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At least 1,369 records · Page 76

Low-loss low thermo-optic coefficient Ta 2 O 5 on crystal quartz planar optical waveguides

Optical resonator-based frequency stabilization plays a critical role in ultra-low linewidth laser emission and precision sensing, atom clocks, and quantum applications. However, there has been limited success in translating traditional bench-top stabilization cavities to compact on-chip integrated waveguide structures that are compatible with photonic integration. The challenge lies in realizing waveguides that not only deliver low optical loss but also exhibit a low thermo-optic coefficient and frequency noise stability. Given the problematic sources of frequency noise within dielectrics, such as thermorefractive noise, resonators with small thermo-optic response are desirable for on-chip reference cavities. We report the first demonstration of a Ta 2 O 5 (tantala) waveguide core fabricated on a crystal quartz substrate lower cladding with TEOS-PECVD SiO 2 upper cladding. This waveguide offers significant advantages over other waveguides in terms of its low thermo-optic coefficient and reduced thermorefractive-related frequency noise. We describe the waveguide structure and key design parameters as well as fabrication considerations for processing tantala on quartz waveguides. We report a waveguide thermo-optic coefficient of -1.14 × 10 -6 RIU/K, a value that is over 6 times smaller in magnitude than that of SiO 2 -substrate tantala waveguides, with a propagation loss of 1.19 dB/cm at 1550 nm and <1.33 dB/cm across the 1525 nm–1610 nm wavelength range. Within a 1.6 mm radius ring resonator, we demonstrate a 2.54 × 10 5 intrinsic Q factor. With the potential for very low loss and the ability to control the thermal response, this waveguide platform takes a key step toward creating thermally stable integrated resonators for on-chip laser frequency stabilization and other applications.

42 ENGINEERING↗

Modeling of a Networked Community Microgrid with High Solar Penetration Considering Control Dynamics of Inverter-Based Resources

Microgrids help facilitate the integration of renewable energy in distribution-level grids and increase the resilience of the electric grid to extreme weather, especially in rural areas. Compared to traditional microgrids, a networked microgrid leverages multiple grid-forming sources to form a potential meshed grid and is more flexible in operation. This paper demonstrates the simulation modeling of an actual networked microgrid located in Adjuntas, Puerto Rico. The model contains representations of power inverters that connect the battery energy storage systems and photovoltaic generation systems to the networked microgrid and is capable of simulating fast grid transients as well as long-term operation of the networked microgrid. The modeling technique for power inverters allows the time-efficient simulation of the microgrid with a minimal penalty on model accuracy.

Li, Dingrui↗

Literature Data on Foam Fracturing Fluid

At the beginning of this project, the Temple team spent significant effort to collect data relevant to foam fracturing. More than 40 articles/reports were found in the open literature that reported the properties of aqueous foams under various testing conditions. The foam properties included viscosity and stability in terms of half-life, while were influenced by the foam quality, shear rate, temperature, pressure, as well as surfactants and additives used in making the foam base solutions. As a result, more than 1100 data points were collected, which are included in a master worksheet named "Literature data on Foam Fracturing Fluid". These data points are organized based on following parameters: 1. Literature source, including authors and publication year 2. Gaseous phase (e.g. CO2, N2) 3. Liquid phase (e.g. tap water, DI water, salt water) 4. Surfactants and their concentrations 6. Additives 7. Foam quality 8. Pressure 9. Temperature 10. Viscosity 11. Foam stability, which was characterized by its half-life: Half-life Foam study data base with data analysis was completed and a webpage is designed hosted on public server at https://surfactant-dashboard.herokuapp.com

15 GEOTHERMAL ENERGY↗

An Appraisal of the Performance and Characteristics of Summary Rays Calculated for the SALSA3D Traveltime Dataset

The SALSA3D tomographic model provides a crucial community resource for improving the quality (in terms of both accuracy and precision) of predictions of the traveltimes of seismic waves and therefore improving our ability to locate anthropogenic or natural seismic events. Constructing the requisite tomographic model requires addressing the challenges implied by a massive and growing dataset of traveltime measurements. This study explores one approach to tackle this challenge: the use of summary rays, which average traveltime measurements from sources within evenly spaced cells, thereby eliminating redundant data.

58 GEOSCIENCES↗

Functional Principal Component Analysis of Radio–Optical Reference Frame Tie

The Gaia optical reference frame is intrinsically undefined with respect to global orientation and spin, so it needs to be anchored in the radio-based International Celestial Reference Frame (ICRF) to provide a referenced and quasi-inertial celestial coordinate system. The link between the two fundamental frames is realized through two samples of distant extragalactic sources, mostly active galactic nuclei and quasars, but only the smaller sample of radio-loud ICRF sources with optical counterparts is available to determine the mutual orientation. The robustness of this link can be mathematically formulated in the framework of functional principal component analysis using a set of vector spherical harmonics to represent the differences in celestial positions of the common objects. The weakest eigenvectors are computed, which describe the greatest deficiency of the link. The deficient or poorly determined terms are specific vector fields on the sphere that carry the largest errors of absolute astrometry using Gaia in reference to the ICRF. This analysis provides guidelines for the future development of the ICRF maximizing the accuracy of the link over the entire celestial sphere. A measure of the robustness of a least-squares solution, which can be applied to any linear model fitting problem, is introduced to help discriminate between reference frame tie models of different degrees.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simulation, Challenge Testing and Validation of Solutions for Residential and Commercial Occupancy Sensing/Counting and CO2 Sensing (Final Report)

Carbon dioxide sensors used for monitoring and control applications in buildings are known to be sensitive to long term drift and can be affected by variations in temperature, humidity, other gas interferents, pressure and other factors that cannot be corrected through the typical auto-calibration methods often embedded in the sensor electronics. This investigation was part of the Category D defined in the ARPA-E Saving Energy Nationwide in Structures With Occupancy Recognition (SENSOR) Financial Assistance Funding Opportunity Announcement No. DE-FOA-0001737, FFDA No. 81.135, January 18, 2017. The FOA defined target criteria for the evaluation of the Category C commercial CO2 sensors selected for review and development through the ARPA-E SENSOR program and charged the Iowa State Category D team with developing an evaluation methodology for Category C sensors in accordance with these criteria. As part of the work, the Iowa State team chose to engage the standards community in the development of the evaluation methodology. Standard development work in the D22.05 Indoor Air and D22.03 Ambient Atmospheres and Source Emissions subcommittees of ASTM International Committee D22 on Air Quality on the evaluation of low cost sensors and provision of guidance for using indoor carbon dioxide concentrations to evaluate indoor air quality and ventilation is of particular relevance to the Category D efforts. To date, three draft standards with specific input by the Iowa State Category D team have passed the subcommittee balloting stage and are being balloted in December 2022 and January 2023 in the main D22 committee. In addition to the aforementioned standards to which the PI was a contributing author, intellectual property developed in this project pertaining to “An Automated System for Evaluation of the Long Term Performance of Carbon Dioxide Sensors” and “An Automated Ground Truth System for Real-Time Reliability Assessment, Capture of Control Decisions and Energy Savings Measurements for Occupancy Recognition Systems and Other Applications” are the other major deliverables of the project. These standards and the developed intellectual property are expected to benefit the public in a number of ways stemming from their provision of means to benchmark the performance of carbon dioxide and other sensor systems. In particular, there is high interest in techniques to demonstrate the performance of low-cost carbon dioxide sensors which can be used for typical HVAC applications (e.g., demand controlled ventilation, outdoor and indoor air monitoring, estimation of occupancy, etc.).

42 ENGINEERING↗

EFT at FASERν

We investigate the sensitivity of the FASERv detector to new physics in the form of non-standard neutrino interactions. FASERv which will be installed 480 m downstream of the ATLAS interaction point, will for the first time study interactions of multi-TeV neutrinos from a controlled source. Our formalism — which is applicable to any current and future neutrino experiment — is based on the Standard Model Effective Theory (SMEFT) and its counterpart, Weak Effective Field Theory (WEFT), below the electroweak scale. Starting from the WEFT Lagrangian, we compute the coefficients that modify neutrino production in meson decays and detection via deep-inelastic scattering, and we express the new physics effects in terms of modified flavor transition probabilities. For some coupling structures, we find that FASERv will be able to constrain interactions that are two to three orders of magnitude weaker than Standard Model weak interactions, implying that the experiment will be indirectly probing new physics at the multi-TeV scale. In some cases, FASERv constraints will become comparable to existing limits — some of them derived for the first time in this paper — already with 150 fb -1 of data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Geothermal play fairway analysis, part 1: Example from the Snake River Plain, Idaho

The Snake River Plain (SRP) volcanic province overlies the track of the Yellowstone hotspot, a thermal anomaly that extends deep into the mantle. Most of the area is underlain by a basaltic volcanic province that overlies a mid-crustal intrusive complex, which in turn provides the long-term heat flux needed to sustain geothermal systems. Previous studies have identified several known geothermal resource areas within the SRP. For the geothermal study presented herein, our goals were to: (1) adapt the methodology of Play Fairway Analysis (PFA) for geothermal exploration to create a formal basis for its application to geothermal systems, (2) assemble relevant data for the SRP from publicly available and private sources, and (3) build a geothermal PFA model for the SRP and identify the most promising plays, using GIS-based software tools that are standard in the petroleum industry. The study focused on identifying three critical resource parameters for exploitable hydrothermal systems in the SRP: heat source, reservoir and recharge permeability, and cap or seal. Data included in the compilation for heat source were heat flow, distribution and ages of volcanic vents, groundwater temperatures, thermal springs and wells, helium isotope anomalies, and reservoir temperatures estimated using geothermometry. Reservoir and recharge permeability was inferred from the analysis of stress orientations and magnitudes, post-Miocene faults, and subsurface structural lineaments based on magnetics and gravity data. Data for cap or seal included the distribution of impermeable lake sediments and clay-seal associated with hydrothermal alteration below the regional aquifer. These data were used to compile Common Risk Segment maps for heat, permeability, and seal, which were combined to create a Composite Common Risk Segment map for all southern Idaho that reflects the risk associated with geothermal resource exploration and identifies favorable resource tracks. Our regional assessment indicated that undiscovered geothermal resources may be located in several areas of the SRP. Two of these areas, the western SRP and Camas Prairie, were selected for more detailed assessment, during which heat, permeability, and seal were evaluated using newly collected field data and smaller grid parameters to refine the location of potential resources. These higher resolution assessments illustrate the flexibility of our approach over a range of scales.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of EDM experiments in paramagnetic atoms and molecules to hadronic CP violation

Experiments searching for the electric dipole moment (EDM) of the electron d e utilize atomic/molecular states with one or more uncompensated electron spins, and these paramagnetic systems have recently achieved remarkable sensitivity to d e . If the source of CP violation resides entirely in the hadronic sector, the two-photon exchange processes between electrons and the nucleus induce CP-odd semileptonic interactions, parametrised by the Wilson coefficient C SP , and provide the dominant source of EDMs in paramagnetic systems instead of d e . We evaluate the C SP coefficients induced by the leading hadronic sources of CP violation, namely nucleon EDMs and CP-odd pion-nucleon couplings, by calculating the nucleon-number-enhanced CP-odd nuclear scalar polarisability, employing chiral perturbation theory at the nucleon level and the Fermi-gas model for the nucleus. This allows us to translate the ACME EDM limits from paramagnetic ThO into novel independent constraints on the QCD theta term |$\bar θ$| < 3 × 10 –8 , proton EDM |d p | < 2 × 10 –23 e cm, isoscalar CP-odd pion-nucleon coupling |$\bar g$$^{(1)}_{πNN}$| < 4 × 10 –10 , and color EDMs of quarks |$\tilde d$ u -$\tilde $d d | < 2 × 10 –24 cm. We note that further experimental progress with EDM experiments in paramagnetic systems may allow them to rival the sensitivity of EDM experiments with neutrons and diamagnetic atoms to these quantities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

CATMoS: Collaborative Acute Toxicity Modeling Suite

Background: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. Objectives: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different endpoints: LD50 value, U.S. Environmental Protection Agency hazard categories, Globally Harmonized System for Classification and Labelling hazard categories, very toxic chemicals (LD50 =50 mg/kg), and non-toxic chemicals (LD50 >2000 mg/kg). Methods: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. Results: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared to in vivo results. Discussion: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for over 800,000 chemicals have been made available via the NTP’s Integrated Chemical Environment. The models are also implemented in a free, standalone open-source tool, OPERA, which allows predictions of new and untested chemicals to be made.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

The Hα Dots Survey. II. A Second List of Faint Emission-line Objects

We present the second catalog of serendipitously discovered compact extragalactic emission-line sources—Hα Dots. These objects have been discovered in searches of moderately deep narrow-band images acquired for the ALFALFA Hα project. In addition to cataloging 119 new Hα Dots, we also present follow-up spectral data for the full sample. These spectra allow us to confirm the nature of these objects as true extragalactic emission-line objects, to classify them in terms of activity type (star-forming or AGN), and to identify the emission line via which they were discovered. We tabulate photometric and spectroscopic data for the all objects, and we present an overview of the properties of the full Hα Dot sample. The Hα Dots represent a broad range of star-forming and active galaxies detected via several different emission lines over a wide range of redshifts. The sample includes Hα-detected blue compact dwarf galaxies at low redshift, [O iii]-detected Seyfert 2 and Green Pea-like galaxies at intermediate redshifts, and QSOs detected via one of several UV emission lines, including Lyα. Despite the heterogeneous appearance of the resulting catalog of objects, we show that our selection method leads to well-defined samples of specific classes of emission-line objects with properties that allow for statistical studies of each class.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of secondary organic aerosol simulation bias in the Community Earth System Model (CESM2.1)

Organic aerosol (OA) has been considered as one of the most important uncertainties in climate modeling due to the complexity in presenting its chemical production and depletion mechanisms. To better understand the capability of climate models and probe into the associated uncertainties in simulating OA, we evaluate the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 (CAM6) with comprehensive tropospheric and stratospheric chemistry representation (CAM6-Chem) through a long-term simulation (1988–2019) with observations collected from multiple datasets in the United States. We find that CESM generally reproduces the interannual variation and seasonal cycle of OA mass concentration at surface layer with a correlation of 0.40 compared to ground observations and systematically overestimates (69%) in summer and underestimates (-19%) in winter. Through a series of sensitivity simulations, we reveal that modeling bias is primarily related to the dominant fraction of monoterpene-formed secondary organic aerosol (SOA), and a strong positive correlation of 0.67 is found between monoterpene emission and modeling bias in the eastern US during summer. In terms of vertical profile, the model prominently underestimates OA and monoterpene concentrations by 37%–99% and 82%–99%, respectively, in the upper air (>500 m) as validated against aircraft observations. Our study suggests that the current volatility basis set (VBS) scheme applied in CESM might be parameterized with monoterpene SOA yields that are too high, which subsequently results in strong SOA production near the emission source area. We also find that the model has difficulty in reproducing the decreasing trend of surface OA in the southeastern US probably because of employing pure gas VBS to represent isoprene SOA which is in reality mainly formed through multiphase chemistry; thus, the influence of aerosol acidity and sulfate particle change on isoprene SOA formation has not been fully considered in the model. This study reveals the urgent need to improve the SOA modeling in climate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The De-Icing Comparison Experiment (D-ICE): a study of broadband radiometric measurements under icing conditions in the Arctic

Abstract. Surface-based measurements of broadband shortwave (solar) and longwave (infrared) radiative fluxes using thermopile radiometers are made regularly around the globe for scientific and operational environmental monitoring. The occurrence of ice on sensor windows in cold environments – whether snow, rime, or frost – is a common problem that is difficult to prevent as well as difficult to correct in post-processing. The Baseline Surface Radiation Network (BSRN) community recognizes radiometer icing as a major outstanding measurement uncertainty. Towards constraining this uncertainty, the De-Icing Comparison Experiment (D-ICE) was carried out at the NOAA Atmospheric Baseline Observatory in Utqiaġvik (formerly Barrow), Alaska, from August 2017 to July 2018. The purpose of D-ICE was to evaluate existing ventilation and heating technologies developed to mitigate radiometer icing. D-ICE consisted of 20 pyranometers and 5 pyrgeometers operating in various ventilator housings alongside operational systems that are part of NOAA's Barrow BSRN station and the US Department of Energy Atmospheric Radiation Measurement (ARM) program North Slope of Alaska and Oliktok Point observatories. To detect icing, radiometers were monitored continuously using cameras, with a total of more than 1 million images of radiometer domes archived. Ventilator and ventilator–heater performance overall was skillful with the average of the systems mitigating ice formation 77 % (many >90 %) of the time during which icing conditions were present. Ventilators without heating elements were also effective and capable of providing heat through roughly equal contributions of waste energy from the ventilator fan and adiabatic heating downstream of the fan. This provided ∼0.6 ∘C of warming, enough to subsaturate the air up to a relative humidity (with respect to ice) of ∼105 %. Because the mitigation technologies performed well, a near complete record of verified ice-free radiometric fluxes was assembled for the duration of the campaign. This well-characterized data set is suitable for model evaluation, in particular for the Year of Polar Prediction (YOPP) first Special Observing Period (SOP1). We used the data set to calculate short- and long-term biases in iced sensors, finding that biases can be up to +60 W m−2 (longwave) and −211 to +188 W m−2 (shortwave). However, because of the frequency of icing, mitigation of ice by ventilators, cloud conditions, and the timing of icing relative to available sunlight, the biases in the monthly means were generally less than the aggregate uncertainty attributed to other conventional sources in both the shortwave and longwave.

54 ENVIRONMENTAL SCIENCES↗

O'Hare Airport roadway traffic prediction via data fusion and Gaussian process regression

This study proposes an approach of leveraging information gathered from multiple traffic data sources at different resolutions to obtain approximate inference on the traffic distribution of Chicago's O'Hare Airport area. Specifically, it proposes the ingestion of traffic datasets at different resolutions to build spatiotemporal models for predicting the distribution of traffic volume on the road network. Due to its good adaptability and flexibility for spatiotemporal data, the Gaussian process (GP) regression was employed to provide short-term forecasts using data collected by loop detectors (sensors) and supplemented by telematics data. The GP regression is used to make predictions of the distribution of the proportion of sensor data traffic volume represented by the telematics data for each location of the sensors. Consequently, the fitted GP model can be used to determine the approximate traffic distribution for a testing location outside of the training points. Policymakers in the transportation sector can find the results of this work helpful for making informed decisions relating to current and future transportation conditions in the area.

42 ENGINEERING↗

Atmospheric Structure Prediction for Infrasound Propagation Modeling Using Deep Learning

Abstract Infrasound is generated by a variety of natural and anthropogenic sources. Infrasonic waves travel through the dynamic atmosphere, which can change on the order of minutes to hours. Infrasound propagation largely depends on the wind and temperature structure of the atmosphere. Numerical weather prediction models are available to provide atmospheric specifications, but uncertainties in these models exist and they are computationally expensive to run. Machine learning has proven useful in predicting tropospheric weather using Long Short‐Term Memory (LSTM) networks. An LSTM network is utilized to make atmospheric specification predictions up to ∼30 km for three different training and testing scenarios: (a) the model is trained and tested using only radiosonde data from the Albuquerque, NM, USA station, (b) the model is trained on radiosonde stations across the contiguous US, excluding the Albuquerque, NM, USA station, which was reserved for testing, and (c) the model is trained and tested on radiosonde stations across the contiguous US. Long Short‐Term Memory predictions are compared to a state‐of‐the‐art reanalysis model and show cases where the LSTM outperforms, performs equally as well, or underperforms in comparison to the state‐of‐the‐art. Regional and temporal trends in model performance across the US are also discussed. Results suggest that the LSTM model is a viable tool for predicting atmospheric specifications for infrasound propagation modeling.

54 ENVIRONMENTAL SCIENCES↗

CODEX clusters

Context: Large area catalogs of galaxy clusters constructed from ROSAT All-Sky Survey provide the basis for our knowledge of the population of clusters thanks to long-term multiwavelength efforts to follow up observations of these clusters. Aims: The advent of large area photometric surveys superseding previous, in-depth all-sky data allows us to revisit the construction of X-ray cluster catalogs, extending the study to lower cluster masses and higher redshifts and providing modeling of the selection function. Methods: We performed a wavelet detection of X-ray sources and made extensive simulations of the detection of clusters in the RASS data. We assigned an optical richness to each of the 24 788 detected X-ray sources in the 10 382 square degrees of the Baryon Oscillation Spectroscopic Survey area using red sequence cluster finder redMaPPer version 5.2 run on Sloan Digital Sky Survey photometry. We named this survey COnstrain Dark Energy with X-ray (CODEX) clusters. Results: We show that there is no obvious separation of sources on galaxy clusters and active galactic nuclei (AGN) based on the distribution of systems on their richness. This is a combination of an increasing number of galaxy groups and their selection via the identification of X-ray sources either by chance or by groups hosting an AGN. To clean the sample, we use a cut on the optical richness at the level corresponding to the 10% completeness of the survey and include it in the modeling of the cluster selection function. We present the X-ray catalog extending to a redshift of 0.6. Conclusions: The CODEX suvey is the first large area X-ray selected catalog of northern clusters reaching fluxes of 10 –13 ergs s –1 cm –2 . We provide modeling of the sample selection and discuss the redshift evolution of the high end of the X-ray luminosity function (XLF). Our results on z < 0.3 XLF agree with previous studies, while we provide new constraints on the 0.3 < z < 0.6 XLF. We find a lack of strong redshift evolution of the XLF, provide exact modeling of the effect of low number statistics and AGN contamination, and present the resulting constraints on the flat ΛCDM.

79 ASTRONOMY AND ASTROPHYSICS↗

Parameterized anomalous transport model for current-carrying collisionless plasmas in pulsed power inertial confinement fusion

Current delivery in pulsed power inertial confinement fusion is influenced by collisionless current-carrying microturbulent plasmas, which are sourced from electrode surfaces. In this setting, the lower hybrid drift instability—triggered by plasma acceleration—is a leading candidate driver of difficult-to-predict momentum and energy transport. To characterize the nonlinear state of the microturbulent plasma, a parameterized anomalous transport model is developed for the instability, with analytic formulas for anomalous collision frequency, resistivity, and species heating rates. The formulas are expressed in terms of linear-theory variables and four dimensionless parameters that characterize the macroscopic plasma state. The model is built on linear theory analysis, power law analysis, and quasilinear theory analysis, and is validated using a series of nonlinear continuum kinetic Vlasov–Poisson simulations. The theoretical and computational investigation demonstrates that the anomalous collision frequency associated with the instability can be reliably approximated, within about a factor of five or better, by the unscaled linear theory growth rate of the fastest-growing wavenumber mode. This finding enables efficient calculation of anomalous resistivity and species heating rates over a wide range of plasma conditions, resulting in improved predictive capabilities.

Complex functions↗