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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 19 records

Evolving Architectures and Considerations to address Distributed Energy Resources and Non-Wired Alternatives

The electric grid is in the beginning stage of a transformation, driven by a combination of shutdowns of coal-fired plants, commissioning of new natural-gas plants, and tremendous growth in energy supply from renewables such as wind, and solar. As utilities navigate this transformation, their progress is supported by advances in Operational Technologies (OT), and Informational Technologies (IT), such as automation, smart inverters, cloud computing, mobile computing, machine learning, big data analytics, which have the potential to enable advanced capabilities more efficiently and at a lower cost. This white paper focuses on the architectural considerations that will allow the industry to transition in a planned manner. It introduces and formalizes two architectural constructs –the data bus and the control bus. The data bus is responsible for carrying all non-operational models and information necessary to drive utility decisions. In contrast, the control bus is responsible for carrying all operational data and control actions taken at the local level, centralized level, or other levels in-between. The paper reviews those architectural considerations, their requirements and how they will evolve. This paper intends to provide a context for vendors, utilities, and their service providers to review and understand the changes that are coming and get ready for them.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Mobile Edge Computing Framework for Traffic Optimization At Urban Intersections Through Cyber-Physical Integration

The stop-and-go traffic pattern on urban roads often results in excessive energy consumption because of unnecessary vehicle braking, idling, and accelerations. With the widespread and increased use of automobiles, this traffic pattern creates many negative impacts (e.g., delayed travel time, air pollution, and additional carbon emission) on the sustainability of our cities. Taking advantage of the recent emerging Internet of Things (IoT) and edge computing paradigms, we propose a mobile edge computing framework that integrates the capability of real-time vehicle-to-infrastructure communication and intelligent speed optimization algorithms into a mobile app to optimize individual vehicles' driving speed at signalized intersections. The optimization aims to mitigate the stop-and-go traffic pattern and its undesirable consequences in urban transportation systems. The framework consists of (1) a cyberinfrastructure-enabled dynamic messaging system for retrieving and delivering real-time traffic and signal phase and timing information from IoT-connected signal controllers and sensors, (2) a real-time speed optimization algorithm for generating intelligent speed advisory using vehicle's information (e.g., GPS and driving directions from mobile sensing) and corresponding signal and traffic information, and (3) an ad-hoc mobile computing environment that converts drivers' smartphones into edge devices to host the speed optimization algorithms for enabling intelligent advisory on the vehicle's driving speed within signalized corridors. The paper presents the design and implementation of the proposed framework. Finally, we demonstrate the feasibility, usefulness, and energy-saving benefits of our proposed framework and its prototyping mobile app on urban transportation systems through traffic simulation, real-vehicle laboratory experiments, an evaluative survey, and field communication tests. The simulation-based energy evaluation results show that the 100% usage of the mobile app can achieve 24% energy savings in the transportation system.

33 ADVANCED PROPULSION SYSTEMS↗

Singularity: Scientific containers for mobility of compute

Here we present Singularity, software developed to bring containers and reproducibility to scientific computing. Using Singularity containers, developers can work in reproducible environments of their choosing and design, and these complete environments can easily be copied and executed on other platforms. Singularity is an open source initiative that harnesses the expertise of system and software engineers and researchers alike, and integrates seamlessly into common workflows for both of these groups. As its primary use case, Singularity brings mobility of computing to both users and HPC centers, providing a secure means to capture and distribute software and compute environments. This ability to create and deploy reproducible environments across these centers, a previously unmet need, makes Singularity a game changing development for computational science.

97 MATHEMATICS AND COMPUTING↗

A rheological model for loose sands with insights from DEM

A rheological model for loose granular media is developed to capture both solid-like and fluid-like responses during shearing. The proposed model is built by following the mathematical structure of an extended Kelvin–Voigt model, where an elastic spring and plastic slider act in parallel to a viscous damper. This arrangement requires the partition of the total stress into rate-independent and rate-dependent stress components. To model the solid-like behavior, a simple frictional plasticity model is adopted without modifications, thus contributing to the rate-independent stress. Instead, the fluid-like or rate-dependent stress is further decomposed into deviatoric and volumetric parts, by proposing a new formulation based on a combination of the μ(I) relation, originally developed under pressure-controlled shear, with a pressure-shear rate relation derived under volume-controlled shear. The proposed formulation allows the model to capture both the increase in the friction coefficient and the enhanced dilation at high shear rates. High-fidelity simulation data, obtained from discrete element method and multiscale modelling, are used to evaluate the performance of the proposed constitutive model. The model provides accurate results under both drained and undrained simple shear paths across a wide range of shear rates. Furthermore, it successfully reproduces at much lower computational cost the flowslide mobility computed through multiscale simulations, which is primarily regulated by the shear rate dependence of the material properties during the dynamic runout stage.

Elasticity↗

Quantum key distribution using card, base station and trusted authority

Techniques and tools for quantum key distribution ("QKD") between a quantum communication ("QC") card, base station and trusted authority are described herein. In example implementations, a QC card contains a miniaturized QC transmitter and couples with a base station. The base station provides a network connection with the trusted authority and can also provide electric power to the QC card. When coupled to the base station, after authentication by the trusted authority, the QC card acquires keys through QKD with a trust authority. The keys can be used to set up secure communication, for authentication, for access control, or for other purposes. The QC card can be implemented as part of a smart phone or other mobile computing device, or the QC card can be used as a fillgun for distribution of the keys.

97 MATHEMATICS AND COMPUTING↗

Analytic derivative couplings and first-principles exciton/phonon coupling constants for an ab initio Frenkel-Davydov exciton model: Theory, implementation, and application to compute triplet exciton mobility parameters for crystalline tetracene

Recently, we introduced an ab initio version of the Frenkel-Davydov exciton model for computing excited-state properties of molecular crystals and aggregates. Within this model, supersystem excited states are approximated as linear combinations of excitations localized on molecular sites, and the electronic Hamiltonian is constructed and diagonalized in a direct-product basis of non-orthogonal configuration state functions computed for isolated fragments. In this work, we derive and implement analytic derivative couplings for this model, including nuclear derivatives of the natural transition orbital and symmetric orthogonalization transformations that are part of the approximation. Nuclear derivatives of the exciton Hamiltonian’s matrix elements, required in order to compute the nonadiabatic couplings, are equivalent to the “Holstein” and “Peierls” exciton/phonon couplings that are widely discussed in the context of model Hamiltonians for energy and charge transport in organic photovoltaics. As an example, we compute the couplings that modulate triplet exciton transport in crystalline tetracene, which is relevant in the context of carrier diffusion following singlet exciton fission.

74 ATOMIC AND MOLECULAR PHYSICS↗

Combining Landau–Zener theory and kinetic Monte Carlo sampling for small polaron mobility of doped BiVO 4 from first-principles

Transition metal oxides such as BiVO 4 are promising photoelectrode materials for solar-to-fuel conversion applications. However, their performance is limited by the low carrier mobility (especially electron mobility) due to the formation of small polarons. Recent experimental studies have shown improved carrier mobility and conductivity by atomic doping; however the underlying mechanism is not understood. A fundamental atomistic-level understanding of the effects on small polaron transport is critical to future material design with high conductivity. We studied the small polaron hopping mobility in pristine and doped BiVO 4 by combining Landau–Zener theory and kinetic Monte Carlo (kMC) simulation fully from first-principles, and investigated the effect of dopant–polaron interactions on the mobility. We found that polarons are spontaneously formed at V in both pristine and Mo/W doped BiVO 4 , which can only be described correctly by density functional theory (DFT) with the Hubbard correction (DFT+U) or hybrid exchange-correlation functional but not local or semi-local functionals. We found that DFT+U and dielectric dependant hybrid (DDH) functionals give similar electron hopping barriers, which are also similar between the room temperature monoclinic phase and the tetragonal phase. The calculated electron mobility agrees well with experimental values, which is around 10 -4 cm 2 V -1 s -1 . We found that the electron polaron transport in BiVO4 is neither fully adiabatic nor nonadiabatic, and the first and second nearest neighbor hoppings have significantly different electronic couplings between two hopping centers that lead to different adiabaticity and prefactors in the charge transfer rate, although they have similar hopping barriers. Without considering the detailed adiabaticity through Landau–Zener theory, one may get qualitatively wrong carrier mobility. We further computed polaron mobility in the presence of different dopants and showed that Cr substitution of V is an electron trap while Mo and W are “repulsive” centers, mainly due to the minimization of local lattice expansion by dopants and electron polarons. The dopants with “repulsive” interactions to polarons are promising for mobility improvement due to larger wavefunction overlap and delocalization of locally concentrated polarons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic Resource Scheduling in Mobile Edge Cloud with Cloud Radio Access Network

Nowadays, by integrating the cloud radio access network (C-RAN) with the mobile edge cloud computing (MEC) technology, mobile service provider (MSP) can efficiently handle the increasing mobile traffic and enhance the capabilities of mobile devices. But the power consumption has become skyrocketing for MSP and it gravely affects the profit of MSP. Previous work often studied the power consumption in C-RAN and MEC separately while less work had considered the integration of C-RAN with MEC. In this paper, we present an unifying framework for the power-performance tradeoff of MSP by jointly scheduling network resources in C-RAN and computation resources in MEC to maximize the profit of MSP. To achieve this objective, we formulate the resource scheduling issue as a stochastic problem and design a new optimization framework by using an extended Lyapunov technique. Specially, because the standard Lyapunov technique critically assumes that job requests have fixed lengths and can be finished within each decision making interval, it is not suitable for the dynamic situation where the mobile job requests have variable lengths. To solve this problem, we extend the standard Lyapunov technique and design the VariedLen algorithm to make online decisions in consecutive time for job requests with variable lengths. Furthermore, our proposed algorithm can reach time average profit that is close to the optimum with a diminishing gap (1/V) for the MSP while still maintaining strong system stability and low congestion. With extensive simulations based on a real world trace, we demonstrate the efficacy and optimality of our proposed algorithm.

97 MATHEMATICS AND COMPUTING↗

An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles

In order to enable Social Internet of Vehicles devices to achieve the purpose of intelligent and autonomous garbage classification in a public environment, while avoiding network congestion caused by a large amount of data accessing the cloud at the same time, it is therefore considered to combine mobile edge computing with Social Internet of Vehicles to give full play to mobile edge computing features of high bandwidth and low latency. At the same time, based on cutting-edge technologies such as deep learning, knowledge graph, and 5G transmission, the paper builds an intelligent garbage sorting system based on edge computing and visual understanding of Social Internet of Vehicles. First of all, for the massive multisource heterogeneous Social Internet of Vehicles big data in the public environment, different item modal data adopts different processing methods, aiming to obtain a visual understanding model. Secondly, using the 5G network, the model is deployed on the edge device and the cloud for cloud-side collaborative management, aiming to avoid the waste of edge node resources, while ensuring the data privacy of the edge node. Finally, the Social Internet of Vehicles devices is used to make intelligent decision-making on the big data of the items. First, the items are judged as garbage, and then the category is judged, and finally the task of grabbing and sorting is realized. The experimental results show that the system proposed in this paper can efficiently process the big data of Social Internet of Vehicles and make valuable intelligent decisions. At the same time, it also has a certain role in promoting the promotion of Social Internet of Vehicles devices.

Shen, Xuehao↗

Combined Experimental and Computational Efforts to Establish Ion Mobility, Solubility and Stability of Functional Liquids for Electrochemical Energy Storage

This work provides a computation-driven investigation of the stability of organic electrolytes for lithium-air batteries. Electrolyte instability is currently a key challenge that limits practical use of aprotic Li-air batteries, and the chemical processes that cause this instability are often kinetically-driven. Computational screening for kinetic stability involves the determination of reaction barriers for the numerous potential reaction mechanisms, barriers that are challenging to calculate due to the difficulty of locating transition state structures. Here we screen a broad set of substituted electrolytes for susceptibility to nucleophilic attack by superoxide. We find that carbonates are not typically expected to be stable and that sulfones are generally stable, validating literature trends. We study the effects of chemical functionalization with electron-donating and withdrawing groups and their interplay with steric factors, identifying functional groups and other chemical modifications that increase stability in these groups. User-input driven transition state identification is used for these initial calculations, and an automated computational pipeline is subsequently presented and validated as a means to perform further high-throughput searches across mechanisms and chemistries. The pipeline integrates cheminformatics-based reaction encoding, relaxed potential energy scans, and nudged elastic band calculations for an end-to-end approach to barrier calculations. We review this automated search approach and its current limitations, and discuss challenges and further work.

25 ENERGY STORAGE↗

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2021. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data.

energy efficiency mobility↗

Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers

Here we present Singularity Hub, a framework to build and deploy Singularity containers for mobility of compute, and the singularity-python software with novel metrics for assessing reproducibility of such containers. Singularity containers make it possible for scientists and developers to package reproducible software, and Singularity Hub adds automation to this workflow by building, capturing metadata for, visualizing, and serving containers programmatically. Our novel metrics, based on custom filters of content hashes of container contents, allow for comparison of an entire container, including operating system, custom software, and metadata. First we will review Singularity Hub’s primary use cases and how the infrastructure has been designed to support modern, common workflows. Next, we conduct three analyses to demonstrate build consistency, reproducibility metric and performance and interpretability, and potential for discovery. This is the first effort to demonstrate a rigorous assessment of measurable similarity between containers and operating systems. We provide these capabilities within Singularity Hub, as well as the source software singularity-python that provides the underlying functionality. Singularity Hub is available at https://singularity-hub.org, and we are excited to provide it as an openly available platform for building, and deploying scientific containers.

97 MATHEMATICS AND COMPUTING↗

Mobility and clustering of barium ions and dications in high-pressure xenon gas

The clustering and drift properties of barium ions in xenon gas are explored theoretically, using density-functional theory and computational ion mobility theory, with the goal of better understanding barium ion transport for neutrinoless double beta decay. Here, we derive the equilibrium conformations, energies, and entropies of molecular ions in the Ba + -Xe and Ba 2 + -Xe systems, which yield a predictive model of cluster formation in high-pressure gas. In this work, we calculate ion-neutral interaction potential curves for these species and use them to predict effective molecular ion mobilities. Our calculation consistently reproduces experimental data on effective mobility and molecular ion formation for the Ba + system, and predicts strong cluster formation in the Ba 2 + system, dominated by stable [ BaXe 6 ] 2 + , [ BaXe 7 ] 2 + , [ BaXe 8 ] 2 + , and [ BaXe 9 ] 2 + complexes in the range of interest. Some implications for barium tagging in gas-phase neutrinoless double beta decay experiments are discussed, and the first predictions of pressure-dependent mobility of the doubly charged Ba 2 + species are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Genotoxic and carcinogenic effects of non-ionizing electromagnetic fields

Highlights: • Public concern over the effects of EMF on cancer is growing. • In vitro and in vivo experiments concerning ELF and EMF have elicited contradictory results. • Epidemiological studies may help us to understand the genotoxic and carcinogenic effects of EMF. • Do adverse effects differ depending on the EMF frequency involved? New technologies in electronics and communications are continually emerging. An increasing use of these electronic devices such as mobile phone, computer, wireless fidelity connectors or cellular towers is raising questions concerning whether they have an adverse effect on the body. Exposure to electromagnetic fields (EMF) is frequently suggested to have adverse health effects on humans and other organisms. This idea has been reported in many studies. In contrast, the therapeutic effects of EMF on different organs have also been reported. Research findings are inconsistent. This has given rise to very profound discrepancies. The duration and frequency of mobile phone calls and the association observed with various health effects has raised serious concerns due to the frequency with which these devices are used and the way they are held close to the head. The present review assesses the results of in vitro, in vivo, experimental, and epidemiological studies. The purpose of the study is to assess data concerning the carcinogenic and genotoxic effects of non-ionizing EMF. The major genotoxic and carcinogenic effects of EMF, divided into subsections as low frequency effects and radiofrequency effects, were reviewed. The inconsistent results between similar studies and the same research groups have made it very difficult to make any comprehensive interpretation. However, evaluation of current studies suggests that EMF may represent a serious source of concern and may be hazardous to living organisms.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2022. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data. Anyone can create an account and access data at https://livewire.energy.gov/.

energy efficiency↗