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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Resilient Solar and Storage Roadmap

Resilience to natural disasters is imperative for safe, economically productive cities. In the immediate aftermath of an earthquake, flood, or other disaster, one key element of resilience is continued operation of shelters and critical emergency management facilities. Operation of these facilities depends on reliable emergency power. Traditional emergency power systems use diesel generators with storage tanks, which provide power for only a few days in the absence of the electric or gas grid. However, a recent study has shown that gas and electric networks can require days or weeks to recover from a disaster, leaving facilities with generators at risk of running out of fuel. This has already been experienced in New York City after Hurricane Sandy where a combination of lengthy outages and high flood waters compromised the traditional diesel storage and generator backup infrastructure at hospitals and shelters. With the risk of natural disasters increasing due to climate change, we must turn to more resilient solutions for providing backup power to shelters, medical centers, and emergency operations centers. From 2015 to 2017, the City and County of San Francisco Solar and Storage for Resilience Project examined the use of microgrids and stand-alone solar electric generation with battery storage to provide resilient post-disaster power to critical facilities. The project evaluated 1,263 potential congregation and shelter sites across the city, 67 of which were identified as shelter sites with power requirements and opportunities to develop resilient infrastructure through solar and storage. Site visits were conducted for 18 of these buildings, spanning all 11 supervisor districts in San Francisco and a range of normal and emergency use types. The project team used observations from these site visits to create representative emergency power profiles for all 67 shelters in San Francisco. Using these profiles, the team found that 8.2 megawatts (MW) of photovoltaic panels and 12.9 MW of battery storage would be required to provide resilient backup power for San Francisco’s shelters following a disaster. Given the high capital cost of deploying this large resource, the project team investigated various financing options — a public-private partnership was found to be a viable pathway for financing resilient solar and storage. Given the added benefit of energy cost savings in normal operation, a public-private partnership financing model would save the City and County of San Francisco 6% over a traditional design-bid-build approach over a 20-year portfolio lifetime. This roadmap documents the project’s steps of identifying critical facilities, surveying power requirements, assessing renewable potential, evaluating financing options to develop the solar and storage systems for resiliency, and modeling individual sites for solar and storage installation. This roadmap also examines the challenges critical facilities face in providing resilient power, such as key technical, political, and financing barriers, as well as the opportunities and policy recommendations to further advance resilient solar and storage development in San Francisco. While this report focuses on a detailed study of San Francisco, the methods and outcomes are applicable to any city or town.

14 SOLAR ENERGY↗
DOE OSTI2023

Thermal Conductivity of a Novel Salt-Hydrogel Complex as a Phase Change Material for Building Thermal Management

Use of electricity for space heating, ventilation and air conditioning in buildings may be better managed through temporary energy storage. Compared with electrochemical storage, the levelized cost of thermal energy storage systems can be lower depending on geographical location and thermophysical properties [1]. In any phase change material (PCM), the rate of absorption and release of thermal energy increases with higher thermal conductivity [2]. However, leading PCMs like paraffin waxes have thermal conductivities on the order of 0.1 W/mK. Glauber’s salt, a salt hydrate, possesses a relatively high thermal conductivity but suffers from supercooling and phase segregation. Research has shown that polymer-based composites with salt hydrates can prevent phase segregation and limit supercooling over hundreds of cycles [3] though the thermal conductivity of the composite may be reduced leading to low energy storage rates. Here, we report thermal conductivity measurements on polymer hydrogels which are stable in solutions of Glauber’s salt. To measure thermal conductivity of soft gels, we use a 3-omega method [4] where heat flows bidirectionally through a substrate below and through a gel placed on top. This suits measurements of both gels and liquids unlike transient plane heat source or transient hot wire methods. We report measurements of thermal conductivity of salt-hydrogel complexes as a function of temperature, cross-linking and salt concentration. In addition, we present modeling of thermal conductivity of sodium sulfate solutions with available theories. We finally employ polarized optical microscopy to observe inside the transparent hydrogel networks, showing that precipitating crystals may influence thermal conductivity measurements for high salt concentrations. Our thermal conductivity results combined with enthalpy of phase change, mass density and specific heat are essential to accurately design thermal storage systems for energy-efficient buildings.

composite, thermal conductivity↗
DOE OSTI2020

Zero-deadtime processing in beta spectroscopy for measurement of the non-zero neutrino mass

The Project 8 collaboration seeks to measure, or more tightly bound, the mass of the electron antineutrino by applying a novel spectroscopy technique to precisely measure the tritium beta-decay spectrum. The current system produces a single analog signal, which is digitized and processed in several stages before being saved to local disk storage. Online processing includes two stages, an FPGA connected to the analog to digital converter reduces the data down to the region of interest before shipping over the local network for further processing and storage. A normal CPU-based processing stage applies triggering logic to only save data at times when a signal is present, further reducing the total volume of data which needs to be written to disk or transferred for long-term storage. The next stage of the project will need to process many input channels and will integrate a necessary aggregation and combination step prior to applying the event search and triggering logic. We present the online processing system which has successfully been deployed for the current, singlechannel, phase. We also present the status and design for a many-channel platform.

Project 8 Collaboration↗
DOE OSTI2023

Normality of I-V Measurements Using ML

There is an increased interest in instrument-computing ecosystems (ICEs) that support science workflows empowered by AI-automated experiments and computations in diverse areas. In particular, electrochemistry ICEs are promising for accelerating the design and discovery of electrochemical systems for energy storage and conversion, by automating significant parts of workflows that combine synthesis and characterization experiments with computations. They require the integration of flow controllers, solvent containers, pumps, fraction collectors, and potentiostats, all connected to an electrochemical cell, as illustrated in Fig. 1. These are specialized instruments with custom software that is not originally designed for network integration. We developed network and software solutions for electrochemical workflows that adapt system and instrument settings in real-time for multiple rounds of experiments. In particular, we developed Python wrappers for Application Programming Interfaces (APIs) of instrument commands and Pyro client-server modules that enable them to be executed from remote computers. The entire workflow is orchestrated by a Jupyter notebook running on a remote computer.

Al Najjar, Anees↗
NASA NTRS2014

Power, Avionics and Software Communication Network Architecture

This document describes the communication architecture for the Power, Avionics and Software (PAS) 2.0 subsystem for the Advanced Extravehicular Mobile Unit (AEMU). The following systems are described in detail: Caution Warn- ing and Control System, Informatics, Storage, Video, Audio, Communication, and Monitoring Test and Validation. This document also provides some background as well as the purpose and goals of the PAS project at Glenn Research Center (GRC).

Avionics↗
DOE OSTI2017

Machine learning $\mathbb{Z}_2$ quantum spin liquids with quasiparticle statistics

After decades of progress and effort, obtaining a phase diagram for a strongly correlated topological system still remains a challenge. Although in principle one could turn to Wilson loops and long-range entanglement, evaluating these nonlocal observables at many points in phase space can be prohibitively costly. With growing excitement over topological quantum computation comes the need for an efficient approach for obtaining topological phase diagrams. In this report we turn to machine learning using quantum loop topography (QLT), a notion we have recently introduced. Specifically, we propose a construction of QLT that is sensitive to quasiparticle statistics. We then use mutual statistics between the spinons and visons to detect a $\mathbb{Z}_2$ quantum spin liquid in a multiparameter phase space. We successfully obtain the quantum phase boundary between the topological and trivial phases using a simple feed-forward neural network. Furthermore, we demonstrate advantages of our approach for the evaluation of phase diagrams relating to speed and storage. Such statistics-based machine learning of topological phases opens new efficient routes to studying topological phase diagrams in strongly correlated systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identification and Testing of Electric Vehicle Fast Charger Cybersecurity Mitigations

Fast-charging infrastructure for electric vehicles (EVs) is needed to enable and achieve the national goals of transitioning the vehicle fleet toward more electrification. Idaho National Laboratory, Oak Ridge National Laboratory, and the National Renewable Energy Laboratory (NREL) have jointly worked to identify, evaluate, and mitigate potential cyber-related consequences associated with fast charger systems. NREL contributed by considering cyberattack scenarios and consequences associated with integrating distributed energy resources (DERs) at fast-charging stations. The dynamic nature of fast-charger load profiles would encourage site operators to incorporate solar for energy cost reduction and energy storage for peak demand cost management at future charging facilities with multiple fast chargers at a site. These energy resources would be monitored and coordinated via a site energy management controller with data exchange between devices and local power metering infrastructure; thus, networking between devices and the design of the system becomes important in the overall cybersecurity posture. In addition, component vendors and system operators might have remote interfaces to any of these systems. It is therefore important to understand the breadth of the cyberattack surface and potential strategies to mitigate impacts. This project has focused on components and protocols expected to be found within a local charging site that includes multiple chargers and DER resources. Our methods and results are summarized in this final report.

42 ENGINEERING↗
DOE OSTI2019

Multi-electron Reduction Capacity and Multiple Binding Pockets in Metal–Organic Redox Assembly at Surfaces

Metal–ligand complexation at surfaces utilizing redox-active ligands has been demonstrated to produce uniform single-site metals centers in regular coordination networks. Two key design considerations are the electron storage capacity of the ligand and the metal-coordinating pockets on the ligand. In an effort to move toward greater complexity in the systems, particularly dinuclear metal centers, we designed and synthesized tetraethyltetra-aza-anthraquinone, TAAQ, which has superior electron storage capabilities and four ligating pockets in a diverging geometry. Cyclic voltammetry studies of the free ligand demonstrate its ability to undergo up to a four-electron reduction. Solution-based studies with an analogous ligand, diethyldi-aza-anthraquinone, demonstrate these redox capabilities in a molecular environment. Surface studies conducted on the Au(111) surface demonstrate TAAQ's ability to complex with Fe. This complexation can be observed at different stoichiometric ratios of Fe:TAAQ as Fe 2p core level shifts in X-ray photoelectron spectroscopy. Scanning tunneling microscopy experiments confirmed the formation of metal–organic coordination structures. The striking feature of these structures is their irregularity, which indicates the presence of multiple local binding motifs. Density functional theory calculations confirm several energetically accessible Fe:TAAQ isomers, which accounts for the non-uniformity of the chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows

This report details recent progress for the ASCR funded project “Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows”. We refer to the project as IPPD/2, reflecting the 2017 renewal under expanded scope and partners In IPPD/2, we increased our research scope to include data motion. We are focusing on three major aspects: a) observe how data is generated, distributed, and used; b) analyze how data is (repeatedly) consumed with a focus both on repeated patterns and anomalies; and c) explore how to optimize data motion. This new work on data motion will augment and complement IPPD/2’s research that focused on the computational aspects of tasks. We leverage and extend our existing tools and demonstrate our work on the Belle II workflow suite as well as on workflows from NSLS-II. The highlights of our work are as follows: Provenance for Workflows: Provenance is used to provide information enabling quality control, re-run computational workflows, and reproduce results. IPPD/2 has been building a scalable provenance management system that enables the capture of provenance from the high-level workflow through all relevant system levels in one integrated environment. Leveraging this work, our recent efforts have included using provenance as an enabling technique. Workload characterization: Leveraging provenance and analysis, we characterize data movement within network, storage, and memory over a variety of workloads. This characterization enables an understanding by performance analysts and application developers of the range of behaviors that could be expected. Performance Prediction for Workflows: The goal of modeling distributed workflows is to understand performance bottlenecks and enable more intelligent task scheduling to optimize selected metrics of interest (e.g., task throughput or output data rate). IPPD/2 has utilized both analytical and AI/ML modeling methodologies for performance modeling. Advanced Scheduling and Fault Modeling for Workflows: Scheduling of large-scale scientific workflows on geographically distributed resources is a challenging problem. To improve workflow throughput, we combined novel scheduling algorithms with task predictions from performance modeling and fault modeling. Dynamically Alleviating Bottlenecks in Workflows: Exploiting our provenance, analysis, and modeling efforts, we have explored and developed several techniques for dynamically detecting and alleviating bottlenecks in data movement. In particular, we have spent considerable effort demonstrating our techniques on production-like workflow configurations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Information Power Grid Posters

This document is a summary of the accomplishments of the Information Power Grid (IPG). Grids are an emerging technology that provide seamless and uniform access to the geographically dispersed, computational, data storage, networking, instruments, and software resources needed for solving large-scale scientific and engineering problems. The goal of the NASA IPG is to use NASA's remotely located computing and data system resources to build distributed systems that can address problems that are too large or complex for a single site. The accomplishments outlined in this poster presentation are: access to distributed data, IPG heterogeneous computing, integration of large-scale computing node into distributed environment, remote access to high data rate instruments,and exploratory grid environment.

Vaziri, Arsi↗
NASA NTRS1990

The role of data management in discipline-independent data visualization

The common data format (CDF) is described in terms of its support applications for the database management of visualization systems. The CDF is a self-describing data abstraction technique for the storage and manipulation of multidimensional data that are based on block structures. The discipline-independent approach is designed to manage, manipulate, archive, display, and analyze data, and can be applied to heterogeneous equipment communicating different data structures over networks. An improved CDF version incorporates a hyperplane access allowing random aggregate access to subdimensional blocks within a multidimensional variable. The visualization pipeline is also discussed, which controls the flow of data and permits the visualization of different classes of data representation techniques. The system is found to accommodate a large variety of scientific data structures and large disk-based data sets.

Treinish, Lloyd A.↗
DOE OSTI2019

Smart Electric Vehicle Charging for a Reliable and Resilient Grid (RECHARGE)

This presentation discusses a project to determine how plug-in electric vehicles (PEVs) charging at scale in two cities should be managed to avoid negative grid impacts. It also will allow critical strategies and technologies to be developed, and will increase the value for PEV owners, building managers, charge network operators, grid services aggregators, and utilities.

25 ENERGY STORAGE↗
DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration: Preprint

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); soft open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Combined Force-Frequency Sampling for Simulation of Systems Having Rugged Free Energy Landscapes.

An adaptive, machine learning-based sampling method is presented for simulation of systems having rugged, multidimensional free energy landscapes. The method's main strength resides in its ability to learn both from the frequency of visits to distinct states and the generalized force estimates that arise in a system as it evolves in phase space. This is accomplished by introducing a self-integrating artificial neural network, which generates an estimate of the free energy directly from its derivatives. The usefulness of the proposed combined approach is examined in the context of two concrete examples, namely, an alanine dipeptide molecule in water and a polymer diffusing through a narrow pore. This new method is found to be robust, faster, and more accurate than approaches that rely only on frequency-based or generalized force-based estimations. After combining the proposed approach with overfill protection and support for sparse data storage and training, the method is shown to be more effective than comparable, previously available techniques and capable of scaling efficiently to larger numbers of collective variables.

Sevgen, Emre↗