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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

RouteE API

This is the API endpoint for RouteE energy prediction, which can be used to get both single vehicle link or route energy estimates and transportation network-wide energy consumption estimates for a variety of vehicles. This enables external researchers and transportation engineers to access and utilize NREL's growing library of pre-trained vehicle models for prediction of transportation energy consumption. This API provides three endpoints: • /route: Energy estimation of a vehicle over a planning link or sequence of links (route). • /network: Network-wide estimation of energy consumption for all vehicle traffic in the desired area. • /compass: Energy-optimal “eco-routing” between input origin and destination coordinates (Currently in beta for Denver metro area only).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

RouteE API

This is the API endpoint for RouteE energy prediction, which can be used to get both single vehicle link or route energy estimates and transportation network-wide energy consumption estimates for a variety of vehicles. This enables external researchers and transportation engineers to access and utilize NREL's growing library of pre-trained vehicle models for prediction of transportation energy consumption. This API provides three endpoints: - /route: Energy estimation of a vehicle over a planning link or sequence of links (route). - /network: Network-wide estimation of energy consumption for all vehicle traffic in the desired area. - /compass: Energy-optimal “eco-routing” between input origin and destination coordinates (Currently in beta for Denver metro area only).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

RouteE API

This is the API endpoint for RouteE energy prediction, which can be used to get both single vehicle link or route energy estimates and transportation network-wide energy consumption estimates for a variety of vehicles. This enables external researchers and transportation engineers to access and utilize NLR's growing library of pre-trained vehicle models for prediction of transportation energy consumption. This API provides three endpoints: - /route: Energy estimation of a vehicle over a planning link or sequence of links (route). - /network: Network-wide estimation of energy consumption for all vehicle traffic in the desired area. - /compass: Energy-optimal “eco-routing” between input origin and destination coordinates (Currently in beta for Denver metro area only).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Aerial drone fleet deployment optimization with endogenous battery replacements for direct delivery of time-sensitive products

Aerial drones offer a distinct potential to reduce the delivery time and energy consumption for the delivery of time-sensitive and small products. However, there is still a need in the relevant industry to understand the performance of drone-based delivery under different business needs and drone operating conditions. We studied a drone deployment optimization problem for direct delivery of time-sensitive products with release dates to customers maintaining a specified time window. This paper presents a new mixed-integer programming model, new valid inequalities, a new greedy heuristic algorithm, and a Genetic algorithm to help business owners optimally schedule and route their drone fleet minimizing the required fleet size, the required number of additional batteries, and total energy consumption. A realistic feature of the optimization method is that instead of replacing the drone battery after each return to the depot, it keeps track of the remaining energy in the drone battery and decides on battery replacements accounting for the drone routing and the user-specified minimum required battery energy. Numerical results based on real data from drone flight tests and prepared food delivery industry provide insights into the effect of different practical drone operating parameters on the required fleet size, the required number of battery replacements, and energy consumption. Here, results demonstrate that the proposed heuristic algorithm substantially outperforms the accelerated CPLEX in runtime while sacrificing the solution quality by a small amount. Additionally, results show that using a mixed fleet of hexacopter and quadcopter drones reduces the total energy consumption by 48.52% compared to using a homogeneous fleet of only hexacopters.

Drone energy consumption↗
DOE OSTI2020

Integrated Resource Supply-Demand-Routing Model for the COVID-19 Crisis

As part of the Department of Energy response to the novel coronavirus disease (COVID-19) pandemic of 2020, a modeling effort was sponsored by the DOE Office of Science. Through this effort, an integrated planning framework was developed whose capabilities were demonstrated with the combination of a treatment resource demand model and an optimization model for routing supplies. This report documents this framework and models, and an application involving ventilator demands and supplies in the continental United States. The goal of this application is to test the feasibility of implementing nationwide ventilator sharing in response to the COVID-19 crisis. Multiple scenarios were run using different combinations of forecasted and observed patient streams, and it is demonstrated that using a "worst-case forecast for planning may be preferable to best mitigate supply-demand risks in an uncertain future. There is also a brief discussion of model uncertainty and its implications for the results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1990

Depth-first search approach for fault-tolerant routing in hypercube multicomputers

Using depth-first search, the authors develop and analyze the performance of a routing scheme for hypercube multicomputers in the presence of an arbitrary number of faulty components. They derive an exact expression for the probability of routing messages by way of optimal paths (of length equal to the Hamming distance between the corresponding pair of nodes) from the source node to an obstructed node. The obstructed node is defined as the first node encountered by the message that finds no optimal path to the destination node. It is noted that the probability of routing messages over an optimal path between any two nodes is a special case of the present results and can be obtained by replacing the obstructed node with the destination node. Numerical examples are given to illustrate the results, and they show that, in the presence of component failures, depth-first search routing can route a message to its destination by means of an optimal path with a very high probability.

Chen, Ming-Syan↗
DOE OSTI2019

Modeling and Optimization of Trip Level Energy Consumption and Charging Management for Connected Automated Electric Vehicles

This will be a presentation for a tutorial session in 2019 ITEC based on reviewing the publicly existing work in the literature. Trip aware energy consumption and charging management for electric vehicles is a key component to ensure sustainability of electrified transportation. The upcoming vehicle communication and autonomous driving technologies will provide opportunities to achieve more intelligent management strategies. This tutorial will introduce the state-to-art technologies that are being designed for optimizing the trip level energy cost and recharging operations of connected automated electric vehicles (CAEVs). The information needs, modeling, control and optimization techniques for optimal trip level energy management will be introduced. Opportunities and benefits from vehicle communication and automation will be discussed. In general, three main sub-topics will be presented in detail: first, advanced EV energy consumption modeling and prediction technologies; second, energy efficient driving technologies, e.g. eco-driving and eco-routing, etc.; third, optimally automatic charging decision making for CAEVs. Following these details, the research challenges, opportunities for co-optimization between the energy consumption and energy recharging of CAEVs will be illustrated in this tutorial.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Toward Time Synchronization in Delay Tolerant Network based Solar System Internetworking

The expanding presence in space will place an increased dependency on networked communications– a scalable communications infrastructure; that is, the Solar System Internet (SSI). Upcoming developments towards a SSI include NASA’s upcoming LunaNet, or lunar Internet, which provides multi-hop multi-path communications using Delay Tolerant Networking (DTN). DTN has been an active area of research and development, particularly in routing, security, and optimization. DTNs are marked by mobility, disconnection, and a wide variance of latencies (propagation and processing delays). In this paper, we outline progress towards a theory of time synchronization across such a network. An underlying assumption of DTN is that the network is time synchronized already, rather than synchronization being provided as a service. While this is necessary for schedule-based routing, which is necessarily prevalent in DTNs, it is so deeply ingrained as to be built into the primary unit of data in DTNs– the bundle. Indeed, a bundle’s creation timestamp and its time to live (called the lifetime) are based on time, and there are special recommendations for systems that lack accurate clocks. The assumption of time synchronization makes sense when limiting considerations to smaller-scale and more traditional space communication. However, just as end-to-end connectivity cannot be guaranteed in DTNs, neither can access to a reference or authoritative clock. In this more general case, it might be necessary to synchronize over time-varying meshes, and perhaps even to consider relativistic effects. Moreover, by imposing synchronization restrictions in order to sustain a network, the effectiveness of the network to achieve scalability will be necessarily muted. To work towards a time synchronization theory for DTNs, we build upon past successes in modeling DTNs using time-varying graphs and sheaves. This includes error and limitation estimation, which allows one to define domains over which schedule-based routing is possible, up to some threshold sensitivity. Despite the theoretical nature of these results, the approaches taken are also algorithmic, and hence lend themselves to practical implementations. The paper concludes with comparisons of the various methods along with suggestions for future work.

Delay Tolerant Networking↗
NASA NTRS2011

Traffic Flow Management Wrap-Up

Traffic Flow Management involves the scheduling and routing of air traffic subject to airport and airspace capacity constraints, and the efficient use of available airspace. Significant challenges in this area include: (1) weather integration and forecasting, (2) accounting for user preferences in the Traffic Flow Management decision making process, and (3) understanding and mitigating the environmental impacts of air traffic on the environment. To address these challenges, researchers in the Traffic Flow Management area are developing modeling, simulation and optimization techniques to route and schedule air traffic flights and flows while accommodating user preferences, accounting for system uncertainties and considering the environmental impacts of aviation. This presentation will highlight some of the major challenges facing researchers in this domain, while also showcasing recent innovations designed to address these challenges.

Grabbe, Shon↗
NASA NTRSDate not supplied

Fine Optimization of TES Design for the X-IFU Instrument on ATHENA

The X-ray Integral Field Unit (X-IFU) instrument on the Advanced Telescope for High ENergy Astrophysics (ATHENA) is baselined to have 3168 transition-edge sensor (TES) microcalorimeter pixels. These pixels will be DC biased and readout using time division multiplexing. We recently reported a demonstration of the required pixel and readout performance in 252 pixels from a 1 kilo-pixel array (e.g. 2.16 eV resolution for 6.9 keV X-rays). Having achieved the required performance, the 50um square TES design in this demonstration array is considered the baseline pixel design for X-IFU. However, by making small adjustments to the TES design, we may be able to make small but consequential improvements to the instrument performance, while staying within the many constraints of the X-IFU requirements. In this presentation, we will show results from newly fabricated devices with subtle changes from the baseline TES design to further optimize the performance for X-IFU. We will discuss optimizing the TES sheet resistance, normal metal features, X-ray absorber attachment points, TES aspect ratio, and heat capacity. These minor design changes can have significant effects on thermo-electric time constants, thermal fluctuation noise, resistive transition shape and uniformity, and non-linearity of X-ray event pulses. In addition, full characterization of these new TES designs allows greater understanding of the relevant physics within the TES and gives routes for further optimization.

Nick Wakeham↗
DOE OSTI2023

QuComm: Optimizing Collective Communication for Distributed Quantum Computing

Distributed quantum computing (DQC) is a scalable way to build a large-scale quantum computing system while the error-prone nonlocal communication between DQC nodes may heavily degrade the fidelity of the distributed quantum program and thus demands specific compiler optimizations. Previous compilers on DQC communication optimization either assumes unlimited communication resource or a few communication qubits due to the hardware limitation. The former compilers may not be efficient when interfacing with communication-resource-constrained DQC hardware while the latter compilers lose the opportunities of optimizing collective communication and routing concurrent communication as they unnecessarily couple limited communication qubits with the implementation of expensive inter-node operations. In this paper, we invent the communication buffer, a communication facility consisting of idle qubits in each compute node, to decouple the execution of inter-node quantum operations from communication qubits: communication qubits are devoted to generating inter-node entanglement while internode operations are conducted in the communication buffer. The communication buffer provides an intermediate layer for inter-node communication and paves the way for collective communication optimization. We then propose QuComm, a buffer-based compiler framework that first performs smart buffer allocation according to communication characteristics of the distributed quantum program and then optimizes and collectively routes inter-node quantum operations. Experimental results on a hierarchical DQC system show that the proposed QuComm can reduce the most expensive inter-node communication request and the latency of various distributed quantum programs by 50.4% and 47.6% on average, respectively.

Wu, Anbang↗
DOE OSTI2023

Socially-aware evaluation framework for transportation

Technological advancements are rapidly changing traffic management in cities. Navigation applications, in particular, have impacted cities in many ways by rerouting traffic. As different routing strategies distribute traffic differently, understanding these disparities across multiple city-relevant dimensions is extremely important for decision-makers. We develop a multi-themed framework called Socially- Aware Evaluation Framework for Transportation (SAEF), which assists in understanding how traffic routing and the resultant dynamics affect cities. The framework is presented for four Bay Area cities, for which we compare three routing strategies - user equilibrium travel time, system optimal travel time, and system optimal fuel. The results demonstrate that many neighborhood impacts, such as traffic load on residential streets and around minority schools, degraded with the system-optimal travel time and fuel routing in comparison to the user-equilibrium travel time routing. The findings also show that all routing strategies subject the city's disadvantaged neighborhoods to disproportionate traffic exposure. Our intent with this work is to provide an evaluation framework that enables reflection on the consequences of traffic routing and management strategies, allowing city planners to recognize the trade-offs and potential unintended consequences.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

From charge storage mechanism to performance: A roadmap toward high specific energy sodium-ion batteries through carbon-anode optimization

Serious critical issues hamper the arrival on the market of sodium-ion batteries (SIBs) as a lower cost substitute to Li-ion batteries (LIBs). Among these, the negligible sodium uptake into graphite, which is the keystone of the present LIB technology, appears to be one of the toughest to tackle. Although hard carbon is known for years as one of the best substitutes, its performance remains below that of graphite in Li-ion batteries, while its mechanism of sodium storage is still under debate. Many other carbons are studied since a few years, some of which presenting capacities far beyond that of graphite. However, they tend to present larger voltage and high first cycle loss, leading to limited benefit in terms of specific energy at full cell level. Overcoming this preoccupying tradeoff requires a deep understanding of the charge storage mechanisms and the correlation between structure, microstructure and performance. The present Review aims at bringing light to this question by drawing a roadmap of the emerging routes for the optimization of carbon materials as SIB anode, on the basis of a critical survey of their reported electrochemical performance and charge storage mechanisms.

Saurel, Damien↗
NASA NTRS2010

A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem

Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.

Montoya, Justin Vincent↗
DOE OSTI2019

An adjoint method for neoclassical stellarator optimization

Stellarators remain an enticing route to steady-state fusion power. However, to achieve the required confinement, the magnetic geometry must be highly optimized. This optimization requires navigating high-dimensional spaces, often necessitating the use of gradient-based methods. The gradient of the neoclassical fluxes is expensive to compute with classical methods, requiring $O(N)$ flux computations, where $N$ is the number of parameters. To reduce the cost of the gradient computation, we present an adjoint method for computing the derivatives of moments of the neoclassical distribution function for stellarator optimization. The linear adjoint method allows derivatives of quantities which depend on solutions of a linear system, such as moments of the distribution function, to be computed with respect to many parameters from the solution of only two linear systems. This reduces the cost of computing the gradient to the point that the finite-collisionality neoclassical fluxes can be used within an optimization loop. With the neoclassical adjoint method, we compute solutions of the drift kinetic equation and an adjoint drift kinetic equation to obtain derivatives of neoclassical quantities with respect to geometric parameters. When the number of parameters in the derivative is large ( $O(10^{2})$ ), this adjoint method provides up to a factor of 200 reduction in cost. We demonstrate adjoint-based optimization of the field strength to obtain minimal bootstrap current on a surface. With adjoint-based derivatives, we also compute the local sensitivity to magnetic perturbations on a flux surface and identify regions where tight tolerances on error fields are required for control of the bootstrap current or radial transport. Moreover, the solve for the ambipolar electric field is accelerated using a Newton method with derivatives obtained from the adjoint method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Self‐Consistent Convolutional Density Functional Approximations: Application to Adsorption at Metal Surfaces

The exchange-correlation (XC) functional in density functional theory is used to approximate multi-electron interactions. A plethora of different functionals are available, but nearly all are based on the hierarchy of inputs commonly referred to as “Jacob's ladder.” This paper introduces an approach to construct XC functionals with inputs from convolutions of arbitrary kernels with the electron density, providing a route to move beyond Jacob's ladder. We derive the variational derivative of these functionals, showing consistency with the generalized gradient approximation (GGA), and provide equations for variational derivatives based on multipole features from convolutional kernels. A proof-of-concept functional, PBEq, which generalizes the PBEα framework with mathematical equation being a spatially-resolved function of the monopole of the electron density, is presented and implemented. It allows a single functional to use different GGAs at different spatial points in a system, while obeying PBE constraints. Analysis of the results underlines the importance of error cancellation and the XC potential in data-driven functional design. After testing on small molecules, bulk metals, and surface catalysts, the results indicate that this approach is a promising route to simultaneously optimize multiple properties of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Synthetic biology for microbial production of lipid-based biofuels

The risks of maintaining current CO 2 emission trends have led to interest in producing biofuels using engineered microbes. Microbial biofuels reduce emissions because CO 2 produced by fuel combustion is offset by CO2 captured by growing biomass, which is later used as feedstock for biofuel fermentation. Hydrocarbons found in petroleum fuels share striking similarity with biological lipids. Here in this paper we review synthetic metabolic pathways based on fatty acid and isoprenoid metabolism to produce alkanes and other molecules suitable as biofuels. Lastly, we further discuss engineering strategies to optimize engineered biosynthetic routes, as well as the potential of synthetic biology for sustainable manufacturing.

09 BIOMASS FUELS↗
DOE OSTI2021

Visualizing plant cell wall changes proves the superiority of hydrochloric acid over sulfuric acid catalyzed γ-valerolactone pretreatment

Thermochemical pretreatment is one of the key steps to process lignocellulosic biomass for production of biofuels and biomaterials. γ-valerolactone (GVL) has been used as a green and renewable solvent to efficiently dissolve lignin under acidic conditions and enhance subsequent enzyme digestibility. Further improvement is still required to lower the pretreatment temperature in order to reduce sugar degradation and irreversible lignin condensation, as well as the capital cost. In this study, we compared the use of HCl and H 2 SO 4 as catalysts during GVL pretreatment, and found the performance of GVL-HCl at 100 °C was comparable to that of GVL-H 2 SO 4 at 120 °C in terms of xylan and lignin removal and enzyme digestibility. We further monitored the lignin removal and cellulose accessibility in the cell walls at different pretreatment time points by imaging the changes in lignin auto-fluorescence and in CtCBM3-GFP binding with confocal laser scanning microscopy (CLSM), respectively. We found GVL-HCl pretreatment at a relative low temperature (100 °C) could rapidly remove lignin in the compound middle lamella and cell corner areas, which concurred with the increase of CtCBM3-GFP binding in these areas. Real-time imaging of cell wall degradation by cellulases further revealed that the secondary cell walls could be digested from both cell lumen and CML sides, and eventually fully deconstructed within 24 h. Furthermore, our results provide new insight into the effects of chloride anions on plant cell wall structure during GVL pretreatment, and offer potential routes to further optimize and enhance the efficiency of GVL-based pretreatment.

09 BIOMASS FUELS↗