Securing Your Applications: An Introduction to OAuth 2.0 and OpenID Connect (OIDC)
Discussion of open standards OAuth 2.0 and Open ID Connect
Hooks, Ronald Fred [Sandia National Laboratories (↗
SEARCH · Engineering Papers
Results for “CONNECTIONS”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Emerald Connections Weatherization Plus Health Pilot Program
The Emerald Connections Weatherization Plus Health Pilot Program (Healthy Homes Pilot or the pilot), delivered 97 comprehensive energy retrofits to low-income households in two underserved communities: Lynn, Massachusetts (57) and the Beacon Hill neighborhood in Seattle, Washington (40). Designed by Emerald Cities Collaborative (ECC) and funded via a U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) Enhancement and Innovation (E&I) grant, ECC created the pilot to expand the reach and range of services typically available to participating WAP households.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Connecting the Texas Gulf Coast with COMPASS to Build Research Opportunities
This project aimed to connect students from TAMUCC, a university with few DOE grants, to the DOE COMPASS project and national laboratory research. Through this engagement, we worked to build a partnership with DOE to expand upon collaboration opportunities.
59 BASIC BIOLOGICAL SCIENCES↗
On the connection between least squares, regularization, and classical shadows
Classical shadows (CS) offer a resource-efficient means to estimate quantum observables, circumventing the need for exhaustive state tomography. Here, we clarify and explore the connection between CS techniques and least squares (LS) and regularized least squares (RLS) methods commonly used in machine learning and data analysis. By formal identification of LS and RLS ``shadows'' completely analogous to those in CS---namely, point estimators calculated from the empirical frequencies of single measurements---we show that both RLS and CS can be viewed as regularizers for the underdetermined regime, replacing the pseudoinverse with invertible alternatives. Through numerical simulations, we evaluate RLS and CS from three distinct angles: the tradeoff in bias and variance, mismatch between the expected and actual measurement distributions, and the interplay between the number of measurements and number of shots per measurement. Compared to CS, RLS attains lower variance at the expense of bias, is robust to distribution mismatch, and is more sensitive to the number of shots for a fixed number of state copies---differences that can be understood from the distinct approaches taken to regularization. Conceptually, our integration of LS, RLS, and CS under a unifying ``shadow'' umbrella aids in advancing the overall picture of CS techniques, while practically our results highlight the tradeoffs intrinsic to these measurement approaches, illuminating the circumstances under which either RLS or CS would be preferred, such as unverified randomness for the former or unbiased estimation for the latter.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Real-Time On-Ramp Merging Control of Connected and Automated Vehicles using Pseudospectral Convex Optimization
Highway on-ramp merging can be a challenging task for human drivers due to the complex vehicle negotiations and interactions in limited time and space. Connected and automated vehicles (CAVs) have great potential to address the problem and offer many benefits in terms of safety, traffic efficiency, and fuel economy. However, real-time optimal control of CAVs still faces many challenges, including nonlinear dynamics, complex inter-vehicle interactions, and a highly dynamic and uncertain traffic environment. To address these challenges, we develop a novel control approach that balances the solution optimality and computational efficiency to determine optimal merging speed profiles in real time. Specifically, by employing a pseudospectral method and a sequential convex programming approach, two algorithms are proposed and implemented within the model predictive control (MPC) framework to enable real-time generation of optimal solutions for potential on-vehicle applications. The convergence and optimality of the proposed algorithms are validated by comparing with a general-purpose solver under different traffic scenarios.
Shi, Yang↗
A novel islanding detection technique for grid connected photovoltaic system
Islanding detection is the major issue in Grid Connected Photovoltaic (PV) System and still it remains a challenge for researchers to interconnect the PV system with the Grid. The algorithms which are listed in the literature are failed to identify the Islanding phenomena for the several source configuration. In this paper a novel islanding detection technique is presented to reduce the non-detection zone (NDZ) at the point of common coupling (PCC) and it can be widely used for various renewable energy system configurations. The simulations have been carried out in Matlab/Simulink for several test conditions. The simulations results are presented to confirm the effectiveness of the proposed method.
14 SOLAR ENERGY↗
Grid connection management of distributed generators on the basis of renewable energy sources
The concept of distributed energy of renewable energy sources is becoming increasingly popular. It is not simply supplementary but a real alternative to the conventional power supply from centralized power grids. Distributed electricity generators integrated into the Unified Energy System are a complex system in which the relationship between the observed parameters and the system state is ambivalent and ambiguous. Therefore, the approach to management in automatic control systems based on control of the output parameters is inappropriate in nature. In this case, the elaboration of a control action should be carried out on the basis of data on the current state of the object of control. Issues of the grid connection of distributed generators and control of their process parameters are considered.
14 SOLAR ENERGY↗
A Novel Deep Reinforcement Learning Approach to Traffic Signal Control with Connected Vehicles
The advent of connected vehicle (CV) technology offers new possibilities for a revolution in future transportation systems. With the availability of real-time traffic data from CVs, it is possible to more effectively optimize traffic signals to reduce congestion, increase fuel efficiency, and enhance road safety. The success of CV-based signal control depends on an accurate and computationally efficient model that accounts for the stochastic and nonlinear nature of the traffic flow. Without the necessity of prior knowledge of the traffic system’s model architecture, reinforcement learning (RL) is a promising tool to acquire the control policy through observing the transition of the traffic states. In this paper, we propose a novel data-driven traffic signal control method that leverages the latest in deep learning and reinforcement learning techniques. By incorporating a compressed representation of the traffic states, the proposed method overcomes the limitations of the existing methods in defining the action space to include more practical and flexible signal phases. The simulation results demonstrate the convergence and robust performance of the proposed method against several existing benchmark methods in terms of average vehicle speeds, queue length, wait time, and traffic density.
42 ENGINEERING↗
Connecting Global Modes of Variability to Climate in High Mountain Asia
Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.
54 ENVIRONMENTAL SCIENCES↗
Anomaly Detection in Connected and Autonomous Vehicle Trajectories Using LSTM Autoencoder and Gaussian Mixture Model
Connected and Autonomous Vehicles (CAVs) technology has the potential to transform the transportation system. Although these new technologies have many advantages, the implementation raises significant concerns regarding safety, security, and privacy. Anomalies in sensor data caused by errors or cyberattacks can cause severe accidents. To address the issue, this study proposed an innovative anomaly detection algorithm, namely the LSTM Autoencoder with Gaussian Mixture Model (LAGMM). This model supports anomalous CAV trajectory detection in the real-time leveraging communication capabilities of CAV sensors. The LSTM Autoencoder is applied to generate low-rank representations and reconstruct errors for each input data point, while the Gaussian Mixture Model (GMM) is employed for its strength in density estimation. The proposed model was jointly optimized for the LSTM Autoencoder and GMM simultaneously. The study utilizes realistic CAV data from a platooning experiment conducted for Cooperative Automated Research Mobility Applications (CARMAs). The experiment findings indicate that the proposed LAGMM approach enhances detection accuracy by 3% and precision by 6.4% compared to the existing state-of-the-art methods, suggesting a significant improvement in the field.
33 ADVANCED PROPULSION SYSTEMS↗
Development and Evaluation of Velocity Predictive Optimal Energy Management Strategies in Intelligent and Connected Hybrid Electric Vehicles
In this study, a thorough and definitive evaluation of Predictive Optimal Energy Management Strategy (POEMS) applications in connected vehicles using 10 to 20 s predicted velocity is conducted for a Hybrid Electric Vehicle (HEV). The presented methodology includes synchronous datasets gathered in Fort Collins, Colorado using a test vehicle equipped with sensors to measure ego vehicle position and motion and that of surrounding objects as well as receive Infrastructure to Vehicle (I2V) information. These datasets are utilized to compare the effect of different signal categories on prediction fidelity for different prediction horizons within a POEMS framework. Multiple artificial intelligence (AI) and machine learning (ML) algorithms use the collected data to output future vehicle velocity prediction models. The effects of different combinations of signals and different models on prediction fidelity in various prediction windows are explored. All of these combinations are ultimately addressed where the rubber meets the road: fuel economy (FE) enabled from POEMS. FE optimization is performed using Model Predictive Control (MPC) with a Dynamic Programming (DP) optimizer. FE improvements from MPC control at various prediction time horizons are compared to that of full-cycle DP. All FE results are determined using high-fidelity simulations of an Autonomie 2010 Toyota Prius model. The full-cycle DP POEMS provides the theoretical upper limit on fuel economy (FE) improvement achievable with POEMS but is not currently practical for real-world implementation. Perfect prediction MPC (PP-MPC) represents the upper limit of FE improvement practically achievable with POEMS. Real-Prediction MPC (RP-MPC) can provide nearly equivalent FE improvement when used with high-fidelity predictions. Constant-Velocity MPC (CV-MPC) uses a constant speed prediction and serves as a “null” POEMS. Results showed that RP-MPC, enabled by high-fidelity ego future speed prediction, led to significant FE improvement over baseline nearly matching that of PP-MPC.
33 ADVANCED PROPULSION SYSTEMS↗
Neuroevolution Application to Collaborative and Heuristics-Based Connected and Autonomous Vehicle Cohort Simulation at Uncontrolled Intersection
Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go vehicle dynamics. Low deviation from the road speed limit is hence continuously sustained for cohorts of at most 50 m long. This limitation can be mitigated with additional lanes that the cohorts can split into. The concept also allows the testing and implementation of fast-turning lanes by simply replicating and reconnecting the control architecture at each new road crossing, enabling high scalability for complex road network analysis. The controller is also successfully validated within a high-fidelity vehicle dynamic environment, showing its potential for driverless vehicle control in addition to offering a new traffic control simulation model for future autonomous operation studies.
Jacquelin, Frederic (ORCID:0000000183154344)↗
ROTATION PERIODS FOR COOL STARS IN THE 4 Gyr OLD OPEN CLUSTER M67, THE SOLAR–STELLAR CONNECTION, AND THE APPLICABILITY OF GYROCHRONOLOGY TO AT LEAST SOLAR AGE
We report rotation periods for 20 cool (FGK) main sequence member stars of the 4 Gyr-old open cluster M67 (=NGC 2682), obtained by analyzing data from Campaign 5 of the K2 mission with the Kepler Space Telescope . The rotation periods delineate a sequence in the color–period diagram (CPD) of increasing period with redder color. This sequence represents a cross-section at the cluster age of the surface P = P ( t , M ), suggested in prior work to extend to at least solar age. The current Sun is located marginally (approximately 1 σ ) above M67 in the CPD, as its relative age leads us to expect, and lies on the P = P ( t , M ) surface to within measurement precision. We therefore conclude that the solar rotation rate is normal as compared with cluster stars, a fact that strengthens the solar–stellar connection. The agreement between the M67 rotation period measurements and prior predictions further implies that rotation periods, especially when coupled with appropriate supporting work such as spectroscopy, can provide reliable ages via gyrochronology for other similar FGK dwarfs from the early main sequence to solar age and likely until the main sequence turnoff. The M67 rotators have a rotational age of 4.2 Gyr with a standard deviation of 0.7 Gyr, implying that similar field stars can be age-dated to precisions of ∼17%. The rotational age of the M67 cluster as a whole is therefore 4.2 Gyr, but with a lower (averaged) uncertainty of 0.2 Gyr.
79 ASTRONOMY AND ASTROPHYSICS↗
Protostar l1455 IRS1: a rotating disk connecting to a filamentary network
We conducted IRAM-30 m C{sup 18}O (2–1) and SMA 1.3 mm continuum {sup 12}CO (2–1) and C{sup 18}O (2–1) observations toward the Class 0/I protostar L1455 IRS1 in Perseus. The IRAM-30 m C{sup 18}O results show IRS1 in a dense 0.05 pc core with a mass of 0.54 M {sub ⊙}, connecting to a filamentary structure. Inside the dense core, compact components of 350 au and 1500 au are detected in the SMA 1.3 mm continuum and C{sup 18}O, with a velocity gradient in the latter one perpendicular to a bipolar outflow in {sup 12}CO, likely tracing a rotational motion. We measure a rotational velocity profile ∝r{sup −0.75} that becomes shallower at a turning radius of ∼200 au, which is approximately the radius of the 1.3 mm continuum component. These results hint at the presence of a Keplerian disk with a radius <200 au around L1455 IRS1 with a protostellar mass of about 0.28 M {sub ⊙}. We derive a core rotation that is about one order of magnitude faster than expected. A significant velocity gradient along a filament toward IRS1 indicates that this filament is dynamically important, providing a gas reservoir and possibly responsible for the faster-than-average core rotation. Previous polarimetric observations show a magnetic field aligned with the outflow axis and perpendicular to the associated filament on a 0.1 pc scale, while on the inner 1000 au scale, the field becomes perpendicular to the outflow axis. This change in magnetic field orientations is consistent with our estimated increase in rotational energy from large to small scales that overcomes the magnetic field energy, wrapping the field lines and aligning them with the disk velocity gradient. These results are discussed in the context of the interplay between filament, magnetic field, and gas kinematics from large to small scales. Possible emerging trends are explored with a sample of 8 Class 0/I protostars.
79 ASTRONOMY AND ASTROPHYSICS↗
LYMAN-ALPHA SPECTRA FROM MULTIPHASE OUTFLOWS, AND THEIR CONNECTION TO SHELL MODELS
We perform Lyman- α (Ly α ) Monte-Carlo radiative transfer calculations on a suite of 2500 models of multiphase, outflowing media, which are characterized by 14 parameters. We focus on the Ly α spectra emerging from these media and investigate which properties are dominant in shaping the emerging Ly α profile. Multiphase models give rise to a wide variety of emerging spectra, including single-, double-, and triple-peaked spectra. We find that the dominant parameters in shaping the spectra include (i) the cloud covering factor, f {sub c} , which is in agreement with earlier studies, and (ii) the temperature and number density of residual H i in the hot ionized medium. We attempt to reproduce spectra emerging from multiphase models with “shell models” which are commonly used to fit observed Ly α spectra, and investigate the connection between shell-model parameters and the physical parameters of the clumpy media. In shell models, the neutral hydrogen content of the shell is one of the key parameters controlling Ly α radiative transfer. Because Ly α spectra emerging from multiphase media depend much less on the neutral hydrogen content of the clumps, the shell-model parameters such as H i column density (but also shell velocity and dust content) are generally not well matched to the associated physical parameters of the clumpy media.
79 ASTRONOMY AND ASTROPHYSICS↗
The accretion flow-discrete ejection connection in GRS 1915+105
The microquasar GRS 1915+105 is known for its spectacular discrete ejections. They occur unexpectedly, thus their inception has escaped direct observation. It has been shown that the X-ray flux increases in the hours leading up to a major ejection. In this article, we consider the serendipitous interferometric monitoring of a modest version of a discrete ejection described in Reid et al. that would have otherwise escaped detection in daily radio light curves. The observation begins ∼1 hr after the onset of the ejection, providing unprecedented accuracy on the estimate of the ejection time. The astrometric measurements allow us to determine the time of ejection as MJD 56436.274{sub −0.013}{sup +0.016}, i.e., within a precision of 41 minutes (95% confidence). Just like larger flares, we find that the X-ray luminosity increases in last 2–4 hr preceding ejection. Our finite temporal resolution indicates that this elevated X-ray flux persists within 21.8{sub −19.1}{sup +22.6} minutes of the ejection with 95% confidence, the highest temporal precision of the X-ray–superluminal ejection connection to date. This observation provides direct evidence that the physics that launches major flares occurs on smaller scales as well (lower radio flux and shorter ejection episodes). The observation of a X-ray spike prior to a discrete ejection, although of very modest amplitude, suggests that the process linking accretion behavior to ejection is general from the smallest scales to high luminosity major superluminal flares.
79 ASTRONOMY AND ASTROPHYSICS↗
The connection between reddening, gas covering fraction, and the escape of ionizing radiation at high redshift
Using a large sample of spectroscopically confirmed z∼3 galaxies, we establish an empirical relationship between reddening (E(B−V)), neutral gas covering fraction (f{sub cov}(H I)), and the escape of ionizing (Lyman continuum, LyC) photons. Our sample includes 933 galaxies at z∼3,121 of which have deep spectroscopic observations (≳7 hr) at 850≲λ{sub rest}≲1300 Å with the Low Resolution Imaging Spectrograph on Keck. The high covering fraction of outflowing optically thick H I indicated by the composite spectra of these galaxies implies that photoelectric absorption, rather than dust attenuation, dominates the depletion of LyC photons. By modeling the composite spectra as the combination of an unattenuated stellar spectrum including nebular continuum emission with one that is absorbed by H I and reddened by a line-of-sight extinction, we derive an empirical relationship between E(B−V) and f{sub cov}(H I). Galaxies with redder UV continua have larger covering fractions of H I characterized by higher line-of-sight extinctions. We develop a model which connects the ionizing escape fraction with E(B−V), and which may be used to estimate the ionizing escape fraction for an ensemble of galaxies. Alternatively, direct measurements of the escape fraction for our sample allow us to constrain the intrinsic LyC-to-UV flux density ratio to be 〈S(900 A-ring )/S(1500 A-ring )〉{sub int}≳0.20, a value that favors stellar population models that include weaker stellar winds, a flatter initial mass function, and/or binary evolution. Last, we demonstrate how the framework discussed here may be used to assess the pathways by which ionizing radiation escapes from high-redshift galaxies.
79 ASTRONOMY AND ASTROPHYSICS↗
The Lyα-LyC connection: evidence for an enhanced contribution of UV-faint galaxies to cosmic reionization
The escape of ionizing Lyman continuum (LyC) photons requires the existence of low-N {sub H i} sightlines, which also promote escape of Lyα. We use a suite of 2500 Lyα Monte-Carlo radiative transfer simulations through models of dusty, clumpy interstellar (“multiphase”) media from Gronke and Dijkstra, and compare the escape fractions of Lyα (f{sub esc}{sup Lyα}) and LyC radiation (f{sub esc}{sup ion}). We find that f{sub esc}{sup ion} and f{sub esc}{sup Lyα} are correlated: galaxies with a low f{sub esc}{sup Lyα} consistently have a low f{sub esc}{sup ion}, while galaxies with a high f{sub esc}{sup Lyα} exhibit a large dispersion in f{sub esc}{sup ion}. We argue that there is increasing observational evidence that Lyα escapes more easily from UV-faint galaxies. The correlation between f{sub esc}{sup ion} and f{sub esc}{sup Lyα} then implies that UV-faint galaxies contribute more to the ionizing background than implied by the faint-end slope of the UV luminosity function. In multiphase gases, the ionizing escape fraction is most strongly affected by the cloud covering factor, f {sub cl}, which implies that f{sub esc}{sup ion} is closely connected to the observed Lyα spectral line shape. Specifically, LyC-emitting galaxies typically having narrower, more symmetric line profiles. This prediction is qualitatively similar to that for “shell models.”.
79 ASTRONOMY AND ASTROPHYSICS↗