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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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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Semiconductor optoelectronic devices for free-space optical communications

The properties of individual injection lasers are reviewed, and devices of greater complexity are described. These either include or are relevant to monolithic integration configurations of the lasers with their electronic driving circuitry, power combining methods of semiconductor lasers, and electronic methods of steering the radiation patterns of semiconductor lasers and laser arrays. The potential of AlGaAs laser technology for free-space optical communications systems is demonstrated. These solid-state components, which can generate and modulate light, combine the power of a number of sources and perform at least part of the beam pointing functions. Methods are proposed for overcoming the main drawback of semiconductor lasers, that is, their inability to emit the needed amount of optical power in a single-mode operation.

Katz, J.↗
NASA NTRS1988

NASA/Army Rotorcraft Technology. Volume 1: Aerodynamics, and Dynamics and Aeroelasticity

The Conference Proceedings is a compilation of over 30 technical papers presented at this milestone event which reported on the advances in rotorcraft technical knowledge resulting from NASA, Army, and industry rotorcraft research programs over the last 5 to 10 years. The Conference brought together over 230 government, industry, and allied nation conferees to exchange technical information and hear invited technical papers by prominent NASA, Army, and industry researchers covering technology topics which included: aerodynamics, dynamics and elasticity, propulsion and drive systems, flight dynamics and control, acoustics, systems integration, and research aircraft.

Source record↗
NASA NTRS1990

Interferometric Fiber-Optic Gyroscope

Integrated three-waveguide directional coupler functions as polarizer and splitter. Designed with transverse electric (TE) polarization in bar state (two coupling lengths) and transverse magnetic (TM) polarization in cross state (one coupling length). Intended for eventual fabrication as in mass-producible integrated optical circuit that provides advantages including low drive voltage, large-bandwidth phase modulation, preservation of polarization in transmission between devices on same substrate, and low cost.

Depaula, Ramon P.↗
NASA NTRS2011

Human-Robot Interaction Directed Research Project

Human-robot interaction (HRI) is about understanding and shaping the interactions between humans and robots (Goodrich & Schultz, 2007). It is important to evaluate how the design of interfaces and command modalities affect the human s ability to perform tasks accurately, efficiently, and effectively (Crandall, Goodrich, Olsen Jr., & Nielsen, 2005) It is also critical to evaluate the effects of human-robot interfaces and command modalities on operator mental workload (Sheridan, 1992) and situation awareness (Endsley, Bolt , & Jones, 2003). By understanding the effects of interface design on human performance, workload, and situation awareness, interfaces can be developed that support the human in performing tasks with minimal errors and with appropriate interaction time and effort. Thus, the results of research on human-robot interfaces have direct implications for design. Because the factors associated with interfaces and command modalities in HRI are too numerous to address in 3 years of research, the proposed research concentrates on three manageable areas applicable to National Aeronautics and Space Administration (NASA) robot systems. These topic areas emerged from the Fiscal Year (FY) 2011 work that included extensive literature reviews and observations of NASA systems. The three topic areas are: 1) video overlays, 2) camera views, and 3) command modalities. Each area is described in detail below, along with relevance to existing NASA human-robot systems. In addition to studies in these three topic areas, a workshop is proposed for FY12. The workshop will bring together experts in human-robot interaction and robotics to discuss the state of the practice as applicable to research in space robotics. Studies proposed in the area of video overlays consider two factors in the implementation of augmented reality (AR) for operator displays during teleoperation. The first of these factors is the type of navigational guidance provided by AR symbology. In the proposed studies, participants performance during teleoperation of a robot arm will be compared when they are provided with command-guidance symbology (that is, directing the operator what commands to make) or situation-guidance symbology (that is, providing natural cues so that the operator can infer what commands to make). The second factor for AR symbology is the effects of overlays that are either superimposed or integrated into the external view of the world. A study is proposed in which the effects of superimposed and integrated overlays on operator task performance during teleoperated driving tasks are compared

Rochlis, Jennifer↗
DOE OSTI2021

Rapidly ramp cryogenic air separation unit without loss of O2 product purity—application for low-carbon fossil-fuel plants

The rapid integration of intermittent renewable sources into the electricity grid is driving the need for low-carbon, fossil-fuel power plant capable of rapid ramping. Therefore, a cryogenic air separation unit (ASU) as part of low-carbon, fossil-fuel power plant should be capable of rapid ramping. However, highly integrated and nonlinear processes of the ASU would significantly restrict this rapid ramping. To overcome this fundamental issue, we study the basic dynamic process of a state-of-the-art double-column ASU. A flow-driven dynamic model was established in Aspen Plus Dynamics, assuming perfect flow controls, to capture the basic dynamics of ramping ASU. We find the vapor-liquid counter-current flow structure in the low-pressure column is critical to the air separation when rapidly ramping the ASU. This flow structure is established based on a complicated heat integration process. It is simplified as an apparent counter-current heat transfer process in this work, which greatly reduces the complexity for studying the dynamics of ASU. For keeping this basic flow structure, the heat integration is maintained as its heat duty follows the ASU load, through several basic feed-forward and feed-back controllers on the critical stream flowrates. Moreover, we find a fundamental issue of mismatched dynamics in the low-pressure column, resulting in a significant loss of O2 product purity when rapidly ramping down the ASU and an obvious fluctuation of O2 product purity. Based on these explorations, we propose a basic control method for rapidly ramping the ASU without loss of O2 product purity. Results show the ASU basic dynamic process successfully ramps at a rate up to 10%/min (40-100% load) while maintaining the O2 product purity within 95.2-95.6 mol%.

Cheng, Mao↗
NASA NTRS2009

Concepts for Life Cycle Cost Control Required to Achieve Space Transportation Affordability and Sustainability

Cost control must be implemented through the establishment of requirements and controlled continually by managing to these requirements. Cost control of the non-recurring side of life cycle cost has traditionally been implemented in both commercial and government programs. The government uses the budget process to implement this control. The commercial approach is to use a similar process of allocating the non-recurring cost to major elements of the program. This type of control generally manages through a work breakdown structure (WBS) by defining the major elements of the program. If the cost control is to be applied across the entire program life cycle cost (LCC), the approach must be addressed very differently. A functional breakdown structure (FBS) is defined and recommended. Use of a FBS provides the visibifity to allow the choice of an integrated solution reducing the cost of providing many different elements of like function. The different functional solutions that drive the hardware logistics, quantity of documentation, operational labor, reliability and maintainability balance, and total integration of the entire system from DDT&E through the life of the program must be fully defined, compared, and final decisions made among these competing solutions. The major drivers of recurring cost have been identified and are presented and discussed. The LCC requirements must be established and flowed down to provide control of LCC. This LCC control will require a structured rigid process similar to the one traditionally used to control weight/performance for space transportation systems throughout the entire program. It has been demonstrated over the last 30 years that without a firm requirement and methodically structured cost control, it is unlikely that affordable and sustainable space transportation system LCC will be achieved.

Rhodes, Russel E.↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗
NASA NTRS1982

Progress on advanced dc and ac induction drives for electric vehicles

Progress is reported in the development of complete electric vehicle propulsion systems, and the results of tests on the Road Load Simulator of two such systems representative of advanced dc and ac drive technology are presented. One is the system used in the DOE's ETV-1 integrated test vehicle which consists of a shunt wound dc traction motor under microprocessor control using a transistorized controller. The motor drives the vehicle through a fixed ratio transmission. The second system uses an ac induction motor controlled by transistorized pulse width modulated inverter which drives through a two speed automatically shifted transmission. The inverter and transmission both operate under the control of a microprocessor. The characteristics of these systems are also compared with the propulsion system technology available in vehicles being manufactured at the inception of the DOE program and with an advanced, highly integrated propulsion system upon which technology development was recently initiated.

Schwartz, H. J.↗
NASA NTRS2000

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

In this report, a fully integrated prototype of a flight servo control system is successfully developed and implemented using brushless dc motors. The control system is developed by the fuzzy logic theory, and implemented with a multilayer neural network. First, a neural network-based architecture is introduced for fuzzy logic control. The characteristic rules and their membership functions of fuzzy systems are represented as the processing nodes in the neural network structure. The network structure and the parameter learning are performed simultaneously and online in the fuzzy-neural network system. The structure learning is based on the partition of input space. The parameter learning is based on the supervised gradient decent method, using a delta adaptation law. Using experimental setup, the performance of the proposed control system is evaluated under various operating conditions. Test results are presented and discussed in the report. The proposed learning control system has several advantages, namely, simple structure and learning capability, robustness and high tracking performance and few nodes at hidden layers. In comparison with the PI controller, the proposed fuzzy-neural network system can yield a better dynamic performance with shorter settling time, and without overshoot. Experimental results have shown that the proposed control system is adaptive and robust in responding to a wide range of operating conditions. In summary, the goal of this study is to design and implement-advanced servosystems to actuate control surfaces for flight vehicles, namely, aircraft and helicopters, missiles and interceptors, and mini- and micro-air vehicles.

Rubaai, Ahmed↗
DOE OSTI2022

System, method, and apparatus for integrating high power density power electronics on a mobile application

A motor drive converter includes a cold plate having a first side and a second side, the first side being opposite to the second side. The motor drive converter may further include at least one motor phase power electronics disposed on the first side of the cold plate, and a capacitor array disposed on the second side of the cold plate. The cold plate may include slots therethrough for a conductor to pass through the cold plate. The conductor may be configured to electrically coupling the capacitor array and the at least one motor phase power electronics.

Stoltz, Thomas Joseph↗
DOE OSTI2020

Corroborative Evaluation of the Real-World Energy Saving Potentials of InfoRich Eco-Autonomous Driving (iREAD) System

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing. These four approaches, spanning simulation and testing aspects, evaluate real-world fuel economy benefits with different ranges and resolutions. The large-scale simulations leverage an extensive real-world driving database to assess overall eco-driving benefits across a range of road network and driving scenarios. The real-world driving data are further leveraged to generate representative driving routes for deeper evaluation. Based on the representative routes, in-depth simulation relying on high-fidelity models investigates how different traffic scenarios can impact the eco-driving performance. The vehicle-in-the-loop setup reinforces the in-depth simulations by conducting tests with an actual vehicle operated on a chassis dynamometer; the measured energy savings were indeed found to agree with the in-depth simulation savings estimates. Finally, limited but representative road testing with the fully integrated vehicle will be conducted to demonstrate the eco-driving capability and conclude the overall evaluation regimen.

ARPA-E↗
NASA NTRS1997

Steady-State Pursuit Is Driven by Object Motion Rather Than the Vector Average of Local Motions

We have previously shown that humans can pursue the motion of objects whose trajectories can be recovered only by spatio-temporal integration of local motion signals. We now explore the integration rule used to derive the target-motion signal driving pursuit. We measured the pursuit response of 4 observers (2 naive) to the motion of a line-figure diamond viewed through two vertical bar apertures (0.2 cd/square m). The comers were always occluded so that only four line segments (93 cd/square m) were visible behind the occluding foreground (38 cd/square m). The diamond was flattened (40 & 140 degree vertex angles) such that vector averaging of the local normal motions and vertical integration (e.g. IOC) yield very I or different predictions, analogous to using a Type II plaid. The diamond moved along Lissajous-figure trajectories (Ax = Ay = 2 degrees; TFx = 0.8 Hz; TFy = 0.4 Hz). We presented only 1.25 cycles and used 6 different randomly interleaved initial relative phases to minimize the role of predictive strategies. Observers were instructed to track the diamond and reported that its motion was always coherent (unlike type II plaids). Saccade-free portions of the horizontal and vertical eye-position traces sampled at 240 Hz were fit by separate sinusoids. Pursuit gain with respect to the diamond averaged 0.7 across subjects and directions. The ratio of the mean vertical to horizontal amplitude of the pursuit response was 1.7 +/- 0.7 averaged across subjects (1SD). This is close to the prediction of 1.0 from vertical motion-integration rules, but far from 7.7 predicted by vector averaging and infinity predicted by segment- or terminator-tracking strategies. Because there is no retinal motion which directly corresponds to the diamond's motion, steady-state pursuit of our "virtual" diamond is not closed-loop in the traditional sense. Thus, accurate pursuit is unlikely to result simply from local retinal negative feedback. We conclude that the signal driving steady-state pursuit is not the vector average of local motion signals, but rather a more vertical estimate of object motion, derived in extrastriate cortical areas beyond V1, perhaps NIT or MST.

Stone, Leland S.↗
DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

Reverse Flow Engine Core Having a Ducted Fan with Integrated Secondary Flow Blades

Secondary air flow is provided for a ducted fan having a reverse flow turbine engine core driving a fan blisk. The fan blisk incorporates a set of thrust fan blades extending from an outer hub and a set of integral secondary flow blades extending intermediate an inner hub and the outer hub. A nacelle provides an outer flow duct for the thrust fan blades and a secondary flow duct carries flow from the integral secondary flow blades as cooling air for components of the reverse flow turbine engine.

Kisska, Michael K.↗
DOE OSTI2022

Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

A Multirange Vehicle Speed Prediction With Application to Model Predictive Control-Based Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles

Abstract Connectivity and automated driving technologies have opened up new research directions in the energy management of vehicles which exploit look-ahead preview and enhance the situational awareness. Despite this advancement, the vehicle speed preview that can be obtained from vehicle-to-vehicle/infrastructure (V2V/I) communications is often limited to a relatively short time-horizon. The vehicular energy systems, specifically those of the electrified vehicles, consist of multiple interacting power and thermal subsystems that respond over different time-scales. Consequently, their optimal energy management can greatly benefit from long-term speed prediction beyond that available through V2V/I communications. Accurately extending the look-ahead preview, on the other hand, is fundamentally challenging due to the dynamic nature of the traffic environment. To address this challenge, we propose a data-driven multirange vehicle speed prediction strategy for arterial corridors with signalized intersections, providing the vehicle speed preview for three different ranges, i.e., short-, medium-, and long-range. The short-range preview is obtained by V2V/I communications. The medium-range preview is realized using a neural network (NN), while the long-range preview is predicted based on a Bayesian network (BN). The predictions are updated in real-time based on the current state of traffic and incorporated into a multihorizon model predictive control (MH-MPC) for integrated power and thermal management (iPTM) of connected vehicles. The results of design and evaluation of the performance of the proposed data-informed MH-MPC for iPTM of connected hybrid electric vehicles (HEVs) using traffic data for real-world city driving are reported.

Automation & Control Systems↗
DOE OSTI2025

Low Cost High-Performance HRE-Free 3-in-1 Electric Drive Unit

The project team completed work to expand upon American Axle & Manufacturing’s (AAM) baseline technology and develop a high-speed, AC induction electric drive unit (EDU) with total direct-oil-cooling and integrated power electronics. The project accelerated advancements in EDU technology by allowing AAM to build upon the progress made in developing the underlying baseline technologies. The following seven improvements to AAM’s baseline technology were implemented in this research and development program: 1) Increased speed (30k RPM) AC induction motor, 2) Silver-sintering of discrete silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFET) to heat sinks, 3) Electrically insulated rotor bars, 4) Optimized lamination steel, 5) EDU-integrated 650VDC inverter package, 6) Over-molded stator with molded liners, and 7) 650VDC power-dense stator design. The successful development of the technology resulted in a meaningful cost reduction for EDU systems in the market. Coupled with falling battery system costs, lower EDU costs will likely accelerate the market acceptance and related production scaling of battery electric vehicles. The objective of this project was to research, develop, and test a Heavy Rare Earth (HRE)-free 3-In-1 electric drive unit (EDU) that has class leading power density and cost. The key technologies to be developed were anticipated to meet or exceed the Department of Energy (DOE) targets of a cost ≤ $\$$7/kilowatt (kW), power density ≥ 12 kW/liter, and operating voltage ≥ 600 VDC.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Kinetic Inductance Traveling Wave Amplifier Designs for Practical Microwave Readout Applications

Abstract A Kinetic Inductance Traveling Wave Amplifier (KIT) utilizes the nonlinear kinetic inductance of superconducting films, particularly niobium titanium nitride (NbTiN), for parametric amplification. These amplifiers achieve remarkable performance in terms of gain, bandwidth, and compression power and frequently approach the quantum limit for noise. However, most KIT demonstrations have been isolated from practical device readout systems. Using a KIT as the first amplifier in the readout chain of an unoptimized microwave SQUID multiplexer coupled to a transition-edge sensor microcalorimeter, we see an initial improvement in the flux noise [1]. One challenge in KIT integration is the considerable microwave pump power required to drive the non-linearity. To address this, we have initiated efforts to reduce the pump power by using thinner NbTiN films and an inverted microstrip transmission line design. In this article, we present the new transmission line design, fabrication procedure, and initial device characterization—including gain and added noise. These devices exhibit over 10 dB of gain with a 3 dB bandwidth of approximately 5.5–7.25 GHz, a maximum practical gain of 12 dB, and typical gain ripple under 4 dB peak to peak. We observe an appreciable impedance mismatch in the NbTiN transmission line, which is likely the source of the majority of the gain ripple. Finally, we perform an initial noise characterization and demonstrate system-added noise of three quanta or less over nearly the entire 3 dB bandwidth.

Physics↗