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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
DOE OSTI2020

Observation of Reactor Antineutrinos with a Rapidly Deployable Surface-Level Detector

We deploy a small 80 kg antineutrino detector, called MiniCHANDLER, based on a solid plastic scintillator, for nearly three months at a distance of 25 m from a 2.9 GW thermal-power-reactor core at the North Anna Nuclear Generating Station. We report the detection of an antineutrino signal resulting from inverse beta decay at 5.5σ significance with no overburden and minimal shielding. This result also demonstrates that three-dimensional segmentation can be used to significantly improve the signal-to-noise ratio, in this case by a factor of 4. Finally, in addition, this measurement represents an observation of a positron spectrum in a small surface-deployed detector; this observation of reactor antineutrinos is achieved with a mobile neutrino detector mounted in an ordinary small trailer.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A Simulation Framework to Support the Deployment of Vanadium Redox Flow Batteries

This work presents a simulation framework to support Vanadium Redox Flow Batteries deployment. First, an electrical equivalent model of a commercial three-stack, 20 kW VRFB is implemented to capture the battery dynamics. Next, a topology of a power electronics-based solution to integrate a VRFB is introduced, and the effectiveness of the control system is evaluated through battery charging and discharging operation under varying conditions. The results provide insights into power and voltage levels, demonstrating that the series-connected architecture can alleviate the voltage boost on the interface power electronics converter. Additionally, efficiency and temperature-critical factors for VRFB system deployment-are also analyzed.

Rezende Da Costa Reis Kimpara, Renata [ORNL] (ORCI↗
DOE OSTI2022

Deploying Traffic Smoothing Cruise Controllers Learned from Trajectory Data

Autonomous vehicle-based traffic smoothing con- trollers are often not transferred to real-world use due to challenges in calibrating many-agent traffic simulators. We show a pipeline to sidestep such calibration issues by collecting trajectory data and learning controllers directly from trajectory data that are then deployed zero-shot onto the highway. We construct a dataset of 772.3 kilometers of recorded drives on the I-24. We then construct a simple simulator using the recorded drives as the lead vehicle in front of a simulated platoon consisting of one autonomous vehicle and five human followers. Using policy-gradient methods with an asymmetric critic to learn the controller, we show that we are able to improve average MPG by 11% in simulation on congested trajectories. We deploy this controller to a mixed platoon of 4 autonomous Toyota RAV-4’s and 7 human drivers in a validation experiment and demonstrate that the expected time-gap of the controller is maintained in the real world test. Finally, we release the driving dataset [1], the simulator, and the trained controller at https://github.com/nathanlct/trajectory-training-icra.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Defining a Use Case for ADMS Testbed: Data Quality Requirements for ADMS Deployment

Advanced distribution management systems (ADMS) provide a suite of tools to meet the needs of a modern grid: increased reliability and power quality, improved resiliency and security, reduced costs, and enhanced customer participation. A critical challenge that utilities face with adoption of ADMS is the quality of models and data that the ADMS uses for making control decisions. Data quality has a two-fold impact on ADMS adoption: 1. Data quality improvement might constitute up to 25% of ADMS deployment costs. 2. The accuracy of data and models used by the ADMS affects the utility's ability to meet its operational objectives. Thus, quantifying the data quality requirements and its impact on performance is critical to reducing the overall cost of deployment, enabling increased adoption and ensuring that the ADMS performs as specified. This paper offers the motivation, methodology, and evaluation strategy to fill this critical gap.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

ADDS-EVS: An agent-based deployment decision-support system for electric vehicle services

Rapid and sustainable development of the electric vehicle (EV) industry places the requirement for the plan of EV deployment. For public EV, existing models mainly focus on the charging facility design and fail to capture the multi-modal scenarios. In this work, we develop an agent-based decision-support system for multi-modal electric transits to locate the optimal combinations of key parameters, including the fleet size, the transit schedule, the charging facility design, and the routing strategy. We demonstrate the utilities of our system by simulating public EV services deployed to serve travel needs related to a transportation hub in New York City. To support the decision of the fleet size, we summarize system-level performances including the total satisfied demand, passengers' waiting time, vehicle idling time. The spatial and temporal patterns are extracted to serve a deeper understanding of system dynamics and service quality. Finally, we investigate the interaction between the fleet size design and the routing strategy. The results suggest a necessity of integrating the operation strategies into the planning phase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Model-Based Framework to Optimize Charger Station Deployment for Battery Electric Vehicles

The development of battery electric vehicles (BEVs) is accelerating due to their environmental advantages over gasoline and diesel-powered vehicles, including a decrease in air pollution and an increase in energy efficiency. The deployment of charging infrastructure will need to increase to keep pace with demand, especially for large commercial vehicles for which few public chargers currently exist. In this paper, a new flexible framework is proposed for optimizing the placement of charging stations for BEVs, within which different physical models and optimization techniques may be used. Furthermore, a set of metrics is suggested to help enforce complex constraints and facilitate direct comparison between different optimization techniques. Unlike many existing charger placement techniques, the proposed method directly considers the historical driving patterns on a vehicle-by-vehicle basis, using transparent models to assess impacts of candidate charger placements, thus improving the explainability of the results. In the developed framework, modeled BEVs are first generated along the road network to mimic historical traffic data and are simulated traveling along a given route according to a simplified vehicle model. During the simulation, the charger placement problem is initially relaxed to allow vehicles to charge at any node along the road network, and vehicle states are tracked to assess areas of high charging demand. Charging stations are then placed based on the results of the relaxed simulation, and suggested placements are evaluated via road network simulation with fixed charger locations. This proposed framework is applied to a sample problem of placing charging stations along five major highway corridors for Class 8 over-the-road electric trucks. A novel mixed integer programming (MIP) formulation is proposed to optimize charger placements based upon the expected charging demand. Constraints were imposed on the final placement results to limit expected wait times at each station and ensure a minimum threshold of trucking routes are viable for BEVs. The results demonstrate the flexibility and potential effectiveness of the developed model-based framework for scalable charger station deployment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Biomass market dynamics supporting the large‐scale deployment of high‐octane fuel production in the United States

Abstract US Department of Energy research aimed at co‐optimizing fuels and engine performance identified several bioblendstocks that can improve fuel economy including an aromatic‐rich hydrocarbon derived from woody biomass. This work supports an analysis of its large‐scale deployment implying a production target of approximately 15 billion liters of bioblendstock for the supply of 57 billion liters of high‐octane fuel by 2050. It simulates potential transition pathways to lignocellulosic feedstock market structures capable of supplying a mature biorefining industry at this scale. In the present absence of biorefineries, transitions are modeled via nonbiofuel feedstock markets, so‐called companion markets. The resource distribution across several demand industries is simulated to determine biomass availability and price dynamics over time. Results indicate that the wood supply base is mainly influenced by traditional markets including housing and pulp and paper. The selected companion market of wood pellet combustion for heat and electricity generation is found to positively stimulate biomass mobilization, especially in the initial absence of biorefineries. Eventually, biorefineries are found to be able to out‐compete the companion market. As such, they directly benefit from the processing (i.e., pelleting) capacity established to produce commodity‐type intermediates for the companion market. We conclude that the amount of bioblendstock produced is directly related to the size of the companion market (and its pelleting capacity). An initially larger companion market generates up to 20 million dry tonnes of additional feedstock, equivalent to 27 commercial‐scale biorefineries, or an additional production of 5 billion liters by 2050. Distinguishing between industry‐specific feedstock preferences based on average biomass quality characteristics, this analysis goes beyond past research efforts that assume automatic fungibility across different feedstocks. Improving engine performance is a key driver for the promotion of low‐carbon fuels derived from bioblendstocks. This analysis portrays feedstock market transition pathways for their large‐scale deployment.

09 BIOMASS FUELS↗
DOE OSTI2018

Breeding progress and preparedness for mass‐scale deployment of perennial lignocellulosic biomass crops switchgrass, miscanthus, willow and poplar

Abstract Genetic improvement through breeding is one of the key approaches to increasing biomass supply. This paper documents the breeding progress to date for four perennial biomass crops (PBCs) that have high output–input energy ratios: namely Panicum virgatum (switchgrass), species of the genera Miscanthus (miscanthus), Salix (willow) and Populus (poplar). For each crop, we report on the size of germplasm collections, the efforts to date to phenotype and genotype, the diversity available for breeding and on the scale of breeding work as indicated by number of attempted crosses. We also report on the development of faster and more precise breeding using molecular breeding techniques. Poplar is the model tree for genetic studies and is furthest ahead in terms of biological knowledge and genetic resources. Linkage maps, transgenesis and genome editing methods are now being used in commercially focused poplar breeding. These are in development in switchgrass, miscanthus and willow generating large genetic and phenotypic data sets requiring concomitant efforts in informatics to create summaries that can be accessed and used by practical breeders. Cultivars of switchgrass and miscanthus can be seed‐based synthetic populations, semihybrids or clones. Willow and poplar cultivars are commercially deployed as clones. At local and regional level, the most advanced cultivars in each crop are at technology readiness levels which could be scaled to planting rates of thousands of hectares per year in about 5 years with existing commercial developers. Investment in further development of better cultivars is subject to current market failure and the long breeding cycles. We conclude that sustained public investment in breeding plays a key role in delivering future mass‐scale deployment of PBCs.

09 BIOMASS FUELS↗
DOE OSTI2023

Approaches for Synthesis and Deployment of Controller Models on Automated Vehicles for Car-following in Mixed Autonomy

This paper describes the software design patterns and vehicle interfaces that were employed to transition vehicle controllers from simulation environments to open-road field experiments. The approach relies on a life cycle that utilizes model-based design and code generation, along with agile software development, and both software and hardware-in-the-loop testing, with additional safety margins. Autonomous designs should consider the dynamics of mixed autonomy in traffic to safely operate among humans. The software that provides a vehicle’s behavior intelligence is often developed through simulation, which may have a mismatch between dynamics, or as a result of a reinforcement learning workflow, which may be a black box with challenges to analyze. In each of these cases, it is important to have research interfaces that provide strongly typed data streams accessible to researchers who are not software experts while continuing to satisfy safety and liveness constraints. This paper describes how we design the hardware platform interfaces and software design process for a mixed autonomy traffic experiment with a leader-follower scenario. Controller synthesis for these vehicles requires clearly articulated vehicle interfaces and software design patterns for successful onboard deployment. Testing strategies for such controllers are also described before algorithms are transitioned to full-scale field experiments with safety operators for the vehicles. Testing strategies include software-in-the-loop simulation testing, hardware-in-the-loop simulation, ghost-car testing, and read-only testing in live traffic. With our approach, we were not only able to validate our controller synthesized in scripts and simulation, but also able to scale deployment to multiple vehicles.

Bhadani, Rahul↗
DOE OSTI2026

Pioneer WEC v1 Ocean Deployment

There are seven zip files of data pertaining to the Pioneer WEC v1 ocean deployment.(1-6) Pioneer multiple sensor data "Month Year".zip: contains monthly data from the majority of onboard instruments (e.g., electrical power, mechanical motion, etc.)(7) Pioneer vibration sensor data full 6 months.zip: contains data from the vibration sensor instrument for the full 6 month deployment

Ocean sensing↗
DOE OSTI2022

Optimization Models For Drone Deployment

Model that supports drone deployment. Analysis on speed, package weight, energy consumption, # of drones, and battery replacements. This software developed tools for drone deployment optimization for direct delivery by introducing a new model that presents new insights addressing real-life issues. Specifically, this developed a new mixed-integer programming model with both time windows and battery replacements.

Roni, MohammadS↗
DOE OSTI2025

Deployed quantum link characterization via Bayesian ancilla-assisted process tomography

The development of large-scale quantum networks requires reliable quantum channels, the quality of which can be quantified by the framework of quantum process tomography. Here, in this work, we leverage ancilla-assisted process tomography (AAPT) and Bayesian inference to probe a 1.6 km deployed fiber-optic link. We send one of the two polarization-entangled photons at Alice in one building to Bob in another, exploiting the local qubit as an ancilla system to characterize the corresponding quantum channel. Monitoring over a 24 h period returns a steady process fidelity of 97.6(1)%, while controllable spectral filtering with passbands from 0.025 to 4.38 THz finds fidelities that first increase, and then level off with bandwidth, suggesting both stable operation with time and minimal polarization mode dispersion. To our knowledge, these results represent the first AAPT of a deployed quantum link, revealing a valuable tool for in situ analysis of entanglement-based quantum networks.

Rahman, Arefur [Arizona State Univ., Tempe, AZ (Un↗
DOE OSTI2023

Field Demonstration of the Brick Ontology to Scale up the Deployment of ASHRAE Guideline 36 Control Sequences

Many commercial buildings have a vast network of sensors as part of their building automation systems (BAS) that allows opportunities for energy consumption and cost savings by deploying advanced control sequences. However, this resource is often underutilized since BAS are typically programmed with simple control sequences with limited potential to deliver on these opportunities. The recent availability of ASHRAE Guideline 36 (G36) with advanced HVAC control sequences supports control retrofits in existing buildings to unlock much of the savings potential. However, barriers such as the lack of standard naming convention of building assets and data points, proprietary equipment and BAS, and the inherent uniqueness of buildings and their systems prevent building stakeholders from adopting any “plug-and-play” implementation of G36. Instead, control vendors must often undertake the manual and labor-intensive point mapping process to identify a data stream’s functional and spatial relationship within the HVAC system along with other relevant contexts and map it to the new control sequences. The vendor must carry out the point mapping process in each individual building since the mapping is unlikely to port over to another building. Even for the same building, the point mapping process can occur multiple times if various control vendors implement different control retrofits and/or multiple control retrofits happen over the lifecycle of the building. Then, there is the likelihood that G36 control sequences are programmed uniquely to the building, preventing the same implementation from being reused in another. Therefore, this paper presents a field demonstration of how we leveraged the Brick ontology with BACnet, OpenBuildingControl’s Control Description Language (CDL), and open-source support tools to implement scalable and portable advanced building controls. These tools provide standardized semantic descriptions and relationships of the building’s assets and data points (Brick), standardized communication protocol to read from and write to the building’s BAS (BACnet), and standardized code implementations (CDL) of standardized advanced control strategies (G36). We implemented G36’s hot water supply temperature setpoint reset in a Berkeley, CA building for this field demonstration. This field demonstration aims to show how integrating these tools may streamline the deployment of advanced control sequences such as G36 in a consistent manner regardless of differences found across buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Deployment of CF8C-Plus Cast Stainless Steels

The goal of this project was to accelerate the deployment of a new cast austenitic stainless steel, CF8C Plus, for new energy-relevant applications. The alloy was jointly developed by Oak Ridge National Laboratory (ORNL) and Caterpillar and is a low-cost, high-performance alternative to conventional cast steels and, in some cases, a cost-effective substitute for Ni-base alloys. CF8C-Plus steel won a 2003 R&D 100 Award, was patented in 2006 and was recognized as a new heat-resistant cast alloy grade by ASTM (HG10MNN). In 2006, CF8C-Plus was successfully commercialized for the Caterpillar Regeneration System (CRS) burner housing, which is needed for the operation of the ceramic diesel particular filter required in all on-highway diesel engines. To date, over 500 tons of CF8C-Plus have been cast for this single application. It was anticipated that the demonstrated commercial success in the CRS application could be translated to an expanded range of other transportation and power generation applications. Increased deployment of CF8C-Plus and Cu/W modified CF8C-Plus castings can lead to engines with increased efficiency and durability while lowering cost. Potential industrial partners that were targeted included automotive and diesel engine and part manufacturers as well as turbine, reciprocating engine and boiler manufacturers.

ASME Code Case↗
DOE OSTI2015

Evaluation of Radiometers Deployed at the National Renewable Energy Laboratory's Solar Radiation Research Laboratory

This study analyzes the performance of various commercially available radiometers used for measuring global horizontal irradiances and direct normal irradiances. These include pyranometers, pyrheliometers, rotating shadowband radiometers, and a pyranometer with fixed internal shading and are all deployed at the National Renewable Energy Laboratory's Solar Radiation Research Laboratory. Data from 32 global horizontal irradiance and 19 direct normal irradiance radiometers are presented. The radiometers in this study were deployed for one year (from April 1, 2011, through March 31, 2012) and compared to measurements from radiometers with the lowest values of estimated measurement uncertainties for producing reference global horizontal irradiances and direct normal irradiances.

14 SOLAR ENERGY↗
DOE OSTI2014

Overview of Development and Deployment of Codes, Standards and Regulations Affecting Energy Storage System Safety in the United States

This report acquaints stakeholders and interested parties involved in the development and/or deployment of energy storage systems (ESS) with the subject of safety-related codes, standards and regulations (CSRs). It is hoped that users of this document gain a more in depth and uniform understanding of safety-related CSR development and deployment that can foster improved communications among all ESS stakeholders and the collaboration needed to realize more timely acceptance and approval of safe ESS technology through appropriate CSR.

Conover, David R.↗
DOE OSTI2014

Economic Conditions and Factors Affecting New Nuclear Power Deployment

This report documents work performed in support of the US Department of Energy Office of Nuclear Energy’s Advanced Small Modular Reactor (AdvSMR) program. The report presents information and results from economic analyses to describe current electricity market conditions and those key factors that may impact the deployment of AdvSMRs or any other new nuclear power plants. Thus, this report serves as a reference document for DOE as it moves forward with its plans to develop advanced reactors, including AdvSMRs. For the purpose of this analysis, information on electricity markets and nuclear power plant operating costs will be combined to examine the current state of the nuclear industry and the process required to successfully move forward with new nuclear power in general and AdvSMRs in particular. The current electricity market is generally unfavorable to new nuclear construction, especially in deregulated markets with heavy competition from natural gas and subsidized renewables. The successful and profitable operation of a nuclear power plant (or any power plant) requires the rate at which the electricity is sold to be sufficiently greater than the cost to operate. The wholesale rates in most US markets have settled into values that provide profits for most operating nuclear power plants but are too low to support the added cost of capital recovery for new nuclear construction. There is a strong geographic dependence on the wholesale rate, with some markets currently able to support new nuclear construction. However, there is also a strong geographic dependence on pronuclear public opinion; the areas where power prices are high tend to have unfavorable views on the construction of new nuclear power plants. The use of government-backed incentives, such as subsidies, can help provide a margin to help justify construction projects that otherwise may not seem viable. Similarly, low interest rates for the project will also add a positive margin to the economic analysis. In both cases, the profitable price point is decreased, making more markets open to profitable entry. Overall, the economic attractiveness of a nuclear power construction project is not only a function of its own costs, but a function of the market into which it is deployed. Many of the market characteristics are out of the control of the potential nuclear power plant operators. The decision-making process for the power industry in general is complicated by the short-term market volatility in both the wholesale electricity market and the commodity (natural gas) market. Decisions based on market conditions today may be rendered null and void in six months. With a multiple-year lead time, nuclear power plants are acutely vulnerable to market corrections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Policies to Support Wind Power Deployment: Key Considerations and Good Practices

Policies have played an important role in scaling up wind deployment and increasing its economic viability while also supporting country-specific economic, social, and environmental development goals. Although wind power has become cost-competitive in several contexts, challenges to wind power deployment remain. Within the context of country-specific goals and challenges, policymakers are seeking

29 ENERGY PLANNING, POLICY, AND ECONOMY↗