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At least 343 records · Page 19

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DOE OSTI2020

Impact of Lateral Alignment on the Energy Savings of a Truck Platoon

A truck platooning system was tested using two heavy-duty tractor-trailer trucks on a closed test track to investigate the sensitivity of intentional lateral offsets over a range of intervehicle spacings. The fuel consumption for both trucks in the platoon was measured using the SAE J1321 gravimetric procedure while travelling at 65 mph and loaded to a gross weight of 65,000 lb. In addition, the SAE J1939 instantaneous fuel rate was calibrated against the gravimetric measurements and used as proxy for additional analyses. The testing campaign demonstrated the effects of intervehicle gaps, following-vehicle longitudinal control, and manual lateral control. The new results are compared to previous truck-platooning studies to reinforce the value of the new information and demonstrate similarity to past trends. Fuel savings for the following vehicle was observed to exceed 10% at closer following distances. The results showed that energy savings generally increased in a non-linear fashion as the gap was reduced. The impact of different following-truck lateral offsets had a measurable impact, with up to 4% reduction in total fuel-savings (relative to an isolated vehicle condition) observed for offsets up to 1.3 m. The fuel-consumption savings on the straight segments of the track exceeded those on the curved segments by upwards of 6% and highlight some potential differences expected between close-track testing and on-highway use.

adaptive cruise control↗

DOE OSTI2020

Impact of Lateral Alignment on the Energy Savings of a Truck Platoon: Preprint

adaptive cruise control↗

DOE OSTI2026

Efficient bidirectional quantum frequency conversion between telecom and visible bands using adaptively phase-matched III-V nanophotonic waveguides

Quantum frequency conversion (QFC) is essential for interfacing quantum systems operating at different wavelengths and for realizing scalable quantum networks. Despite extensive progress, achieving QFC with simultaneous high efficiency, low pump power, minimal noise, broad bandwidth, and pump-wavelength flexibility remains challenging. Here, we demonstrate efficient, low-noise, and bidirectional QFC between the telecom (1550-nm) and visible (780-nm) bands using unpoled indium gallium phosphide (InGaP) χ (2) nanophotonic waveguides, eliminating the need for a long-wavelength pump. Leveraging the large nonlinear susceptibility of InGaP together with adaptive phase-matching control, we obtain 27% (55%) internal efficiency in a 6-mm (2.5-mm)-long waveguide with a low pump power of 20 mW (50 mW) and a noise flux spectral density of 10 −4 counts per second per hertz at signal–pump detuning of 20 nm. These results mark a significant advance in integrated nonlinear photonics for high-performance QFC, facilitating the development of versatile and scalable quantum networks.

Hu, Jierui [Univ. of Illinois at Urbana-Champaign,↗

DOE OSTI2021

Ferromagnetic liquid droplets with adjustable magnetic properties

Significance Structured functional liquids combine mechanical versatility of fluids with solid-state properties, such as ferromagnetism, and offer a route to synthesize and control magnetic liquids for adaptive liquid robotics. Studies on these intriguing materials are only in their nascent state, and a profound understanding of the physical state is still lacking. We use hydrodynamics experiments to probe how the magnetization of ferromagnetic liquid droplets, governed by the assembly and jamming of magnetic nanoparticles at liquid–liquid interfaces, and their response to external stimuli can be tuned by chemical, structural, and magnetic means. Our results highlight the leading role of structural short-range order on magnetic properties, which provide a path toward nano-patterning structured liquids.

36 MATERIALS SCIENCE↗

DOE OSTI2024

FLARE: field line analysis and reconstruction for 3D boundary plasma modeling

The FLARE code is a magnetic mesh generator that is integrated within a suite of tools for the analysis of the magnetic geometry in toroidal fusion devices. A magnetic mesh is constructed from field line segments and permits fast reconstruction of field lines in 3D boundary plasma codes such as EMC3-EIRENE. Both intrinsically non-axisymmetric configurations (stellarators) and those with symmetry breaking perturbations of an axisymmetric equilibrium (tokamaks) are supported. The code itself is written in Modern Fortran with MPI support for parallel computing, and it incorporates object-oriented programming for the definition of the magnetic field and the material surface geometry. Extended derived types for a number of different magnetohydrodynamic equilibrium and plasma response models are implemented. The core element of FLARE is a field line tracer with adaptive step-size control, and this is integrated into tools for the construction of Poincaré maps and invariant manifolds of X-points. A collection of high-level procedures that generate output files for visualization is build on top of that. The analysis modules are build with Python frontends that facilitate customization of tasks and/or scripting of parameter scans.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Rotated-Droop Control for Enhanced Stability and Power Decoupling in Microgrids With Complex Line Impedances

Classical droop control in microgrids predominantly assumes inductive line impedance, which simplifies implementation but causes power coupling and steady-state errors in systems with resistive and inductive lines. This paper proposes a rotated-droop control strategy for grid-forming inverters that reformulates the power equations by incorporating the magnitude and angle of the line impedance within a rotated reference frame. This method enhances the decoupling of active and reactive power dynamics without increasing complexity or requiring communication links. A small-signal state-space model was created to capture the dynamic behavior of the system under varying impedance parameters, preserving the original droop gains by rotating the power control structure. This allows eigenvalue-based stability analysis and enhances damping and transient performance. Simulation and experimental results validated the improved power-sharing performance, faster response, and robustness of the proposed method under different impedance conditions. This approach maintains the decentralized structure of the conventional droop control while enabling greater adaptability and scalability, making it suitable for modern inverter-based microgrids with dynamic topologies.

Campo-Ossa, Daniel Dario [Univ. of Puerto Rico, Ag↗

DOE OSTI2021

Label-free DNA biosensing by topological light confinement

Large-area and transparent all-dielectric metasurfaces sustaining photonic bound states in the continuum (BICs) provide a set of fundamental advantages for ultrasensitive biosensing. BICs bridge the gap of large effective mode volume with large experimental quality factor. Relying on the transduction mechanism of reactive sensing principle, herein, we first numerically study the potential of subwavelength confinement driven by topological decoupling from free space radiation for BIC-based biosensing. Then, we experimentally combine this capability with minimal and low-cost optical setup, applying the devised quasi-BIC resonator for PNA/DNA selective biosensing with real-time monitoring of the binding event. A sensitivity of 20 molecules per micron squared is achieved, i.e. ≃0.01 pg. Further enhancement can easily be envisaged, pointing out the possibility of single-molecule regime. This work aims at a precise and ultrasensitive approach for developing low-cost point-of-care tools suitable for routine disease prescreening analyses in laboratory, also adaptable to industrial production control.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data

As part of the sensor characterization task of the SMART 2.0 project, this dataset includes raw data from three spinning lidars ([Ouster OS2-128](https://ouster.com/products/scanning-lidar/os2-sensor/), [Velodyne Puck (VLP-16)](https://velodynelidar.com/products/puck/), and [Velodyne Ultra Puck (VLP-32)](https://velodynelidar.com/products/ultra-puck/)), one camera ([Mako G-319](https://www.alliedvision.com/en/camera-selector/detail/mako/g-319/)), and one present weather sensor ([Vaisala FD-70](https://www.vaisala.com/en/products/weather-environmental-sensors/forward-scatter-fd70)). All data were synchronized, with the log start time indicated in the file name (HHMMSS). The data can be filtered by date, log time (HHMMSS), sensor, frame ID, and weather classification. These data were gathered statically at the Argonne Testbed for Multiscale Observational Science (ATMOS). Two target stop signs were placed in view of the sensors to contribute a target for comparing sensor data under different conditions. The weather data for each day are stored in netCDF “.nc” files. The lidar data contain the X, Y, Z, intensity, reflectivity, and ring from Ouster OS2-128 rev6, Velodyne VLP-16, and Velodyne VLP-32 lidars. ![raw lidar image](LiDAR_pointcloud_ATMOS.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Improving Signal-to-Noise Ratio (SNR) for Quantum Readout Signals Using Adaptive Hardware Filters on FPGA

This research presents an innovative approach to improving the Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals, utilizing FPGA-based adaptive filtering on the control board. Our solution aims to bolster quantum computations' reliability by providing a more accurate and precise way to obtain our readout traces and achieve a higher discernability between excitation states in real-time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Center for Tokamak Transient Simulations (RPI Unstructured Mesh Developments for FES SciDAC4 Partnerships) (Final Report)

The goal of this project was the development of unstructured mesh technologies for fusion simulation codes” for FES SciDAC partnerships and to integrate those technologies into the simulation workflows of those partnerships. Specific developments were executed in support of the following FES SciDAC4 partnerships: Partnership Center for High‐fidelity Boundary Plasma Simulation (HBPS), Center for Integrated Simulation of Fusion Relevant RF (RF‐SciDAC), Center for Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces (PSI2), and Center for Tokamak Transient Simulations (CTTS). The key unstructured mesh development areas addressed in this project include (i) methods to most effectively perform PIC calculations on unstructured meshes; (ii) creating meshes for fusion systems accounting for any desired level of geometric complexity and providing physics aware mesh configurations, (iii) adapting unstructured meshes to control the discretization errors, (iv) executing unstructured mesh calculations on GPU accelerated systems, (v) supporting physics/application‐specific PIC operations including surface/wall interactions of particles, (vi) providing infrastructure tools to support the interactions of solvers with unstructured meshes, and (vii) providing advanced methods for coupling plasma physics codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

High Performance Adaptive Deep-Reinforcement-Learning-based Real-time Emergency Control (HADREC) to Enhance Power Grid Resilience in Stochastic Environment (Final Report)

The HADREC technology developed in this project features real-time, validated, and predictive emergency control capabilities needed to effectively safeguard the grid against costly disturbances from extreme weather and other disruptive events. It has the potential to revolutionize the emergency control by providing faster and more effective solution for power grid emergency control. The technology can reduce the grid emergency control action time from minutes to seconds and mitigate the impact of outages and reduce system recovery time. The evaluation results using the models and data from PacifiCorp system have shown ~20% improvement in responding time and 70% improved in tripped generator output, comparing against today’s industrial application. This performance can help reduce preventive measurements and improve network utilization and market efficiency, and help lead to a more reliable and resilient power grid with renewable integration. The project has generated significant interest from industry, academic and commercial companies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Enhancing Camera Calibration for Traffic Surveillance with an Integrated Approach of Genetic Algorithm and Particle Swarm Optimization

Recent advancements in sensor technologies, coupled with signal processing and machine learning, have enabled real-time traffic control systems to effectively adapt to changing traffic conditions. Cameras, as sensors, offer a cost-effective means to determine the number, location, type, and speed of vehicles, aiding decision-making at traffic intersections. However, the effective use of cameras for traffic surveillance requires proper calibration. This paper proposes a new optimization-based method for camera calibration. In this approach, initial calibration parameters are established using the Direct Linear Transformation (DLT) method. Then, optimization algorithms are applied to further refine the calibration parameters for the correction of nonlinear lens distortions. A significant enhancement in the optimization process is achieved through the integration of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) into a combined Integrated GA and PSO (IGAPSO) technique. The effectiveness of this method is demonstrated through the calibration of eleven roadside cameras at three different intersections. The experimental results show that when compared to the baseline DLT method, the vehicle localization error is reduced by 22.30% with GA, 22.31% with PSO, and 25.51% with IGAPSO.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Impact to Cooling Airflow from Truck Platooning

We investigate tradeoffs between the airflow strategies related to engine cooling and the aerodynamic-enabled fuel savings created by platooning. By analyzing air temperatures, engine temperatures and cooling air flow at different platoon distances, we show the thermal impact to the engine from truck platooning. Previously, we collected wind and thermal data for numerous heavy-duty truck platoon configurations (gaps ranging from 4 to 87 meters) and reported the significant fuel savings enabled by these configurations. The fuel consumption for all trucks in the platoon were measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate while travelling at 65 mph and loaded to a gross weight of 65,000 lb. Using thermocouples mounted 1 m ahead of each truck, anemometers at the grill and a grid of under-hood thermocouples as well as J1939 reported engine temperatures, we analyze the impact to critical operating temperatures from different platoon configurations. Results show significant changes in the engine and under-hood air temperatures that correlate with vehicle gap distance and platoon position.

adaptive cruise control (ACC)↗

DOE OSTI2021

Analysis of the Unsteady Wakes of Heavy Trucks in Platoon Formation and Their Potential Influence on Energy Savings

The authors present transient wind velocity measurements from two successive, well-documented truck platooning track-test campaigns to assess the wake-shedding behavior experienced by trucks in various platoon formations. Utilizing advanced analytics of data from fast-response (100-200-Hz) multi-hole pressure probes, this analysis examines aerodynamic flow features and their relationship to energy savings during close-following platoon formations. Applying Spectral analysis to the wind velocity signals, we identify the frequency content and vortex-shedding behavior from a forward truck trailer, which dominates the flow field encountered by the downstream trucks. The changes in dominant wake-shedding frequencies correlate with changes to the lead and follower truck fuel savings at short separation distances. All followers experience a reduction in wake-shedding frequency at following distances less than 20 m—the same zone where lead trucks experience fuel savings/drag reductions and where followers experience a reduction in platooning benefits. The dominant vortex-shedding frequency decreased by upwards of 35% in this region. Additionally, the third truck in a platoon is shown to experience a lower wake-shedding frequency than the second vehicle in either a two- or three-truck platoon. The correlation of changes in the vortex-shedding frequency to trends in drag reduction, and the associated energy savings, suggest that these phenomena may be related and may provide an opportunity for improving the efficiency potential of truck platooning.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Impact to Cooling Airflow from Truck Platooning: Preprint

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

A Novel Multi-Agent Deep Reinforcement Learning-enabled Distributed Power Allocation Scheme for mmWave Cellular Networks

We consider the power allocation problem over shared spectrum for millimeter-Wave (mmWave) cellular downlink. Existing approaches usually find sub-optimal solutions by solving a non-convex optimization which leads to scalability issues due to centralized control. Therefore, distributed and adaptive approaches are desirable. Recently, model-free Deep Reinforcement Learning (DRL) has achieved success in such wireless resource management tasks. By modeling the radio environment as a Markov Decision Process (MDP) with the base stations (BSs) being the agents, power allocation can be automated at the agent level with comparable throughput performance to conventional centralized schemes. The multi-agent setting presents new challenges as the radio environment is impacted by the joint actions of the agents and is no longer stationary from any individual agent’s perspective. Existing literature bypasses this non-stationarity violation by ignoring it which may cause performance degradation. To tackle this issue, we propose a distributed continuous power allocation scheme based on a modified version of multi-agent Deep Deterministic Policy Gradient (MADDPG) that is tailored for the distributed multiple-agent setting. The proposed scheme employs a centralized-training distributed-execution framework where Q-functions are trained over subsets of BSs while each BS determines its transmit power based only on its own local observation. It admits constant per-BS communication and computation complexity and is thus scalable to large networks. Numerical evaluation shows that the proposed scheme adapts well to a wide range of interference conditions and can achieve comparable or better performance than several state-of-the-art non-learning approaches.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge jumps), causing correlated errors that challenge fault-tolerant quantum computing while simultaneously providing a detection signature for quantum sensing applications. Current detection methods operate offline, introducing latency incompatible with in-the-loop qubit control. In this paper, an online detector of charge jumps for superconducting qubits, based on a dilated causal convolutional neural network (DCCNN) designed for in-the-loop deployment on the Quantum Instrumentation Control Kit (QICK) platform, is presented. The network is trained on synthetic Ramsey tomography scans generated from qubit templates measured at the Northwestern Experimental Underground Site (NEXUS) at Fermilab, and translated to FPGA firmware via hls4ml with ap_fixed$\langle 16,6 \rangle$ quantization, reaching a per-inference latency of $6.19 μ$s on the Zynq UltraScale+ RFSoC ZCU216. At this operating point the DCCNN matches the detection efficiency of the established offline $χ^2$ algorithm ($0.843 \pm 0.022$ vs. $0.866 \pm 0.020$ on $|Δq| \in [0.1, 0.5] e$ at matched false-positive rate), while requiring no per-qubit hyperparameter tuning. This shifts charge-jump detection from a post-hoc diagnostic to a control-loop primitive, enabling adaptive protocols that respond to radiation-induced events in situ, with applications to quantum-computing error mitigation and to the use of superconducting qubits as particle detectors.

Gaytan-Villarreal, Daniel [Carnegie Mellon U.]↗

DOE OSTI2024

Wideband Impedance Passivation of MMCs for Suppressing Harmonic Oscillations

Harmonic instability and associated oscillation events have become one of the main concerns in MMC-based HVdc systems. These oscillations can appear in the range from a few hundred hertz to several kilohertz, and the root cause is identified as delay-induced negative damping of MMC impedance appearing at the system resonance frequency. Here, this paper introduces a wideband impedance reshaping method through MMC control to eliminate such negative damping for both grid-following (GFL) and grid-forming (GFM) MMCs, which makes the MMC impedance completely passive from the second harmonic frequency upward, thus preventing all harmonic oscillations. First, simplified impedance models of MMCs are derived for the harmonic stability analysis and the impedance reshaping control design. Next, a passivity-based impedance reshaping method is presented, as well as practical considerations for its implementation. In addition, to maintain the MMC's disturbance ride-through capability, an adaptive activation scheme is developed, which enables the wideband impedance reshaping control only in the presence of harmonic oscillation events. The effectiveness of the proposed method is validated by frequency domain analysis and by electromagnetic transient (EMT) simulations of two typical MMC-based power systems.

17 WIND ENERGY↗