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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

TEAMER: Electrically Engaged Undulation System for Unmanned Underwater Vehicles

This TEAMER RFTS 1 (Request for Technical Support) project supported the flume tank testing of a long range, high endurance unmanned underwater vehicle (UUV) to monitor maritime space. Today, battery-powered remotely operated vehicles (ROVs) lack the duration to make persistent, wide-area data collection possible.The proposed solution, an Electrically Engaged UnduLation (EEL) drone, can sustain missions for longer duration through hydrodynamic energy harvesting. Power is provisioned via the piezoelectric effect, a material-led phenomenon that converts applied stress into electricity. The EEL subsystems include power, propulsion, navigation, ballast, telemetry, and instrumentation. By mimicking the gait of aquatic eels, EEL can counter currents during maneuvering and level-flight. The identified opportunity is in the future capability of extreme endurance UUVs in swarms. The specific goal for the EEL development is to expand the spatio-temporal coverage of the existing ocean observation mission by overcoming significant challenges of autonomous robotics. Some of the challenges presented include novel compliant mechanism for robust actuation, bio-inspired design to emulate efficient locomotion, smart material-based energy harvesting for sustained power, and swarming architecture through enabled autonomy.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Co-Design of Marine Energy Converters for Autonomous Underwater Vehicle Docking and Recharging - Software and Data

Software and testing data from the OH Hinsdale Wave lab for DOE-funded project on Co-Design of Marine Energy Converters for Autonomous Underwater Vehicle Docking and Recharging. This project will perform foundational research and testing to accelerate the sector-wide development and deployment of marine energy converters to provide Power-At-Sea. Specifically, we seek to overcome known challenges and knowledge gaps for the successful co-design of coupled Wave Energy Converter (WEC)-Autonomous Underwater Vehicles (AUV) systems; systems designed and tested for WEC array system health and environmental monitoring applications. This project brings together an experienced, multi-institution, and multi-disciplinary team to focus on the co-design of marine energy (ME) technologies and AUV docking systems, including multi-body hydrodynamic modeling, active control, autonomy, and hardware interfaces necessary to enable new WEC-focused understanding, and allow for robust and ubiquitous AUV docking and recharging in real-world conditions.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Detailed Simulation Datasets Quantifying U.S. DOE VTO/HFTO R&D Benefits Across Light- to Heavy-Duty Vehicles

For more than 20 years, Argonne National Laboratory’s Vehicle & Mobility Systems Department has assessed how R&D investments by the U.S. Department of Energy’s Transportation Technologies Office and Alternative Fuels and Feedstocks Office affect vehicle energy use and cost. The analyses are performed using Autonomie, Argonne’s full-vehicle simulation tool for energy consumption, performance, and cost. The study covers five time frames ranging from present day through 2050, with more than 30 vehicle classes and applications (10 light duty and >20 medium and heavy duty), as well as six powertrain configurations (conventional, start-stop, hybrid electric vehicle, plug-in hybrid electric vehicle, battery-electric vehicle, and fuel cell electric vehicle) and five fuels (gasoline, diesel, natural gas, hydrogen, and electricity). Low and high technology uncertainty scenarios have been considered to capture a realistic range of outcomes. The resulting datasets include the assumptions used (i.e., efficiency, $/kWh), vehicle-level data (power, energy, weight, and cost), and outputs such as energy consumption, manufacturer’s suggested retail price, and total cost of ownership. These data are critical to stakeholders working in transportation, technology assessment, and long-term R&D planning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Cleated Print Surface for Fused Deposition Modeling

Fused Deposition Modeling (FDM) has become popular among Additive Manufacturing technologies due to its speed, geometric scalability, and low cost; however, the primitive nature of the FDM build surface fundamentally limits the utility of FDM in terms of reliability, autonomy, and material selection. Currently, FDM relies on adhesive forces between the first layer of a print and the build surface; depending on the materials involved, this adhesive bond may or may not be reliable. Thermal contraction between the build plate and build materials can break that bond, which causes warpage and delamination of the part from the build surface and subsequent failure of the part. Furthermore, with each print, the user must use tools or manual maneuvering to separate the printed part from the build surface as well as retexture or replace the used build surface. In this paper, we present a novel build platform that allows for a mechanical bond between the print and build surface by using dovetail-shaped features. The first layer of the print flows into the features and becomes mechanically captivated by the build platform. Once the print is completed, the platform is rolled or flexed open to release the part from the mechanical bond. This design not only lowers the risk of delamination during printing but also eliminates the need for a user to reset or replace the build surface between print jobs. The effectiveness of each geometry was determined by measuring the distance at the pinch point compared to the distance that the extrusion filled below the pinch point. The captivation ratio was measured to compare the different geometries tested and determine which direction of extrusion creates a better ratio.

42 ENGINEERING↗
DOE OSTI2014

The Cost of Jointness: Insights from Environmental Monitoring Systems in Low-Earth Orbit

This report summarizes the results of doctoral research that explored the cost impact of acquiring complex government systems jointly. The report begins by reviewing recent evidence that suggests that joint programs experience greater cost growth than non-joint programs. It continues by proposing an alternative approach for studying cost growth on government acquisition programs and demonstrates the utility of this approach by applying it to study the cost of jointness on three past programs that developed environmental monitoring systems for low-Earth orbit. Ultimately, the report concludes that joint programs' costs grow when the collaborating government agencies take action to retain or regain their autonomy. The report provides detailed qualitative and quantitative data in support of this conclusion and generalizes its findings to other joint programs that were not explicitly studied here. Finally, it concludes by presenting a quantitative model that assesses the cost impacts of jointness and by demonstrating how government agencies can more effectively architect joint programs in the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Vehicle Modeling for use in the CAFE model: Process description and modeling assumptions

The objective of this project is to develop and demonstrate a process that, at a minimum, provides more robust information that can be used to calibrate inputs applicable under the CAFE model’s existing structure. The project will be more fully successful if a process can be developed that minimizes the need for decision trees and replaces the synergy factors by inputs provided directly from a vehicle simulation tool. The report provides a description of the process that was developed by Argonne National Laboratory and implemented in Autonomie.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Summary of FY17 ParaChoice Accomplishments

As part of analysis support for FCTO, Sandia assesses the factors that influence the future of FCEVs and Hydrogen in the US vehicle fleet. Using ParaChoice, we model competition between FCEVs, conventional vehicles, and other alternative vehicle technologies in order to understand the drivers and sensitivities of adoption of FCEVs. ParaChoice leverages existing tools such as Autonomie (Moawad et al., 2016), AEO (U.S. Energy Information Administration, 2016), and the Macro System Model (Ruth et al., 2009) in order to synthesize a complete picture of the co-evolution of vehicle technology development, energy price evolution, and hydrogen production and pricing, with consumer demand for vehicles and fuel. We then assess impacts of FCEV market penetration and hydrogen use on green- house gas (GHG) emissions and petroleum consumption, providing context for the role of policy, technology development, infrastructure, and consumer behavior on the vehicle and fuel mix through parametric and sensitivity analyses.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

GATE: Energy Efficient Vehicles for Sustainable Mobility-Project TI022- FinalReport

Unique opportunity for industry to engage in original, highly leveraged precompetitive research in automotive and transportation systems, with focus on advanced propulsion systems; fuel economy; vehicle safety, connectivity and autonomy; and advanced driver assistance systems Additional benefits: prepare graduate students for future careers in automotive industry, reaching undergraduate students through capstone design and other project activities, focused recruitment events

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

CASC Newsletter Vol. 4 (Jan 2018)

The Sidney Fernbach Postdoctoral Fellowship in the Computing Sciences was established in 2012 to attract top new researchers into the Computation Directorate. Similar to LLNL’s Lawrence Fellowship, it offers outstanding new scientists the opportunity to establish their own research directions with a great deal of autonomy. The Lawrence Fellowship is open to all technical disciplines at the Laboratory and is awarded to several candidates each year. The Fernbach, on the other hand, focuses specifically on disciplines in the computing sciences: applied mathematics, computer science, computational science, and data science. It usually supports one fellow at a time for a two-year term.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

SNL HPC 2018 [Slides]

A new arms race is emerging among global powers: the hypersonic weapon. Hypersonics are flight vehicles that travel at Mach 5 (five times the speed of sound) or faster. They can cruise in the atmosphere, unlike traditional exo-atmospheric ballistic missiles, allowing stealth and maneuverability during midflight. Faster, lower, and stealthier means the missiles can better evade adversary defense systems. The U.S. has experimented with hypersonics for years, but current investments by Russia and China into their own offensive hypersonic systems may render U.S. missile defense systems ineffective. For the U.S. to avoid obsolescence in this strategically significant technology arena, hypersonics—combined with autonomy—needs to be a force multiplier.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Gasoline Engine and Fuels Offering Reduced fuel Consumption and Emissions (GEFORCE)

The GEFORCE project resulted from a collaborative proposal submitted to a U.S. DOE funding opportunity announcement. The CRADA reported herein was put in place to support the GEFORCE project. The project objective was to establish key engine technologies and fuel characteristics that enable very high fuel efficiency with very low emissions in future vehicles. A matrix of study fuels was designed and produced to support engine experiments in an advanced engine. The advanced engine was constructed and prepared for operation in an engine test cell at a 3rd party laboratory. ORNL conducted engine experiments using a 2.0 LTG engine and used the resulting data to estimatefuel economy values for a mid-size sedan using a vehicle model established in Autonomie. The projected fuel economy trends versus driving schedule were consistent with those identified in a previous projectconducted in partnership with the Coordinating Research Council (CRC), AVFL-20. Additional vehicle modeling is anticipated when data are available from the advanced engine.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Comparison of Distributive Consensus Algorithms for AnomalyDetection on the Power-Grid

As an increasing number of devices in the power-grid rely on high-precision clocks to measure electrical properties and time stamp data, GPS receivers have become a vulnerability on the power-grid. GPS spoofing attacks, in which a fake signal is transmitted, can cause sensor measurement errors that can misinform protective equipment and grid operators for both the transmission and distribution grid. The technology being developed to secure precision clocks in the transmission grid are not appropriate for the distribution grid. Thus, there is a need to developed anomaly detection algorithms that are suitable for the hardware available on the distribution grid. Traditionally, a distributed detection framework is comprised of spatially distributed nodes which acquire observations about a quantity of interest and sends the data to the fusion center, where a global decision is made. Instead the distribution grid has low-power devices, such as smart inverters and microPMUs, that could be used to perform highly parallelized calculations. Having on node calculations is beneficial since it is more network and computation efficient, as the more calculations can be performed where the data is being captured instead of communicating across a slow network to a centralized fusion center. Instead, we could employ an alternate peer-to-peer type of information exchange on the distribution grid that can still reach a global decision. A decentralized approach to anomaly detection makes efficient use of the computational and network bandwidth that exists, and it also lacks the single point of failure of a centralized approach. Thus, a decentralized local information exchange and/or inference is preferred. Lastly, the unreliability of the distribution grid network connections and potential noise or error in the measurements must be considered. In order to produce an effective detection tool, a Byzantine-fault tolerant and asynchronous algorithm must be developed. Thus, the first phase of our project is to develop a distributed, decentralized, asynchronous, Byzantine-fault tolerant, collaborative autonomy-based anomaly detection algorithm to collectively analyze clusters of data for signs of a malicious attack.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Direct Injection 4.3L Propane Engine Research Development and Testing (Final Technical Report)

The objective of this project is to develop a propane-fueled direct injection (DI) engine and emissions control system based on a current production General Motors 4.3 L spark-ignited, DI V6 engine. The team will integrate this engine and aftertreatment system into a package delivery vehicle, and demonstrate a 20% greenhouse gas (GHG) improvement over the baseline gasoline 6.0 L engine version of the vehicle while meeting U.S. Environmental Protection Agency Phase 2 medium-duty/heavy-duty and GHG emission regulations. Engine dynamometer, chassis dynamometer, and in-use fleet test data will be incorporated into the required Autonomie simulations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Optimizing Microgrid Energy Delivery Under High Uncertainty

One of the largest transitions in the power system today is the shift to a more sustainable and resilient power system. This is being driven by public opinion, changes in regulatory policies, and advancements in smart grid technologies. The most noticeable changes taking place is the integration of distributed energy sources (DERs); this study uses the term DER in the most general way as a resource that can be manipulated to alter energy delivery and flow in the transmission and distribution networks. Also, here it is preferred to focus on energy as the true need while power is a function of the equipment rating. As such, wind and solar, demand that can be manipulated, electric vehicles, electric energy storage, thermal storage, and storage in water system are all considered DERs. These additions to the distribution system are evolving the operation of distribution feeders into microgrids- communication, computing, and control-enabled resources that produce, transport, and utilize energy in a manner that provides cost, reliability, and resilience benefits. As this evolution progresses, the planning and operational management (scheduling and control) must explicitly include the consideration of risk. The management of system risk is currently in the purview of the utility and will likely remain so in the future. However, as each microgrid, as well as federation of microgrids, sees autonomy in order to provide maximum benefits to their constituents, they must assume responsibility to manage their internal risk. The primary scope of this study is the scheduling of resources in a distribution feeder(s) operating as microgrids. The study explores a distribution algorithm to develop the transactive schedule for the DERs, to minimize cost and risk over a time horizon, and an initial laboratory-scale to conduct implementation on distributed hardware. Results from case studies are presented that show that solutions derived by the distributed algorithm are valid. This study also discusses the continuing work on the expansion of: 1) the distributed algorithm from a deterministic to stochastic optimization formulation, and 2) implementation of the distributed algorithm into real-time simulation within the Power System laboratory at New Mexico State University (NMSU) and expanding to the Southwest Technology Development Institute located at NMSU where actual solar, energy storage, and demand response resources are installed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

BrainSLAM

This research aims to develop brain-inspired solutions for reliable and adaptive autonomous navigation in systems that have limited internal and external sensors and may not have access to reliable GPS information. The algorithms investigated and developed by this project was performed in the context of Sandas A4H (autonomy for hypersonics) mission campaign. These algorithms were additionally explored with respect to their suitability for implementation on emerging neuromorphic computing hardware technology. This project is premised on the hypothesis that brain-inspired SLAM (simultaneous localization and mapping) algorithms may provide an energy-efficient, context-flexible approach to robust sensor-based, real-time navigation.

42 ENGINEERING↗
DOE OSTI2019

Explaining jurisdictional compliance with California’s top-down streamlined solar permitting law (AB 2188)

In the U.S., the process by which residential rooftop solar photovoltaic (PV) system installations are permitted and inspected by an “authority having jurisdiction” (AHJ) varies across AHJs. As the U.S. has roughly 23,000 AHJs with varying degrees of local autonomy, improving the cross-jurisdictional consistency of permitting and inspection is not a straightforward task. One promising approach is a “top-down” streamlined solar permitting (SSP) mandate by U.S. States to their AHJs. This study set out to understand the factors associated with the likelihood that an AHJ either did or did not comply with California’s top-down streamlined solar permitting law, AB2188, and then to consider how these factors might be relevant to the future prospects of top-down SSP outside of California. This report provides background material on AB2188 and tests five hypotheses about the factors that affect the likelihood that an AHJ will comply or not comply with AB2188, as developed from the policy diffusion literature and background knowledge on AB2188 and its implementation.

14 SOLAR ENERGY↗
DOE OSTI2019

Future SDN-HPON Control Plane Architecture and Protocol for On-Demand Terabit End-to-End Extreme-Scale Science Applications

The UC Davis team conducted architecture, algorithm and experimental studies for next generation ultra-high-bandwidth optical networks in support of extreme-scale science applications. In particular, over the course of this 3-year project, the UC Davis team achieved the following main accomplishments: Designed a network architecture for automated multi-domain service provisioning: Designed information exchange schemes between autonomous systems (domains) Designed application programming interfaces to orchestrate resource reservation in data centers, high performance computation facilities, and communication networks belonging to different autonomous systems Experimentally assessed the multi-domain network architecture in a distributed field trial set-up connecting premises in three continents Designed a broker-based orchestrated multi-domain optical networking framework supporting observe-analyze-act cycle based cognitive inter-domain service provisioning: Designed an inter-domain operation mechanism, e.g., topology abstraction, for the broker plane and domain managers to collaboratively accomplish inter-domain service provisioning while respecting the autonomy of each administrative domain Designed an alien wavelength monitoring scheme and an artificial neural network based optical signal-to-noise ratio estimator for quality-of-transmission aware inter-domain service provisioning Developed a deep neural network based multi-domain traffic predictor and a cognitive routing and spectrum assignment algorithm to realize knowledge-based autonomous traffic engineering in multi-domain networks Implemented an optical signal-to-noise ratio estimator and traffic predictor with Google’s Tensor flow and assessed their performance using experimental and synthetic data Demonstrated the benefits of the proposed cognitive schemes with experiments ona two-domain elastic optical network testbed and evaluations on a six-domain simulation framework Built a two-domain software-defined networking control plane testbed using the ONOS platform and demonstrated the workflow of broker and domain manager cooperation, including hierarchical performance monitoring, topology abstraction and cognitive resource allocation. Designed self-learning cognitive service provisioning schemes using advanced machine learning technologies: Designed a self-taught anomaly detection framework for optical networks, including an unsupervised data clustering module for pattern recognition, a supervised data regression and classification module for online anomaly detection, and the system operation principle Experimentally validated the effectiveness of the self-taught anomaly detection framework with various failure/anomaly scenarios. Designed a self-learning autonomic routing, modulation and spectrum assignment (RMSA) provisioning framework for elastic optical networks with deep reinforcement learning. Designed effective modeling and training mechanisms for the self-learning RMSA framework Conducted extensive numerical simulations with various traffic patterns and topologies to verify the advantage of the self-learning RMSA framework.

42 ENGINEERING↗
DOE OSTI2020

Integrated Military Systems

The Integrated Military Systems (IMS) Center at Sandia National Laboratories is a technical systems integrator of high-risk, high-impact systems. It provides cutting-edge technologies, subsystems, solutions, and products that provide a competitive advantage at every point of engagement. Building on more than six decades of experience, IMS seeks to pursue and provide solutions to the most challenging national security issues. We leverage technical capabilities from the Laboratories' core mission and innovatively apply technology to defense problems. IMS' diverse capabilities produce revolutionary technologies in the areas such as precision strike and defense, autonomy, NG&C, directed energy, signal processing/ATR, lethality and threat assessment, and systems engineering. Our talented engineers and staff take a problem from initial design all the way through testing and fielding.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗