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At least 631 records · Page 35

Crowd Dynamics: Modeling and Control of Multiagent Systems

This review aims to present recent developments in modeling and control of multiagent systems. A particular focus is set on crowd dynamics characterized by complex interactions among agents, also called social interactions, and large-scale systems. Specifically, in a crowd each individual agent interacts with a field generated by the other agents and the environment. These systems can be modeled at the microscopic scale by ordinary differential equations, while an alternative description at the mesoscopic scale is given by a partial differential equation for the propagation of the probability density of the agents. Control actions can be applied at the individual level as well as at the level of the corresponding fields. This article presents and compares different control types, and the specific application to multilane, multiclass traffic is developed in some detail, showing the main tools at work in a hybrid setting with relevant impacts on autonomous driving.

33 ADVANCED PROPULSION SYSTEMS↗

Autonomous aerial flight path inspection using advanced manufacturing techniques

Robotic systems have shown capabilities to perform inspection tasks in dangerous and difficult-to-access environments, such as those found in different components of power plants. However, most of the current robotic inspection technology is designed for specific components. Aerial robots, commonly termed as Drones, have raised an option to inspect a wider range of structural components. Nevertheless, current aerial inspecting technology still relies on a human pilot with limited line of sight, field of view and a reduced perception as the drone flies away, which prevents performing close-quarter inspection in intricate, structurally complex and GPS-denied environments. This work introduces offline inspection path generation methods based on robotics-integrated to manufacturing techniques. One method uses computer-aided manufacturing (CAM) techniques and the other an additive manufacturing (AM) approach to generate the flight path. That is to say, the drone would fly along the path described by a 3D (Three Dimensional) printer’s extruder or a CNC (Computer Numerical Control) machining tool, enabling to fly very close the structure even in physical structures with a complex geometry. Once the trajectories are generated, they are introduced for its validation in the Gazebo robotics simulator. Simulation results demonstrate the proper performance of the method and confirm that this approach can be used for close inspection of structural components.

42 ENGINEERING↗

Desalination for a circular water economy

Today's water systems are enabled by ample fresh water sources, low-cost centralized treatment, and facile wastewater disposal. Climatic change, aging infrastructure, and source water contamination have exposed the vulnerabilities of this linear water paradigm. While seawater desalination enables coastal communities to augment their supply, more broadly securing water systems for municipal, industrial, and agricultural water users will require distributed desalination and fit-for-purpose reuse of nontraditional water sources. Our linear water economy must evolve into a resilient circular water economy, where water is continuously reused and “contaminants” become the feedstocks for other economically valuable processes. Additionally, technology innovation is needed to deliver autonomous, precise, resilient, intensified, modular, and electrified desalination systems that reduce the cost, improve the performance, and enhance the resilience of nontraditional water reuse systems. Meanwhile, strong federal leadership and coordination is needed to accelerate desalination research, promote information gathering efforts to direct technology development, and create an expanded role for non-profit organizations in knowledge dissemination.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Collection of low-grade waste heat for enhanced energy harvesting

Enhanced energy harvesting through the collection of low-grade waste heat is experimentally demonstrated. A structural optimization technique is exploited in the design of a thermal-composite substrate to guide and gather the heat emanating from multiple sources to a predetermined location. A thermoelectric generator is then applied at the selected focusing region to convert the resulting low-grade waste heat to electrical power. The thermal characteristics of the device are experimentally verified by direct temperature measurements of the system and numerically validated via heat conduction simulations. Electrical performance under natural and forced convection is measured, and in both cases, the device with optimized heat flow control plus energy harvesting demonstrates increased power generation when compared with a baseline waste heat recovery system. Electronics applications include energy scavenging for autonomously powered sensor networks or self-actuated devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

MO-FG-303-01: FEATURED PRESENTATION and BEST IN PHYSICS (THERAPY): Automating LINAC QA: Design and Testing of An Image Acquisition and Processing System Utilizing a Combination of Radioluminescent Phosphors, Embedded X-Ray Markers and Optical Measurements

Purpose: The recent development of phosphors to visualize radiation beams from linear accelerators (LINAC) offers a unique opportunity for evaluating radiation fields within the context of the treatment space. The purpose of this study was to establish an automated, self-calibrating prototype system for performing quality assurance (QA) measurements. Methods: A thin layer of Gd{sub 2}O{sub 2}S:Tb phosphor and fiducial markers were embedded on several planar faces of a custom-designed phantom. The phantom was arbitrarily placed near iso-center on the couch of a LINAC equipped with on-board megavoltage (MV) and kilovoltage (kV) imagers. A plan consisting of several beams and integrated image acquisitions was delivered. Images of the phantom were collected throughout the delivery. Salient features, such as fiducials, crosshairs and beam edges were then extracted from these images used to calibrate the system, adjust for variations in phantom placement, and perform measurements. Beam edges were visualized by imaging the light generated by the phosphor on the phantom enabling direct comparison with the light field and laser locations. Registration of MV, kV and optical image data was performed using the embedded fiducial markers, enabling comparison of imaging center locations. Measurements specified by TG-142 were calculated and compared with those obtained from a commercially available QA system. Results: The system was able to automatically extract the location of the fiducials, lasers, light field and radiation field from the acquired images regardless of phantom positioning. It was also able to automatically identify the locations of fiducial markers on kV and MV images. All collected measurements were within TG-142 guidelines. The difference between the prototype and commercially available system were less than 0.2 mm. Conclusion: The prototype system demonstrated the capability of accurately and autonomously evaluating various TG-142 parameters independent of operator input and phantom setup.

60 APPLIED LIFE SCIENCES↗

CROCUS Sodar Measurements of Lower Atmospheric Wind Profiles at Argonne Testbed for Multiscale Observational Science (ATMOS) Site

The Scintec MFAS Sodar (Multiple-Frequency Acoustic Sounder) is an autonomous, ground-based acoustic remote sensing system designed to measure vertical profiles of horizontal wind speed, wind direction, and vertical velocity in the lower atmosphere. The instrument transmits sequences of acoustic pulses and detects the Doppler-shifted sound waves backscattered by small-scale temperature and velocity fluctuations caused by atmospheric turbulence. From these Doppler shifts, the system derives three-dimensional wind vectors by combining radial velocities from multiple beam orientations.The MFAS Sodar operates with a first usable range gate beginning at approximately 30 m above ground level and a configurable vertical resolution of 10 m. Under favorable acoustic conditions, the system provides wind profiles extending up to 600 m above ground level. Measurements are processed into 15-minute averaged profiles containing wind speed, direction, vertical velocity, and diagnostic quantities such as signal-to-noise ratio and echo strength.This dataset was collected at the Argonne Testbed for Multiscale Observational Science (ATMOS) facility in Lemont, Illinois, as part of DOE's CROCUS Urban Integrated Field Laboratory (UIFL) initiative. The purpose of these observations is to characterize the vertical wind structure and boundary-layer evolution across the urban–suburban gradient of the greater Chicago region. In particular, these data are intended to improve understanding of how local meteorology, such as lake-breeze penetration, nocturnal jets, and daytime mixing, varies between the densely built urban core and the suburban periphery. The MFAS observations provide critical context for evaluating high-resolution model simulations and for integrating with complementary lidar, radar, and in-situ meteorological measurements within the broader CROCUS UIFL network.All data are archived in NetCDF (Network Common Data Form) format and include wind and diagnostic parameters. The files can be accessed and analyzed using standard software that supports NetCDF, such as Python (e.g., xarray, netCDF4), MATLAB, R (e.g., ncdf4, raster), or Panoply (NASA’s NetCDF visualization application).

54 ENVIRONMENTAL SCIENCES↗

Raman Lidar MERGE Value-Added Product

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Raman lidars (RLs) are semi-autonomous, land-based, laser remote sensing systems that provide height- and time-resolved measurements of water vapor mixing ratio, temperature, aerosol backscatter, extinction, and linear depolarization ratio from about 200 m to greater than 10 km AGL. These systems transmit at a wavelength of 355 nm with 300 mJ, ~5 ns pulses, and a pulse repetition frequency of 30 Hz. The receiver incorporates nine detection channels, including two water vapor channels at 408 nm, two nitrogen channels at 387 nm, three elastic channels, and two rotational Raman channels for temperature profiling at 354 and 353 nm. Figure 1 illustrates the layout of the ARM RL receiver system. Backscattered light from the atmosphere enters the telescope and is directed into the receiver system (i.e., aft optics). This signal is then split between a narrow-field-of-view radiometer (NFOV) path (blue) and a wide-field-of-view zenith radiometer (WFOV) path (red). The WFOV (2 mrad) path contains three channels (water vapor, nitrogen, and unpolarized elastic), and the NFOV (0.3 mrad) path contains six channels (water vapor, nitrogen, parallel and perpendicular elastic, and two rotational Raman). All nine detection channels use Electron Tubes 9954B photomultiplier tubes (PMTs). The signals from each of the nine PMTs are acquired using transient data recorders from Licel GbR (Berlin, Germany). The Licel data recorders provide simultaneous measurements of both analog photomultiplier current and photon counts at height resolution of 7.5 m and a time resolution of 10 s. The analog signal provides good linearity in the strong signal regime, but poor sensitivity at low signal levels. Conversely, the photo counting signal provides good sensitivity in the weak signal regime, but is strongly nonlinear at higher signal levels. The advantage in recording both signals is that they can be combined (or merged) into a single signal with improved dynamic range. The process of combining the analog and photon counting data has become known as “gluing” (Whiteman et al., 2006).

47 OTHER INSTRUMENTATION↗

Detecting and Characterizing Mg ii Absorption in DESI Survey Validation Quasar Spectra

Abstract We present findings of the detection of Magnesium II (Mg ii , λ = 2796, 2803 Å) absorbers from the early data release of the Dark Energy Spectroscopic Instrument (DESI). DESI is projected to obtain spectroscopy of approximately 3 million quasars (QSOs), of which over 99% are anticipated to be at redshifts greater than z > 0.3, such that DESI would be able to observe an associated or intervening Mg ii absorber illuminated by the background QSO. We have developed an autonomous supplementary spectral pipeline that detects these systems through an initial line-fitting process and then confirms the line properties using a Markov Chain Monte Carlo sampler. Based upon a visual inspection of the resulting systems, we estimate that this sample has a purity greater than 99%. We have also investigated the completeness of our sample in regard to both the signal-to-noise properties of the input spectra and the rest-frame equivalent width ( W 0 ) of the absorber systems. From a parent catalog containing 83,207 quasars, we detect a total of 23,921 Mg ii absorption systems following a series of quality cuts. Extrapolating from this occurrence rate of 28.8% implies a catalog at the completion of the five-year DESI survey that will contain over eight hundred thousand Mg ii absorbers. The cataloging of these systems will enable significant further research because they carry information regarding circumgalactic medium environments, the distribution of intervening galaxies, and the growth of metallicity across the redshift range 0.3 ≤ z < 2.5.

79 ASTRONOMY AND ASTROPHYSICS↗

Engineered setpoints for autonomous distributed sensors and actuators

Loads on an electric power system are configured with under-frequency relays in which the frequency setpoints and delay times for reclosure are uniformly distributed. If demand exceeds supply in the system, frequency will decrease. The decrease in frequency will actuate relays and reduce load to the point where demand will meet the available supply. After its engineered delay time, each relay will attempt to close contact and reestablish the load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Autonomous Utility Pole Identification

The implementation of small unmanned aerial systems (sUAS) for the purpose of powerline inspection is an emerging concept among utility companies. Such operations can produce a significant amount of useful data for the purpose of training different machine learning models or keep track of the integrity of electrical infrastructure. As such, this system is developed for the purpose of properly cataloging and leveraging this collected data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Harnessing deep reinforcement learning to construct time-dependent optimal fields for quantum control dynamics

Here, we present an efficient deep reinforcement learning (DRL) approach to automatically construct time-dependent optimal control fields that enable desired transitions in dynamical chemical systems. Our DRL approach gives impressive performance in constructing optimal control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide a detailed description of the algorithms and hyperparameters as well as performance metrics for our DRL-based approach. Our results demonstrate that DRL can be employed as an effective artificial intelligence approach to efficiently and autonomously design control fields in quantum dynamical chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Line Impedance Conditioner for Saturation Mitigation of Zigzag Transformer in Hybrid AC/DC Transmission System Considering Line Unbalances

Hybrid ac/dc transmission extends the power transfer capacity of existing long ac lines closer to their thermal limit, by superposing the dc current onto three-phase ac lines through a zigzag transformer. However, this transformer could suffer saturation under unbalanced line impedance conditions. This paper introduces the concept of hybrid line impedance conditioner (HLIC) as a cost-effective approach to compensate for the line unbalance and therefore avoid saturation. The topology and operation principle are presented. The two-level control strategy is described, which enables autonomous adaptive regulation without the need of system-level control. Design and implementation are also analyzed, including dc-link capacitance as one of the key line conditioner components, HLIC installation, and protection under fault conditions. The cost study on this HLIC-based hybrid system is also performed to reveal the benefits of the solution. In conclusion, simulation results and experimental results based on a down-scaled prototype are provided to verify the feasibility of the proposed approach.

30 DIRECT ENERGY CONVERSION↗

NREL, Industry Collaboration to Usher in New Wave of Autonomous Vehicle Research

In an important step toward advancing intelligent, efficient, and autonomous electric vehicles, the National Renewable Energy Laboratory (NREL) plans to partner on research and development efforts with EasyMile, a smart mobility solutions company. EasyMile provided a demo of its driverless EZ10 shuttle on the NREL campus in September 2017.

33 ADVANCED PROPULSION SYSTEMS↗

Evaluating the Impacts of Autonomous Electric Vehicles Adoption on Vehicle Miles Traveled and CO2 Emissions

Autonomous electric vehicles (AEVs) can potentially revolutionize the transportation landscape, offering a safer, contact-free, easily accessible, and more eco-friendly mode of travel. Prior to the market uptake of AEVs, it is critical to understand the consumer segments that are most likely to adopt these vehicles. Beyond market adoption, it is also important to quantify the impact of AEVs on broader transportation systems and the environment, such as impacts on the annual vehicle miles traveled (VMT) and greenhouse gas (GHG) emissions. In this pilot study, using survey data, a statistical model correlating AEV adoption intention and socioeconomic and built environment attributes was estimated, and a sensitivity analysis was conducted to understand the importance of factors impacting AEV adoption. We found that the market segments range from early adopters who are wealthy, technologically savvy, and relatively young to non-adopters who are more cautious to new technologies. This is followed by a synthetic population microsimulation of market penetration for the San Francisco Bay Area. With five household vehicle replacement scenarios, we assessed the annual VMT and tailpipe carbon dioxide (CO2) emissions change associated with vehicle replacement. It is found that adopting AEVs can potentially reduce more than 5 megatons of CO2 yearly, which is approximately 30% of the total CO2 emitted by internal combustion engine (ICE) cars in the region.

33 ADVANCED PROPULSION SYSTEMS↗

Event-Driven Predictive Approach for Real-Time Volt/VAR control with CVR in solar PV rich Active Distribution Network

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. In addition, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems.

14 SOLAR ENERGY↗

High-dimensional multi-fidelity Bayesian optimization for quantum control

Abstract We present the first multi-fidelity Bayesian optimization (BO) approach for solving inverse problems in the quantum control of prototypical quantum systems. Our approach automatically constructs time-dependent control fields that enable transitions between initial and desired final quantum states. Most importantly, our BO approach gives impressive performance in constructing time-dependent control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide detailed descriptions of our machine learning methods as well as performance metrics for a variety of machine learning algorithms. Taken together, our results demonstrate that BO is a promising approach to efficiently and autonomously design control fields in general quantum dynamical systems.

Computer Science↗

Multichannel Processing of Vibrational Response Measurements: An Application of Constrained Subspace Identification

Dynamic structural systems occur in a wide variety of applications such as autonomous ve-hicles employed militarily for battlefield management or non-military tasks like tracking awildfire in the hills of a drought-ridden area. Many such systems operating in the air or atsea employ a variety of subsystems ranging from airfoils for flight or machinery for propulsionor reactor components as simple as pipes carrying cooling for control.

42 ENGINEERING↗