (TFM) non-isothermal simulations of perovskite O 2 -absorption and desorption tubes that share a wall. Conjugate heat transfer between steel walled tubes and the perovskite bed were managed with user-defined functions. As the project moves to simulating larger scale devices that will require more robust conjugate heat transfer methods, developed kinetic rates and associate methodologies have been recast for use in the ANSYS Fluent CFD program.

36 MATERIALS SCIENCE↗

Thermal Neutron Scattering Evaluation Methods Development at ORNL [Slides]

The goal of the project was to develop a procedure to generate covariance matrix for S( α,β ) data that incorporated both computational simulations and experimental data. Experimental data and computer simulation fit is achieved using the Unified Monte Carlo (UMC) method. The framework is material & simulation method independent, and this is demonstrated using light water. A methodology was developed for generalized generation of covariances for thermal scattering files. The framework was subsequently tested on light water by generating covariance of pDOS with encouraging results. Preliminary results suggest temperature effects of polyethylene may warrant further investigation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

High Intensity Gamma Ray Source Scintillation Attenuation Spectrometer and Filter Stack Monoenergetic Calibration

The Laser-Based X-ray Radiographic Imaging team at Los Alamos National Lab is looking for a monoenergetic MeV X-ray source to both verify our Monte Carlo N-particle simulations of detector performance and calibrate the instruments for future measurements. Funded by the Laboratory Directed Research and Development (LDRD) program, our overall goal is to improve the radiographic quality and reliability of laser-based X-ray sources for deployment at both dynamic and static radiography facilities. Laser-based X-ray sources have demonstrated smaller spot sizes to current electron accelerator based sources. The smaller laser spot size leads to significantly improved resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Novel experimental probes of QCD in SIDIS and e + e - annihilation (Final Technical Report)

The research addressed with this award seeks to advance our understanding of the structure and dynamics underlying the properties of visible matter. In our current understanding the nucleons (protons and neutrons) are not fundamental but are comprised of quarks and gluons, which are collectively called partons. A static quark picture fails to explain the properties of the nucleons, such as their mass and intrinsic spin, which are thought to emerge dynamically from the quark-gluon interactions via the strong force. In this work, novel observables employing correlations of particles produced in the scattering of high energy electrons off protons at the CLAS12 experiment at Jefferson Lab were analyzed to probe quark-gluon interactions. The ultimate goal of this line of inquiry is to be able to describe the properties of protons and neutrons from first principles, similar to how studying the hydrogen atom has led to the formulation of the theory of Quantum Electrodynamics. Because quarks cannot be observed directly but only as part of more complex composite particles, a smaller, complimentary part of this work was the analysis of particle production in electron-positron annihilation at the Belle II experiment to understand the production of particles from initial quarks. This takes advantage of the fact that in e + e - annihilation the initial quark dynamics is known, unlike in the scattering of nucleons. Several new applications using Machine Learning algorithms for event tagging and reconstruction to support this program were developed as part of this award. In addition, we had a significant role in the development of the physics program for the future Electron-Ion Collider, which is a new collider to be build in the US within the next decade.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Orson Anderson Era of Mineral Physics at Lamont in the 1960s

From 1964 to the early 1970s, Orson Anderson led a research program at the Lamont Geological Observatory in the newly-emerging field of “mineral physics”. In collaboration with colleagues Edward Schreiber and Naohiro Soga, Orson exploited the techniques of physical acoustics to study the behavior of the sound velocities of minerals at elevated pressures and temperatures. This research program also included semi-empirical studies of the relationships between the bulk modulus and the molar volume of solids, the use of lattice dynamics to calculate the elastic moduli of cubic structures as a function of pressure to predict instabilities, and theoretical investigations of the Lagrangian and Eulerian formulations of finite strain equations of state.

58 GEOSCIENCES↗

The Time Domain Spectroscopic Survey: Changing-look Quasar Candidates from Multi-epoch Spectroscopy in SDSS-IV

Active galactic nuclei (AGN) can vary significantly in their rest-frame optical/UV continuum emission, and with strong associated changes in broad line emission, on much shorter timescales than predicted by standard models of accretion disks around supermassive black holes. Most such changing-look or changing-state AGN—and at higher luminosities, changing-look quasars (CLQs)—have been found via spectroscopic follow-up of known quasars showing strong photometric variability. The Time Domain Spectroscopic Survey of the Sloan Digital Sky Survey IV (SDSS-IV) includes repeat spectroscopy of large numbers of previously known quasars, many selected irrespective of photometric variability, and with spectral epochs separated by months to decades. Our visual examination of these repeat spectra for strong broad line variability yielded 61 newly discovered CLQ candidates. We quantitatively compare spectral epochs to measure changes in continuum and Hβ broad line emission, finding 19 CLQs, of which 15 are newly recognized. The parent sample includes only broad line quasars, so our study tends to find objects that have dimmed, i.e., turn-off CLQs. However, we nevertheless find four turn-on CLQs that meet our criteria, albeit with broad lines in both dim and bright states. We study the response of Hβ and Mg ii emission lines to continuum changes. The Eddington ratios of CLQs are low, and/or their Hβ broad line width is large relative to the overall quasar population. Repeat quasar spectroscopy in the upcoming SDSS-V black hole Mapper program will reveal significant numbers of CLQs, enhancing our understanding of the frequency and duty cycle of such strong variability, and the physics and dynamics of the phenomenon.

79 ASTRONOMY AND ASTROPHYSICS↗

Post-Transcriptional Mechanisms Respond Rapidly to Ecologically Relevant Thermal Fluctuations During Temperature-Dependent Sex Determination

An organism’s ability to integrate transient environmental cues experienced during development into molecular and physiological responses forms the basis for adaptive shifts in phenotypic trajectories. During temperature-dependent sex determination (TSD), thermal cues during discrete periods in development coordinate molecular changes that ultimately dictate sexual fate and contribute to patterns of inter- and intra-sexual variation. How these mechanisms interface with dynamic thermal environments in nature remain largely unknown. By deploying thermal loggers in wild nests of the American alligator (Alligator mississippiensis) over two consecutive breeding seasons, we observed that 80% of nests exhibit both male- and female-promoting thermal cues during the thermosensitive period, and of these nests, all exhibited both male- and female-promoting temperatures within the span of a single day. These observations raise a critical question—how are opposing environmental cues integrated into sexually dimorphic transcriptional programs across short temporal scales? To address this question, alligator embryos were exposed to fluctuating temperatures based on nest thermal profiles and sampled over the course of a daily thermal fluctuation. We examined the expression dynamics of upstream genes in the temperature-sensing pathway and find that post-transcriptional alternative splicing and transcript abundance of epigenetic modifier genes JARID2 and KDM6B respond rapidly to thermal fluctuations while transcriptional changes of downstream effector genes, SOX9 and DMRT1, occur on a delayed timescale. Our findings reveal how the basic mechanisms of TSD operate in an ecologically relevant context. We present a hypothetical hierarchical model based on our findings as well as previous studies, in which temperature-sensitive alternative splicing incrementally influences the epigenetic landscape to affect the transcriptional activity of key sex-determining genes.

59 BASIC BIOLOGICAL SCIENCES↗

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗

Development of a Data Platform for High-Temperature Gas-cooled Reactor (HTGR) Nuclear Energy University Program (NEUP) Thermal-Fluid Experiments

Since the U.S. Department of Energy (DOE)’s Office of Nuclear Energy (NE) initiated the Nuclear Energy University Program (NEUP) in 2009, a total of 30 NEUP projects focused on High-Temperature Gas-cooled Reactor (HTGR) thermal-fluid experiments were funded up to fiscal year (FY) 2021. This represents a total DOE investment of approximately $23M over the 12-year period, covering thermal fluid phenomena important to both pebble bed and prismatic HTGR designs. The NEUP projects have produced a large amount of high-quality experimental and computational data that were published in final project reports, journal articles, dissertations, and conference proceedings, but in most cases the actual data sets and supporting information such as facility and instrumentation descriptions were not publicly disseminated to the HTGR community. To the authors’ best knowledge, a data platform that organizes and summarizes these NEUP-funded projects for HTGR research does not currently exist. To improve access to this HTGR validation data and optimize the return on the significant investment made by DOE, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program started a survey of completed and ongoing HTGR NEUP projects with the aim of developing a public-access data platform that can be used to retrieve computational fluid dynamics (CFD) and system code validation data and guide future NEUP investments. This paper summarizes the status of the current ART-GCR database, provides an overview of the NEUP-funded HTGR-related research projects from FY2009 to FY2021 and identify validation knowledge gaps still existing in HTGR thermal-fluid research.

42 ENGINEERING↗

A multi-stage stochastic programming model for adaptive biomass processing operation under uncertainty

Variations of physical and chemical characteristics of biomass reduce equipment utilization and increase operational costs of biomass processing. Biomass processing facilities use sensors to monitor the changes in biomass characteristics. Integrating sensory data into the operational decisions in biomass processing will increase its flexibility to the changing biomass conditions. In this paper, we propose a multi-stage stochastic programming model that minimizes the expected operational costs by identifying the initial inventory level and creating an operational decision policy for equipment speed settings. These policies take the sensory information data and the current biomass inventory level as inputs to dynamically adjust inventory levels and equipment settings according to the changes in the biomass' characteristics. We ensure that a prescribed target reactor utilization is consistently achieved by penalizing the violation of the target reactor feeding rate. A case study is developed using real-world data collected at Idaho National Laboratory's biomass processing facility. We show the value of multi-stage stochastic programming from an extensive computational experiment. Our sensitivity analysis indicates that updating the infeed rate of the system, the processing speed of equipment, and bale sequencing based on the moisture level of biomass improves the processing rate of the reactor and reduces operating costs.

09 BIOMASS FUELS↗

A fast reduced model for a shell-and-tube based latent heat thermal energy storage heat exchanger and its application for cost optimal design by nonlinear programming

Numerical simulation of latent heat thermal energy storage (LHTES) systems plays a fundamental role in studying the physical process and guiding the engineering design. Discretization of the PDEs describing the nonlinear solidification/melting process of phase change materials (PCMs) leads to a large-scale complex dynamics system, where the system behavior depends on a set of parameters. In a design setting, repeated model evaluations are required over the set of parameters results in significant computational burden. In this paper, an explicit analytic solution was built for the propagation of the solidification front in a cylindrical coordinate. The analytic solution approach is further employed to develop a low computational reduced model (RM) as a module for a shell-and-tube based LHTES heat exchanger. The levelized Cost of Energy (LCOE) is used as a design metric and the RM model is used to apply system-level constraints in the nonlinear programming formulation that facilitates efficient global optimal design of the PCM properties, flow conditions and tube geometries. The use of LCOE as the design metric prevents over design of the heat transfer rate and also establishes a fair ground for evaluation of different thermal storage technologies and their integrated applications with other systems. Optimal results showed that a higher effectiveness results in a higher LCOE; the velocity of the HTF and the length of the channel are highly correlated with each other; both larger PCM latent energy and conductivity result in lower LCOE.

25 ENERGY STORAGE↗

Dynamics of X-pinches Powered by a Capacitor Bank

X-pinches are formed by crossing two metal wires in the shape of the letter ‘X’ between the electrodes of a pulsed power device. The plasma generated then evolves in complex ways and has been the subject of many experiments and simulations, both as a plasma object and for its use as a source of intense soft x-rays, of interest to high energy density plasma (HEDP) studies. The dynamics of the x-pinch that lead to the emission x-ray photons begin soon after this initial explosive phase, resulting in the formation of a micro z-pinch (≤ 300 µm long, ~100 µm diameter) at the crossing point. If the current is high enough, then a subsonic plasma implosion in the micro z-pinch begins, which creates a high density, high temperature plasma. These x-pinches have been typically studied at the nanosecond time scale (rise-time $τ_r ≤ 100 ns, dI/dt > 1 kA/ns$). The microsecond x-pinch ($I_p~350 kA, τ_{1/4} = 1 µs, 0.3 kA/ns$) allows a different parameter space to be studied that compliments HEDP studies in the nanosecond regime (with an attendant lower hard-radiation hazard) but it also creates plasma conditions that are interesting in their own right, with features that make it a good model for studying the hydrodynamics of astrophysical jets, for example. With high electron density and temperatures pushing close to 0.5 keV, it is relevant for high energy density studies and provides a suitable test bed for the spectroscopy of highly ionized atoms. The aim of the original proposal was to initiate a new experimental plasma research program at Florida A&M University with three main objectives: (1) To create x-pinch plasmas from different materials using a direct capacitor bank discharge and to study the dynamics of the high-density plasmas and their associated soft x-ray emission properties and potential applications. (2) Understanding the nature of the supersonic plasma jets observed in the mid-plane of the microsecond x-pinch and their relevance as a laboratory model for studying astrophysical jets. (3) To provide a research platform to support the education of under-represented undergraduate and graduate students at Florida A&M University and to provide training in high energy density laboratory plasma physics. Each of the main objectives has been met and results of the work have been published in refereed journals or presented at several scientific meetings. A number of students both undergraduate and graduate have participated in the research program in a hands-on way and have thereby acquired training in high energy density physics. The success of the work can also be measured in two PhD dissertations (one of which is still in progress). The acquisition of important research equipment and instrumentation means that the work can continue in some fashion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A data-driven linear formulation of the optimal demand response scheduling problem for an industrial air separation unit

Demand response (DR) has become a key element in balancing the power grid as the contribution of time-varying renewable power generation increases. Chemical plants are appealing candidates for DR programs as they offer large, concentrated and flexible loads. DR participation calls for frequent production rate changes over time scales that overlap with the dominant dynamics of the plant. Production scheduling should therefore consider the process dynamics explicitly. Here we present a data-driven approach for modelling the scheduling-relevant dynamics based on historical closed-loop operating data using autoregressive with extra inputs (ARX) models. We introduce a new, linear scheduling problem formulation based on the ARX representation, and demonstrate its implementation on an industrial air separation unit.

42 ENGINEERING↗

Cellular fluidics

The natural world provides many examples of multiphase transport and reaction processes that have been optimized by evolution. These phenomena take place at multiple length and time scales and typically include gas–liquid–solid interfaces and capillary phenomena in porous media. Many biological and living systems have evolved to optimize fluidic transport. However, living things are exceptionally complex and very difficult to replicate, and human-made microfluidic devices (which are typically planar and enclosed) are highly limited for multiphase process engineering. In this paper, we introduce the concept of cellular fluidics: a platform of unit-cell-based, three-dimensional structures—enabled by emerging 3D printing methods—for the deterministic control of multiphase flow, transport and reaction processes. We show that flow in these structures can be ‘programmed’ through architected design of cell type, size and relative density. We demonstrate gas–liquid transport processes such as transpiration and absorption, using evaporative cooling and CO 2 capture as examples. We design and demonstrate preferential liquid and gas transport pathways in three-dimensional cellular fluidic devices with capillary-driven and actively pumped liquid flow, and present examples of selective metallization of pre-programmed patterns. Our results show that the design and fabrication of architected cellular materials, coupled with analytical and numerical predictions of steady-state and dynamic behaviour of multiphase interfaces, provide deterministic control of fluidic transport in three dimensions. Cellular fluidics may transform the design space for spatial and temporal control of multiphase transport and reaction processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗