Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Drives”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimization of the N ∥ Upshift in the DIII-D high field side lower hybrid current drive experiment

High field side lower hybrid current drive (LHCD) is one potential candidate for efficient non-inductive current drive in tokamak power plants, and the first test of this technology will occur on the DIII-D tokamak during the 2024 campaign. Previous LFS launch experiments operated in the multi-pass regime and relied on scrape-off layer interactions to close the spectral gap. In the DIII-D experiment, single-pass damping is achievable via an upshift in the parallel refractive index N ∥ caused by mode converting twice (slow → fast → slow). This mode conversion affects the ray trajectories and can lead to enhanced N ∥ upshift depending on where mode conversion occurs. Compared to multi-pass absorption experiments, the optimization of launched N ∥ and plasma parameters can be counter-intuitive: increased density may increase efficiency and smaller N ∥,launch tend to damp closer to the separatrix. A hard x-ray camera installed to measure the bremsstrahlung (50–250 keV) radiation from LHCD-generated fast electrons is capable of verifying the trends reporting in this paper through comparison to the ray-tracing/Fokker–Planck codes GENRAY/CQL3D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Optimization of simulated high-field side lower hybrid current drive coupling using machine learning predictions of scrape-off layer density

Lower hybrid current drive (LHCD) is a potential source of non-inductive off-axis current drive (CD) for tokamaks. Although LHCD has been successfully deployed on a number of tokamaks, it is highly sensitive to the scrape-off layer (SOL) conditions local to the LHCD launcher. Large gaps between the launcher and plasma core, SOL turbulence, or edge density perturbations due to edge-localized modes can hamper CD or cause large reflected power. These coupling issues in part motivated the installation of an LHCD launcher on the high-field side (HFS) of DIII-D. On the HFS, the SOL is less turbulent and more controllable compared to the low-field side. This quiescence may result in more predictable edge conditions and thus a more predictable CD. Here, in this work, HFS SOL reflectometry measurements are predicted from global plasma parameters using machine learning models. The SOL predictions coupled with the full-wave simulation of the LHCD launcher allow for the prediction of reflected power, directivity, and arcing risk before the discharge. Launcher performance is then optimized using multi-objective Bayesian optimization, finding the shot parameters that result in an optimal SOL density that maximizes CD while minimizing the risk of arcing. The predictions and optimizations of LHCD performance are then accelerated using a surrogate model of the full-wave LHCD simulation.

Bayesian optimization↗
DOE OSTI2025

Physics of laser direct-drive liquid deuterium–tritium wetted foam capsules for inertial confinement fusion

Laser direct-drive liquid deuterium–tritium (DT) wetted foam capsules hold substantial promise for future advancements in inertial confinement fusion (ICF). For this new class of ICF capsules, additive manufacturing (AM) techniques are used to create low aspect ratio spherical shells of a low-density, foam-like CH lattice, which is wetted with cryogenic liquid DT. In the present paper, we discuss key physics issues intrinsic to ignition and burn propagation in laser direct drive wetted foam capsules. These include requirements on laser energy and power, implosion velocity, fuel adiabat, and initial density and dimensions of the CH lattice shell.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Hot-electron preheat and mitigation in polar-direct-drive experiments at the National Ignition Facility

Target preheat by superthermal electrons from laser–plasma instabilities is a major obstacle to achieving thermonuclear ignition via direct-drive inertial confinement fusion at the National Ignition Facility (NIF). Polar-direct-drive surrogate plastic implosion experiments were performed on the NIF to quantify preheat levels at ignition-relevant scale and develop mitigation strategies. Here, the experiments were used to infer the hot-electron temperature, energy fraction, divergence, and to directly measure the spatial hot-electron energy deposition profile inside the imploding shell. Silicon layers buried in the ablator are shown to mitigate the growth of laser–plasma instabilities and reduce preheat, providing a promising path forward for ignition designs at an on-target intensity of about 10 15 W/cm 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Sensitivity of the dynamic-shell target to laser drive nonuniformities

The dynamic-shell concept for inertial confinement fusion (ICF) uses an initially homogeneous target and a carefully shaped laser pulse to form a shell and implode it. The laser pulse consists of a series of pickets that drive shocks into the target. The first few shocks converge inwards and rebound from the center of the target, creating an expanding, low-density plasma. Subsequent shocks are launched into the expanding plasma and eventually coalesce to form a shell, which is then imploded with a traditional ICF laser pulse. This study describes radiation-hydrodynamic simulations that investigate the sensitivity of dynamic-shell targets to imperfections in the laser drive. A one-dimensional (1D) study looks at mistiming and power variations in the pickets and a two-dimensional (2D) study examines irradiation perturbations imposed by the laser-beam geometry. Simulations show that less than ~2% power imbalance or 200 ps timing variation in the pickets is sufficient to keep the yield above 90% of the maximum. Additionally, the 2D simulations show that 72 or more beams are required to keep irradiation nonuniformities low enough to obtain fusion yields close to that of 1D simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Optimization Methodology of Polar Direct-Drive Illumination for the National Ignition Facility

Improved laser illumination uniformity drives shocks and implosions to create more extreme high energy density environments. Predominantly, the geometry of experiments that can be performed is dictated by the layout of beams at laser facilities, limiting inter-facility and multiscale investigations. This Letter presents the first automated, algorithmic approach for generating illumination configurations for high energy density experiments. The method is demonstrated in comparison to a polar direct drive solid target experiment at the National Ignition Facility. The new illumination configuration is simulated to create greater than ×3 higher peak pressure and almost ×2 higher density by maintaining better shock uniformity. Furthermore, the optimization process is performed with reduced computational expense and isotropic plasma profiles, while accounting for the impact of cross-beam energy transfer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Designing an Intrusion Detection for an Adjustable Speed Drive System Controlling a Critical Process

In this article, we address the cyber-security problem of industrial control systems (ICSs) when their sensor measurements may be compromised due to an attacker who has intercepted those measurements via a network. We introduce a general-purpose method “Dynamic Watermarking (DW)” to detect potential cyber-intrusions on speed sensor measurements within industrial control systems, which deploy an adjustable speed drive (ASD) to control a critical process. The DW method is injecting a random private low-amplitude signal with a zero mean Gaussian distribution, “watermark”, into one of the input phase voltages powering the ASD system. The watermark signal propagates through the system including pulse width modulation (PWM) power conversion stage and motor, then ultimately appears in the speed sensor measurements. By deploying two statistical DW tests with two proper thresholds, the system can detect potential cyber-intrusions or unobservable cyber-attacks such as replay attacks and false data injection attacks (FDIA). The DW method tested on a laboratory-scale ASD system experimentally to protect the system against cyber-intrusions. This system, powered by a commercial PWM drive operating at 208 V, 3-phase, and 3.7 kW, served as our experimental platform.

42 ENGINEERING↗
DOE OSTI2024

High-bandwidth Dynamic Load Emulation of Mechanical Systems using Electric Drives

Machine drives are versatile systems that can be programmed to emulate a variety of mechanical loads. In this paper, we walk through the modeling and control framework of a shaft-coupled dual-motor drive system that is programmed to emulate a fictitious mechanical system. We quantitatively evaluate the control performance of such a system and derive a theoretical limit that explains its inaccuracy at high operating frequencies. To overcome this problem, we propose an alternate control structure that achieves the same control objective at high frequencies as well. After suitable adjustments are made to the controller, we validate its performance using simulation results.

machine drives ,load emulation, speed-torque chara↗
DOE OSTI2020

Optimal Eco-Driving Control of Connected and Autonomous Vehicles Through Signalized Intersections

This article focuses on the speed planning problem for connected and automated vehicles (CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalized intersections on the road is considered. The eco-driving problem is formulated as a data-driven chance-constrained robust optimization problem. Effective red-light duration (ERD) is defined as a random variable, and describes the feasible passing time through the signalized intersections. Usually, the true probability distribution for ERD is unknown. Consequently, a data-driven approach is adopted to formulate chance constraints based on empirical sample data. This incorporates robustness into the eco-driving control problem with respect to uncertain signal timing. Dynamic programming (DP) is employed to solve the optimization problem. The simulation results demonstrate that the proposed method can generate optimal speed reference trajectories with 40% less vehicle fuel consumption, while maintaining the arrival time at a similar level compared to a modified intelligent driver model (IDM). The proposed control approach significantly improves the controller's robustness in the face of uncertain signal timing, without requiring to know the distribution of the random variable a priori.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Exploring Social Dynamics of Hard-Disk Drives Circularity with an Agent-Based Approach

By 2025, it is estimated that installed data storage in the U.S. will be 2.2 Zettabytes, generating about 50 million units of end-of-life hard-disk drives (HDDs) per year. The circular economy (CE) tackles waste issues by maximizing value retention in the economy, for instance, through reuse and recycling. However, the reuse of hard disk drives is hindered by the lack of trust organizations have toward other means of data removal than physically destroying HDDs. Here, an agent-based approach explores how organizations' decisions to adopt other data removal means affect HDDs' circularity. The model applies the theory of planned behavior to model the decisions of HDDs end-users. Results demonstrate that the attitude (which is affected by trust) of end-users toward data-wiping technologies acts as a barrier to reuse. Moreover, social pressure can play a significant role as organizations that adopt CE behaviors can set an example for others.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2021

Electric-Drive Vehicle Power Electronics Thermal Management: Current Status, Challenges, and Future Directions

Effective thermal management of traction-drive power electronics is critical to the advancement of electric-drive vehicles and is necessary for increasing power density and improving reliability. Replacing traditional silicon devices with more efficient, higher temperature, higher voltage, and higher frequency wide-bandgap (WBG) devices will enable increased power density but will result in higher device heat fluxes. Compact packaging of high-temperature WBG devices near low-temperature-rated components creates thermal management challenges that need to be addressed for future power-dense systems. This paper summarizes the thermal performance of on-road automotive power electronics thermal management systems and provides thermal performance and pumping-power metrics for select vehicles. Thermal analyses reveal that the package/conduction resistance dominates the total thermal resistance (for existing automotive systems). We model advanced packaging concepts and compare the results with existing packaging designs to quantify their thermal performance enhancements. Double-side-cooled configurations that do not use thermal interface materials are package concepts predicted to provide a low junction-to-fluid thermal resistance (compared to current packages). Dielectric-fluid-cooled concepts enable a redesign of the package to reduce the package resistance, can be implemented in single- and two-phase cooling approaches, and allow for cooling of passive components (e.g., capacitors) and bus bars.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

2021 Smoky Mountains Conference Data Challenge Synthetic-to-Real Domain Adaptation for Autonomous Driving Dataset

The dataset is comprised of both real and synthetic images from a vehicle's forward-facing camera. Each camera image is accompanied by a corresponding pixel-level semantic segmentation image (all files are .png files). In total, the dataset contains 5600 images in the training/validation set and 1400 images in the testing set. The training dataset contains mostly synthetic RGB images collected with a wide range of weather and lighting conditions using the CARLA simulator [1]. In addition, the training data also includes a small pre-selected subset of data from the Cityscapes training dataset – which is comprised of RGB-segmentation image pairs from driving scenarios in various European cities [2]. The testing data is split into three sets. The first set contains synthetic CARLA images with weather/lighting conditions that were not present in the training set. The second set is a subset of the Cityscapes testing dataset. Finally, the third set is an unknown testing set which will not be revealed to the participants until after the submission deadline. [1] Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., and Koltun, V. (2017, October). CARLA: An open urban driving simulator. In Conference on robot learning (pp. 1-16). PMLR. [2] Cordts, M., Omran, M., Ramos, S., Rehfeld, T., Enzweiler, M., Benenson, R., ... and Schiele, B. (2016). The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3213-3223).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Cooperative Automated Cohort Driving on Connected Infrastructure, Arterial Roadways, and Highways: Final Project Demonstration and System-of-Systems Model Correlation

This project seeks to synergize vehicle automated driving and connectivity data to improve mobility and energy efficiency of groups of mixed vehicles operating in close proximity (vehicle cohort) on various infrastructure. A custom cellular communication network links vehicles operating as a cohort with infrastructure to a centralized system-of-systems digital twin with an AI-based optimal behavior planner. The data contained in this set are from final testing and technology demonstrations to U.S. Department of Energy staff at the American Center for Mobility. The data contain single-lane, single-light scenarios; multi-lane, multi-light arterial scenarios; and limited-access highway scenarios. All test cases were derived from simulations and replicated on the test track. The project employed two and four light-duty vehicles with connectivity and drive automation for the testing. The baseline scenario without connectivity was run under the control of the system-of-systems centralized planner but operating each vehicle with an intelligent driver model controlling the velocity, lane utilization, and vehicle gap. This was to ensure the highest compatibility with the simulation in terms of dynamic behavior. The connected cohort case utilized AI optimization to perform coordinated and cooperative control for energy, as well as safe, comfortable behavior for the cohort. The dataset is appropriately named with unconnected and connected designations, with comparisons sharing the same run index number. The included PowerPoint and PDF files describe the test setup and provide an overview of results from the project. ![image](de-EE0009209_March_2023_Data_Arterial_Scenario_Results.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Test of a Novel, Commercial-Scale Wave Energy Direct-Drive Rotary Power Take-Off at the NREL National Wind Technology Center (CRADA CRD-14-571 Final Report)

The National Renewable Energy Laboratory (NREL) will work with Columbia Power Technologies [C-Power] to support work under US DOE DE-EE-0006399, “Build and Test of a Novel, Commercial-Scale Wave Energy Direct-Drive Rotary Power Take-Off Under Realistic Open-Ocean Conditions.” Work will include a review of their design for a novel wave energy direct drive generator. After review, the system will be prototyped and tested in the NREL National Wind Technology Center (NWTC) 5MW dynamometer and data will be recorded and analyzed. Conclusions from data analysis will be used to improve the design prior to completing a version of the system for ocean deployment. Additionally, NREL will work with Columbia Power Technologies [C-Power] to quantify the system levelized cost of energy (LCOE) and analyze the system in agreement with US DOE System Performance Advancement (SPA) goals 1 and 2.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Fully Integrated High Speed Megawatt Class Motor and High Frequency Variable Speed Drive System

This project involved developing a fully integrated high speed megawatt class motor and high frequency variable speed drive system that serve as a commercially viable and technically sound methodology for high speed industrial system applications. The project team organizations consist of Clemson University and TECO Westinghouse Motor Company (TWMC) formed an academic and industrial collaboration that combines the design, analysis, manufacturing and testing experience required for a large research project of this magnitude. The project resulted in an integrated high speed megawatt class medium voltage motor drive system that is at a TRL 6 with a clear path for commercialization. The fully integrated prototype system has been manufactured by TWMC in its Round Rock, Texas facility and tested at full power on a dynamometer at the Clemson University’s eGRID Center in North Charleston, South Carolina.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Koopman Model Predictive Control for Eco-Driving of Automated Vehicles

In this paper, we develop a data-driven process for building a model predictive control (MPC) for eco-driving of automated vehicles. The process involves performing system identification in which the non-linear vehicle dynamics model is approximated by the Koopman operator, a linear predictor of higher state-dimension, in a data-driven framework. This approach allows us to formulate the eco-driving problem in a constrained quadratic program that leads to a computationally fast MPC. The MPC is then implemented as a closed-loop control of an electric vehicle in numerical simulations for demonstration.

autonomous vehicle↗
DOE OSTI2025

HOLISTIC ENERGY EFFICIENCY ANALYSIS OF ELECTRIFIED OFF-HIGHWAY MATERIAL HANDLER: FROM DRIVE CYCLE CHARACTERIZATION TO POWERTRAIN, HYDRAULIC, AND THERMAL SYSTEM PERFORMANCE

Three complexities surrounding the operation and testing of hybrid electric, heavy-duty nonroad machines have been addressed experimentally and using 1D simulation. Their resolutions have been intertwined with the development of a prototype machine that was proven to reduce fuel consumption in excess of 20%. A real-world drive cycle that leveraged hydraulic cylinder position was developed and utilized to ensure accurate reproduction of hydraulic work between the baseline and hybrid machines, while simultaneously maintaining less than 5% RMS error in position for main load handling functions. The newly developed, machine-specific drive cycle also contributed towards making equivalent comparisons in energy consumption between machine types through composite performance metrics that were extrapolated over a typical shift duration. Lastly, this work addressed thermal management energy consumption, a topic of increasing popularity when discussing electrified vehicles, by proposing a 1.4% energy savings through special mechanization and control of cooling system components.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Exploring Social Dynamics of Hard-Disk Drives Circularity with an Agent-Based Approach: Preprint

By 2025, it is estimated that installed data storage in the US will be 2.2 Zettabytes, generating about 50 million units of end-of-life hard-disk drives (HDDs) per year. The circular economy tackles waste issues by maximizing value retention in the economy, for instance, through reuse and recycling. However, the reuse of hard disk drives is hindered by the lack of trust organizations have toward other means of data removal than physically destroying HDDs. Here, an agent-based approach explores how organizations’ decisions to adopt other data removal means affect HDDs circularity. The model applies the theory of planned behaviour to model the decisions of HDDs end-users. Results demonstrate that the attitude (which is affected by trust) of end-users toward data-wiping technologies acts as a barrier to reuse. Moreover, social pressure can play a significant role as organizations that adopt CE behaviours can set an example for others.

28 EE - Advanced Manufacturing Office (EE-5A)↗