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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Perception Testing in Fog for Autonomous Flight

As the path towards Urban Air Mobility (UAM) continues to take shape, there are outstanding technical challenges to achieving safe and effective air transportation operations under this new paradigm. To inform and guide technology development for UAM, NASA is investigating the current state-of-the-art in key technology areas including traffic management, detect-and-avoid, and autonomy. In support of this effort, a new perception testbed was developed at NASA Ames Research Center to collect data from an array of sensing systems representative of those that could be found on a future UAM vehicle. This testbed, featuring a Light-Detection-and-Ranging (LIDAR) instrument, a long-wave infrared sensor, and a visible spectrum camera was deployed for a multiday test campaign in the Fog Chamber at Sandia National Laboratories (SNL), in Albuquerque, New Mexico. During the test campaign, fog conditions were created for tests with targets including a human, a resolution chart, and a small unmanned aerial vehicle (sUAV). Here, this paper describes in detail, the developed perception testbed, the experimental setup in the fog chamber, the resulting data, and presents an initial result from analysis of the data with the evaluation of methods to increase contrast through filtering techniques.

aeronautics↗
DOE OSTI2022

Molecular analysis and essentiality of Aro1 shikimate biosynthesis multi-enzyme in Candida albicans

In the human fungal pathogen Candida albicans, ARO1 encodes an essential multi-enzyme that catalyses consecutive steps in the shikimate pathway for biosynthesis of chorismate, a precursor to folate and the aromatic amino acids. We obtained the first molecular image of C. albicans Aro1 that reveals the architecture of all five enzymatic domains and their arrangement in the context of the full-length protein. Aro1 forms a flexible dimer allowing relative autonomy of enzymatic function of the individual domains. Our activity and in cellulo data suggest that only four of Aro1’s enzymatic domains are functional and essential for viability of C. albicans, whereas the 3-dehydroquinate dehydratase (DHQase) domain is inactive because of active site substitutions. We further demonstrate that in C. albicans, the type II DHQase Dqd1 can compensate for the inactive DHQase domain of Aro1, suggesting an unrecognized essential role for this enzyme in shikimate biosynthesis. In contrast, in Candida glabrata and Candida parapsilosis, which do not encode a Dqd1 homolog, Aro1 DHQase domains are enzymatically active, highlighting diversity across Candida species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Human-Building Collaboration: Toward lighting enabled collaborative system design

The profession of lighting design is evolving as contemporary lighting systems increasingly rely on cutting-edge computational technologies, sensors, and IOT systems. This trend requires designers to incorporate ideas of automation, dynamic controls, and user-system interaction into their design logic. However, real-time lighting simulations are constrained by inherent limitations arising from the reductive assumptions inevitably introduced in simulated lighting environments. This raises the question of how can designers account for the discrepancies between simulated and real lighting environments, and how can collaboration between humans and autonomous lighting systems bridge this gap. To address this question, we propose a protocol for designing collaborative interactions between humans and systems. Furthermore, this protocol builds on the Human-Lighting System Interaction Framework and demonstrates how human and system intelligence can be combined to fine-tune lighting qualities in a given space. Our paper shows how interactive lighting systems can customize lighting based on user preferences in real-time and how global lighting configurations can be adjusted over time. Specifically, we demonstrate: a) Human-system collaboration assumptions and goals, as well as how the protocol can be integrated into digitally programmable lighting systems. b) Implementations of collaboration that reveal how system autonomy, performance, and user experience are improved over short and long-term timeframes. c) How lighting design can be enhanced beyond simulation-driven design optimization capacities. The associated affordances and limitations are discussed with respect to existing lighting simulation design frameworks.

autonomous systems↗
DOE OSTI2024

Fueling the Future: The Emergence of Self-Powered Enzymatic Biofuel Cell Biosensors

Self-powered biosensors are innovative devices that can detect and analyze biological or chemical substances without the need for an external power source. These biosensors can convert energy from the surrounding environment or the analyte itself into electrical signals for sensing and data transmission. The self-powered nature of these biosensors offers several advantages, such as portability, autonomy, and reduced waste generation from disposable batteries. They find applications in various fields, including healthcare, environmental monitoring, food safety, and wearable devices. While self-powered biosensors are a promising technology, there are still challenges to address, such as improving energy efficiency, sensitivity, and stability to make them more practical and widely adopted. This review article focuses on exploring the evolving trends in self-powered biosensor design, outlining potential advantages and limitations. With a focal point on enzymatic biofuel cell power generation, this article describes various sensing mechanisms that employ the analyte as substrate or fuel for the biocatalyst’s ability to generate current. Technical aspects of biofuel cells are also examined. Research and development in the field of self-powered biosensors is ongoing, and this review describes promising areas for further exploration within the field, identifying underexplored areas that could benefit from further investigation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Development and Evaluation of Velocity Predictive Optimal Energy Management Strategies in Intelligent and Connected Hybrid Electric Vehicles

In this study, a thorough and definitive evaluation of Predictive Optimal Energy Management Strategy (POEMS) applications in connected vehicles using 10 to 20 s predicted velocity is conducted for a Hybrid Electric Vehicle (HEV). The presented methodology includes synchronous datasets gathered in Fort Collins, Colorado using a test vehicle equipped with sensors to measure ego vehicle position and motion and that of surrounding objects as well as receive Infrastructure to Vehicle (I2V) information. These datasets are utilized to compare the effect of different signal categories on prediction fidelity for different prediction horizons within a POEMS framework. Multiple artificial intelligence (AI) and machine learning (ML) algorithms use the collected data to output future vehicle velocity prediction models. The effects of different combinations of signals and different models on prediction fidelity in various prediction windows are explored. All of these combinations are ultimately addressed where the rubber meets the road: fuel economy (FE) enabled from POEMS. FE optimization is performed using Model Predictive Control (MPC) with a Dynamic Programming (DP) optimizer. FE improvements from MPC control at various prediction time horizons are compared to that of full-cycle DP. All FE results are determined using high-fidelity simulations of an Autonomie 2010 Toyota Prius model. The full-cycle DP POEMS provides the theoretical upper limit on fuel economy (FE) improvement achievable with POEMS but is not currently practical for real-world implementation. Perfect prediction MPC (PP-MPC) represents the upper limit of FE improvement practically achievable with POEMS. Real-Prediction MPC (RP-MPC) can provide nearly equivalent FE improvement when used with high-fidelity predictions. Constant-Velocity MPC (CV-MPC) uses a constant speed prediction and serves as a “null” POEMS. Results showed that RP-MPC, enabled by high-fidelity ego future speed prediction, led to significant FE improvement over baseline nearly matching that of PP-MPC.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Distributed Energy Management for Networked Microgrids with Hardware-in-the-Loop Validation

For the cooperative operation of networked microgrids, a distributed energy management considering network operational objectives and constraints is proposed in this work. Considering various ownership and privacy requirements of microgrids, utility directly interfaced distributed energy resources (DERs) and demand response, a distributed optimization is proposed for obtaining optimal network operational objectives with constraints satisfied through iteratively updated price signals. The alternating direction method of multipliers (ADMM) algorithm is utilized to solve the formulated distributed optimization. The proposed distributed energy management provides microgrids, utility-directly interfaced DERs and responsive demands the opportunity of contributing to better network operational objectives while preserving their privacy and autonomy. Results of numerical simulation using a networked microgrids system consisting of several microgrids, utility directly interfaced DERs and responsive demands validate the soundness and accuracy of the proposed distributed energy management. The proposed method is further tested on a practical two-microgrid system located in Adjuntas, Puerto Rico, and the applicability of the proposed strategy is validated through hardware-in-the-loop (HIL) testing.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Future Cost Benefits Analysis for Electrified Vehicles from Advances Due to U.S. Department of Energy Targets

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Future Battery Material Demand Analysis Based on U.S. Department of Energy R&D Targets

The U.S. Department of Energy’s Vehicle Technologies Office (VTO) supports research, development, and deployment of efficient, sustainable transportation technologies that will improve energy efficiency and fuel economy, and enable America to use less petroleum. To accelerate the development and adoption of new technologies, VTO has developed specific targets for a wide range of powertrain components, including the energy storage system. In this study, we use Autonomie, Argonne National Laboratory’s (Argonne’s) vehicle system simulation tool to evaluate future energy storage requirements (power, energy, etc.) for different vehicle classes, powertrains, component technologies and timeframes. BatPac, Argonne’s tool dedicated to energy storage pack design and costs, is then used to quantify the materials required for each pack. Market penetrations are then used to estimate the overall material demand worldwide and in the United States, with or without recycling. The results demonstrate that the positive impact of VTO research and development will lead to significant reduction in material compared to business-as-usual due to new anode and cathode designs, along with acceleration in battery cell chemistry penetrations. In terms of material demands, it is observed that lithium demand reaches about 80,000 tons (by a factor of 42–45), nickel demand reaches about 500,000 tons (by a factor of 47–56), manganese demand reaches about 30,000–50,000 tons (by a factor of 20–34), and cobalt demand reaches about 30,000 tons (by a factor of 13–28) in the future by 2050. The individual material demand per unit energy, however, decreases significantly in the future due to advances in VTO research and development activities. The increase in battery material demands is mostly driven by increased electrified vehicle fleet penetration in the markets.

25 ENERGY STORAGE↗
DOE OSTI2024

Simulation-Based Assessment of Energy Consumption of Alternative Powertrains in Agricultural Tractors

The objectives of this research were to develop simulation models for agricultural tractors with different powertrain technologies and evaluate the energy consumption in typical agricultural operations. Simulation models were developed for conventional, parallel hybrid electric, series hybrid electric, fuel cell hybrid, and battery electric powertrains. Autonomie vehicle simulation software (version 2022) was used for the simulations and the tractor models were simulated in two tilling cycles and in a road transport cycle with a trailer. The alternative powertrains were configured to have at least the same tractive performance as the conventional, diesel engine-powered tractor model. The simulation results showed that the potential of the parallel and series hybrid powertrains to improve energy efficiency depends heavily on the tractor size and the operating cycle conditions. The fuel cell hybrid and battery electric powertrains have a higher potential to reduce energy consumption and emissions but still have inherent technical challenges for practical operation. The battery-powered electric tractor would require improvements in the storage energy density to have a comparable operational performance in comparison to other powertrains. The fuel cell hybrid tractor already provided an adequate operating performance but the availability of hydrogen and refueling infrastructure could be challenging to resolve in the farming context.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Charting the Path to Electrification: Analyzing the Economic and Technological Potential of Advanced Vehicle Powertrains

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) is driving advancements in highway transportation by targeting energy efficiency, environmental sustainability, and cost reductions. This study investigates the fuel economy potential and cost implications of advanced powertrain technologies using comprehensive system simulations. Leveraging tools such as Autonomie and TechScape, developed by Argonne National Laboratory, this study evaluates multiple timeframes (2023–2050) and powertrain types, including conventional internal combustion engines, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). Simulations conducted across standard regulatory driving cycles provide detailed insights into fuel economy improvements, cost trajectories, and total cost of ownership. The findings highlight key innovations in battery energy density, lightweighting, and powertrain optimization, demonstrating the growing viability of BEVs and their projected economic competitiveness with conventional vehicles by 2050. This work delivers actionable insights for policymakers and industry stakeholders, underscoring the transformative potential of vehicle electrification in achieving sustainable transportation goals.

Islam, Ehsan Sabri (ORCID:0000000200220180)↗
DOE OSTI2020

Power at Sea: Use of Wave Energy Converters for Powering Offshore Oil and Gas Operations

New innovative services and goods based on artificial intelligence, next-generation robotics, autonomy, digitization, and electrification are taking root in the ocean economy. More typical competitive forces, such as value enhancement and safety improvement, are also present, as suppliers constantly strive to improve their competitive positioning. Concurrently, the Oil and Gas sector is experiencing mounting pressure to decrease its operational carbon emissions, forcing efforts to reduce or eliminate liquid fuel consumption offshore. Companies in the ocean economy are having to react to this combination of macro- and micro-level drivers and innovate at an ever more rapid pace. However, before many of these new capabilities can be implemented, new, clean, reliable power sources are needed, especially as liquid fuel grows increasingly out of favor. For many of these loads—both old and new and ranging from watts to megawatts—wave energy systems provide the best solution for remote power generation. As such, research, development and demonstration activities are underway to prove wave energy's ability to provide reliable, consistent energy supplies for certain offshore Oil and Gas activities, paving the way for near term commercialization. Furthermore, this paper outlines these drivers, competitive reaction to them, and why and how wave energy can be a preferable choice for power at sea.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Results of Application Demonstration of Autonomous Offshore Power System Supporting Multiple Mobile and Static Assets

Over the last decade, several technology trends have dominated the innovation cycle within the terrestrial economy. Electrification, cloud computing, decarbonization, digitization, and autonomy are representative examples of macro trends that have had a rapid and fundamental impact; an impact felt not only in user-facing technologies, such as electric vehicles and software-as-a-service, but also in the infrastructure required to deliver those technologies. However, the scale of the impact and rollout has not been felt equally between the terrestrial and ocean economies. Here, the innovation cycle in the ocean economy is significantly slower. What accounts for the difference and are there solutions to this issue?

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Potential Impacts of High-Octane Fuel Introduction in a Naturally Aspirated, Port Fuel-Injected Legacy Vehicle

In recent years there has been an increased interest in raising the octane level of gasoline to enable higher compression ratios (CR) in spark-ignition engines to improve vehicle fuel efficiency. A number of studies have examined opportunities to increase efficiency in future vehicles, but potential impacts on the legacy fleet have not received as much attention. In this study, our effort focused on experimental studies on an engine using high-octane fuels without changing the engine’s CR. Spark timing was advanced until maximum torque was reached or knock was encountered for each engine condition, using each individual fuel to maximize engine efficiency. Knock-limited conditions occurred as the output brake mean effective pressure (BMEP) neared the maximum attainable output at a given engine speed. Increasing research octane numbers generally enabled knock-free operation under a greater number of operating conditions. Vehicle modeling using Autonomie was used to project vehicle energy use, fuel economy, and tailpipe CO 2 emissions for the Urban Dynamometer Driving Schedule (UDDS), the Highway Fuel Economy Test (HWFET), and the US06 cycle. Results show that decreases in energy consumption of up to 2% for a small SUV are possible through the use of a 97 RON fuel compared to a baseline using 91 RON fuel, provided that the formulation of the fuel does not cause unanticipated operational issues such as lower maximum BMEP. Greater improvements using high-octane fuels are possible if the CR is increased, but there is no opportunity to increase the CR in legacy vehicles. Thus, these vehicles realize an improvement from increased octane rating in accordance with their ability to spark advance to take advantage of a fuel with a higher octane rating. For the modeled vehicle, improvements of up to 2% in volumetric fuel economy may be possible through the use of a 97 RON fuel with the largest gains expected on the US06 cycle. Fuel economy impacts are strongly coupled to the heating value of the fuels in addition to changes in engine efficiency. Similarly, decreases in tailpipe CO 2 emissions are also achievable. However, simultaneous improvements in energy consumption, fuel economy, and tailpipe CO 2 emissions are not guaranteed and are dependent upon fuel formulation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Performance of DSRC V2V Communication Networks in an Autonomous Semi-Truck Platoon Application

Autonomy for multiple trucks to drive in a fixedheadway platoon formation is achieved by adding precision GPS and V2V communications to a conventional adaptive cruise control (ACC) system. The performance of the Cooperative ACC (CACC) system depends heavily on the reliability of the underlying V2V communications network. Using data recorded on precision-instrumented trucks at both ACM and NCAT test tracks, we provide an understanding of various effects on V2V network performance: Occlusions - non-line-of-sight (NLOS) between the Tx and Rx antenna may cause network signal loss. Rain - water droplets in the air may cause network signal degradation. Antenna position - antennas at higher elevation may have less ground clutter to deal with. RF interference - interference may cause network packet loss. GPS outage - outages caused by tree cover, tunnels, etc. may result in degraded performance. Road curvature - curves may affect antenna diversity. Road grade - antenna may have limited vertical coverage. Our results, which include multiple plots and graphs and their analysis, build on those reported by others and could be of interest to researchers, practitioners, and end-users in the broader autonomous-connected vehicle community.

V2V communications, GPS, truck platoon, semi-auton↗
DOE OSTI2022

Evaluating Class 6 Delivery Truck Fuel Economy and Emissions Using Vehicle System Simulations for Conventional and Hybrid Powertrains and Co-Optima Fuel Blends

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance. Comparisons were made between ultralow-sulfur diesel and a blend of 25% hexyl hexanoate with diesel. Model validation data were informed by 2019 model year Cummins ISB 6.7 L diesel engine maps and transient validation data in a pre-production hybrid configuration and a direct dyno coupled configuration with diesel fuel and a blend of 25% hexyl hexanoate with diesel.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Real-Time Hardware-in-the-Loop Testbed to Evaluate FLISR Implemented with OpenFMB

With the increasing complexity of the distribution smart grid architecture, algorithms such as the fault location, isolation, and service restoration (FLISR) scheme rely on robust communications that are resilient to natural and man-made adverse conditions and exhibit robustness. Existing communications infrastructure for information exchange are centralized at the distribution management system, with very little autonomy or intelligence at the grid-edge. As a first step towards achieving grid-edge self-healing, this paper aims to bridge this shortcoming by implementing a centrally coordinated rules-based FLISR scheme and integrating it with Open Field Message Bus (OpenFMB), which is a flexible publish-subscribe architecture with the potential to enable point-to-multipoint communications and is more robust and resilient to natural and man-made adverse conditions. A proof of concept is developed to validate the centrally coordinated FLISR and OpenFMB mounted on an SEL-3360 computer that interacts with a simple feeder network of five SEL-651R relays, an SEL-3530 RTAC, and a hardware-in-the-loop testbed. Results demonstrate the efficacy of this approach in enabling direct, low-latency information exchange. OpenFMB's publish-subscribe data model also opens new ways to enable grid-edge interoperability among devices of different vendors interacting with different protocols.

Sundararajan, Aditya↗
DOE OSTI2020

Robotic Mapping and Monitoring of Nuclear Infrastructure

Routine inspection of nuclear infrastructure is currently expensive and slow. To remedy this the Applied Research Center (ARC) at Florida International University (FIU) is developing a field robot capable of gathering valuable data quickly, safely, and cheaply. Motivation: Nuclear infrastructure should be inspected routinely to ensure early detection of problems. This process is expensive, hazardous, and slow. Objective: Develop a platform capable of surveying nuclear infrastructure autonomously. Discussion: The quality of the captured data depends on the success of every component of the robot. Good sensors, hardware, localization, data collection, and autonomy are required. Conclusion: This is a promising approach for surveying nuclear infrastructure. The captured data is rich with information and can be evaluated by both people and algorithms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Performance Evaluation of Augmented Teleoperation of Contact Manipulation Tasks

At Argonne National Laboratory, an enhanced telerobotic concept has been suggested by providing augmented virtual fixtures for precise and dexterous manipulation. The proposed technology incorporated a human-robot interface that can assist personnel on the processes of Deactivation and Decommissioning in sites of high radiation. It has been implemented on a dual-arm robot system, known as Baxter, by integrating the Robotic Operating System (ROS) with 3D sensors and visual-haptic operator interface. However, what remained before its practical utilization is the capability for precisely placing the virtual fixtures. To this end, the objectives involved camera calibration, which required hardware fabrication and setup, as well as modification and implementation of ROS. The goal of this Research and Development is to develop an augmented-reality- based operator interface for human-inclusive, intelligent, and autonomous robotic system for the Deactivation and Decommissioning (D and D) of radioactive sites. The objectives are to develop: Collaborative Robot; Multi-modal Mixed-Reality Human-Robot Interface; Intelligent and Autonomous Behaviors. In order to achieve this, Baxter's Head-Kinect camera and Left-Hand camera need to be calibrated to overlap the real environment with the simulated environment. Camera calibration, which is crucial for precisely placing the virtual fixtures, was successful after running the simulations. The real and simulated environments overlapped, permitting the utilization of augmented teleoperation and the dexterous manipulation of Baxter for D and D applications in nuclear sites. Future steps: Performance evaluation of augmented teleoperation of contact manipulation tasks: Multiple-Camera 3D Reconstruction and Automation. Oculus Interface: Augmented reality and machine learning for enhanced telerobotic operation (Augmented Tele-autonomy): Machine-learning techniques for complex and flexible autonomous robotic behaviors. Interactive remote operation of robotic systems. Mesh cutting with simulation and real robot.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗