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Results for “coordinated optimization”

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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Theory underlying CRM training: Psychological issues in flight crew performance and crew coordination

What psychological theory and research can reveal about training in Cockpit Resource Management (CRM) is summarized. A framework is provided for the critical analysis of current approaches to CRM training. Background factors and definitions critical to evaluating CRM are reviewed, followed by a discussion of issues directly related to CRM training effectiveness. Some of the things not known about the optimization of crew performance and the research needed to make these efforts as effective as possible are described.

Helmreich, Robert L.↗
DOE OSTI2018

Mechanically Robust, Sodium-Ion Conducting Membranes for Nonaqueous Redox Flow Batteries

Sodium-based batteries are promising for grid-storage applications because of significantly lower cost compared to lithium-based systems. The advancement of solid-state and redox-flow sodium-ion batteries requires sodium-ion exchange membranes with high conductivity, electrochemical stability, and mechanical robustness. This study demonstrates that membranes based on poly(ethylene oxide) (PEO) can meet these requirements. Membranes plasticized with tetraethylene glycol dimethyl ether (TEGDME) achieve high ionic conductivity. Plasticized PEO membranes containing sodium triflate salt (NaTFS) show about 2 orders of magnitude higher conductivity compared to nonplasticized PEO membranes. Results from vibrational spectroscopy and differential scanning calorimetry describe the coordination chemistry in these multiphase materials and explain the mechanisms behind the increased conductivity. The mechanical properties of the membranes improve by addition of 5 wt % sodium carboxymethyl cellulose (CMC) without compromising the conductivity or electrochemical stability against sodium metal. In conclusion, the optimized membrane is an excellent candidate for low-cost energy storage systems that operate over a wide voltage window near ambient temperature.

25 ENERGY STORAGE↗
DOE OSTI2026

Electrospun Ti–Zr Oxide Heterostructures Enable Strongly Anchored Ultralow-Ir Anodes for Durable Acidic Oxygen Evolution

Proton-exchange-membrane water electrolysis (PEMWE) requires acidic oxygen-evolution-reaction (OER) anodes that combine high activity, high durability, and low Ir loading. Here, we report a Ti-Zr composite electrospun oxide (ESO) nanorod support that enables ultralow-Ir anodes for high-performance PEMWE. Zr-containing Ti oxide heterostructures stabilize anatase-rich TiO2, tune the local oxygen-coordination environment, and strengthen interfacial anchoring of IrOx under acidic anodic conditions. The electrospun nanorod network further creates an open, mechanically coherent catalyst layer that improves Ir utilization, ionomer penetration, and mass transport. At an anode loading of 0.2 mgIr cm-2, the optimized Ir/TiZr20-ESO anode delivers a PEMWE mass activity of 0.99 A mgIr-1 at 1.45 V, 28.3 and 43.0 times higher than commercial Ir black and commercial IrO2/TiO2, respectively. The same anode reaches 3.0 and 4.0 A cm-2 at 1.75 and 1.83 V, respectively, and sustains 2000 h operation at 2.0 A cm-2. Also, accelerated stress tests up to 525 hours over 31,500 cycles confirm promising long-term durability, with an insignificant performance decay of 0.4 μV per cycle. Density functional theory indicates that the Ti-Zr oxide heterostructure suppresses Ti demetallation and strengthens IrO2 interfacial binding, rationalizing the improved high-current-density stability.

25 ENERGY STORAGE↗
DOE OSTI2025

An improved guess for the variational calculation of charge-transfer excitations in large systems

Ab initio quantum-chemical methods that perform well for computing the electronic ground state are not straightforwardly transferable to electronically excited states, particularly in large molecular systems. Wave function theory offers high accuracy, but is often prohibitively expensive. Methods based on time-dependent density functional theory (TD-DFT) are crucially sensitive to the chosen exchange-correlation functional (XCF) parameterization, and system-specific tuning protocols were therefore proposed to address the method's robustness. Methods based on the variational relaxation of the excited-state electron density showcased promising results for the calculation of charge-transfer excitations, but the complex shape of the electronic hypersurface makes convergence to a specific excited state much more difficult than for the ground state when standard variational techniques are applied. We address the latter aspect by providing suitable initial guesses, which we obtain by two separate constrained algorithms. Combined with the squared-gradient minimization algorithm for all-electrons relaxation in a freeze-and-release scheme (FRZ-SGM), we demonstrate that orbital-optimized density functional theory (OO-DFT) calculations can reliably converge to the charge-transfer states of interest even for large molecular systems. We test the FRZ-SGM method on a phenothiazine-anthraquinone CT excitation in a supramolecular Pd(II) coordination cage complex as a function of the cage conformation. This compound has been studied experimentally prior to our work. We compare this freeze-and-release scheme to two XCF reparameterizations, which were recently proposed as low-cost TD-DFT-based alternatives to variational methods. Two dye-semiconductor complexes, which were previously investigated in the context of photovoltaic applications, serve as a second example to investigate the convergence and stability of the FRZ-SGM approach. Our results demonstrate that FRZ-SGM provides reliable convergence for charge-transfer excited states and avoids variational collapse to lower-lying electronic states, whereas time-dependent DFT calculations with an adequate tuning procedure for the range-separation parameter provide a computationally efficient initial estimate of the corresponding energies, with a computational cost comparable to that of configuration-interaction singles (CIS) calculations.

Bogo, Nicola↗
DOE OSTI2024

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗
NASA NTRS1996

Displacement Energies for Nanorods

The geometries have been optimized and harmonic frequencies computed for three small hydrocarbon rods. The two lowest unique frequencies correspond to a torsion and a bend of the rods. The energy to bend or twist the rods has been computed by adding a fraction of the normal coordinate corresponding to these two modes to the equilibrium geometry. The density functional theory (using B3LYP) and self-consistent field (SCF) results are very similar for all properties considered.

Bauschlicher, Charles W., Jr.↗
NASA NTRS2004

A Survey of Collectives

Due to the increasing sophistication and miniaturization of computational components, complex, distributed systems of interacting agents are becoming ubiquitous. Such systems, where each agent aims to optimize its own performance, but where there is a well-defined set of system-level performance criteria, are called collectives. The fundamental problem in analyzing/designing such systems is in determining how the combined actions of self-interested agents leads to 'coordinated' behavior on a iarge scale. Examples of artificial systems which exhibit such behavior include packet routing across a data network, control of an array of communication satellites, coordination of multiple deployables, and dynamic job scheduling across a distributed computer grid. Examples of natural systems include ecosystems, economies, and the organelles within a living cell. No current scientific discipline provides a thorough understanding of the relation between the structure of collectives and how well they meet their overall performance criteria. Although still very young, research on collectives has resulted in successes both in understanding and designing such systems. It is eqected that as it matures and draws upon other disciplines related to collectives, this field will greatly expand the range of computationally addressable tasks. Moreover, in addition to drawing on them, such a fully developed field of collective intelligence may provide insight into already established scientific fields, such as mechanism design, economics, game theory, and population biology. This chapter provides a survey to the emerging science of collectives.

Tumer, Kagan↗
NASA NTRS2017

Waveguide Modulator for Interference Tolerant Functional Near Infrared Spectrometer (fNIRS)

Many crew-related errors in aviation and astronautics are caused by hazardous cognitive states including overstress, disengagement, high fatigue and ineffective crew coordination. Safety can be improved by monitoring and predicting these cognitive states in a non-intrusive manner and designing mitigation strategies. Measuring hemoglobin concentration changes in the brain with functional Near Infrared Spectroscopy is a promising technique for monitoring cognitive state and optimizing human performance during both space and aviation operations. A compact, wearable fNIRS system would provide an innovative early warning system during long duration missions to detect and prevent vigilance decrements in pilots and astronauts. This effort focused on developing a waveguide modulator for use in a fNIRS system.

spectroscopy↗
DOE OSTI2020

Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI-XFC)

Increasing vehicle electrification will require extensive use of extreme fast charging (XFC), especially for larger vehicles. Uncoordinated XFC can create grid challenges, particularly at the distribution level. Two strategies can support widespread XFC: gold-plate the grid (i.e., upgrade all systems to enable worst-case, fully coincident loads) or use integrated planning to codesign a smart system based on advanced controls that leverage load flexibility and distributed energy resources. With the right design and control, XFC can simultaneously support both mobility and grid operations. Fully realizing the potential of XFC, however, will require unprecedented coordination among the charging infrastructure, grid, and vehicles. GEMINI-XFC combines high-fidelity grid and transport modeling at an unprecedented level of resolution and codesigns a smart system based on advanced controls that leverage load flexibility and distributed energy resources to optimize the integration of extreme fast charging (XFC) across a full regional scale with individual customer resolution.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Management of Risk and Uncertainty Through Optimized Co-Operation of Transmission Systems and Microgrids With Responsive Loads (Final Report)

The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. Ambitious national and state-level goals around the decarbonization of electricity relies on the integration of very high levels of renewable resources, most of which are variable and intermittent. The use of demand response is an ideal approach to counterbalance the intermittency of renewable generation and brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. Demand-side participation cannot be leveraged effectively without explicitly including the distribution system dynamics in the optimization-based wholesale market operations. This project grew from a vision for co-optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy management system of the lower voltage system (distribution or microgrid) can also sell (buy) excess (necessary) energy from the transmission system. Until recently, very little research had been conducted on the co-optimization of these two systems due to computational limitations. However, advances in computational capabilities, and the judicious use of decomposition methods and innovative approximation methods for high-dimension dynamic programming made this goal a viable objective for this project, leading to a fundamental shift in the ability to integrate and fully utilize demand-side resources. To this end, the modeling framework developed introduces a novel co-optimization framework, to include the operations of both the transmission and distribution systems (or microgrids) in operational decision making. This framework was used to analyze renewable and distributed generation along with responsive demand and to compare the capability of co-optimized systems to perform with higher levels of variable renewables. An ideal microgrid is defined as an electric entity capable of operating in both interconnected (with the high-voltage grid) and islanded mode. As such, the microgrid should incorporate generating units (traditional units and intermittent) and if needed, exchange power with the high-voltage grid. The interplay between the microgrid and high-voltage grid motivated the development of the co-optimization approach to ensure efficient performance of the interconnected network. Results show that the use of a bi-level optimization approach is an appropriate structure, capable of co-optimizing a transmission system with multiple distribution systems and microgrids. While increasing the number of connected systems provides increasing flexibility for renewables integration this can also the economic benefits to the low-voltage subsystems with each additional system connected. Comparison of a traditional single-level decision structure with the co-optimization approach illustrates a reduction in overall system cost under co-optimization, while specific cost allocations to transmission and distribution systems are changed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Innovative Open-Source Energy Software to Drive and Enable Energy Savings and Process Optimization

U.S. Department of Energy (DOE) energy system-analysis software tools have been used for years helping to identify over 170 TBTU/year of energy savings through the Save Energy Now “Energy Savings Assessment” and Better Plants “In-Plant Training” Programs. While most of the fundamental energy savings opportunities do not evolve much with time, computer technology never stops, leaving most of these software tools inoperable on modern computers.This has sparked an initiative to revitalize the DOE energy system analysis tools into a new, open-source, integrated software tool suite - MEASUR. Designed for industrial energy coordinators, engineers, utility-program implementers and individuals who are interested in improving system efficiency, MEASUR can aide users in identifying, assessing, and quantifying energy savings opportunities within pump, fan, process heating, steam, motors, and compressed air systems. In addition, the software contains over 40 equipment and property calculators for simple energy-related calculations and analyses.This paper will present a results comparison for each energy-consuming system using data from past DOE-sponsored energy assessments (to establish the accuracy of the savings algorithms) to validate and verify the accuracy of the energy and cost savings calculated by MEASUR. Additionally, an example highlighting 3rd-party development of the tool’s opensource framework into real-time sensor systems and efficiency-optimization will be presented.

Armstrong, Kristina↗
DOE OSTI2023

Simultaneous Improvements in Efficiency and Stability of Organic Solar Cells via a Symmetric‐Asymmetric Dual‐Acceptor Strategy

Abstract Simultaneously achieving improvements in power conversion efficiency (PCE) and stability is the main task of the current development stage of organic solar cells (OSCs). This work reports a symmetry–asymmetry dual‐acceptor (SADA) strategy to construct ternary devices, which is found to be feasible for increasing both the PCE and the operational lifetime of OSCs. In this contribution, the symmetric acceptor L8‐BO and the asymmetric acceptor BTP‐S9 are blended in equal proportions with polymer donor PM6 for the consideration of absorption spectrum complementarity and cascade energetic alignment. In addition, the features of crystallinity and miscibility of the dual‐acceptor deliver optimized morphology lead to a high PCE of 18.84%. In addition, the asymmetric acceptor BTP‐S9 with a larger dipole moment shows tighter molecular stacking and longer crystal correlation length, which favor intrinsic molecular photostability, and further consolidate the operational lifetime of OSCs when coordinated with L8‐BO. This work demonstrates the efficacy of the SADA strategy for constructing efficient and stable OSCs.

Chemistry↗
DOE OSTI2022

Atomically Dispersed Dual‐Metal Site Catalysts for Enhanced CO 2 Reduction: Mechanistic Insight into Active Site Structures

Abstract Carbon‐supported nitrogen‐coordinated single‐metal site catalysts (i.e., M−N−C, M: Fe, Co, or Ni) are active for the electrochemical CO 2 reduction reaction (CO 2 RR) to CO. Further improving their intrinsic activity and selectivity by tuning their N−M bond structures and coordination is limited. Herein, we expand the coordination environments of M−N−C catalysts by designing dual‐metal active sites. The Ni‐Fe catalyst exhibited the most efficient CO2RR activity and promising stability compared to other combinations. Advanced structural characterization and theoretical prediction suggest that the most active N‐coordinated dual‐metal site configurations are 2N‐bridged (Fe‐Ni)N 6 , in which FeN 4 and NiN 4 moieties are shared with two N atoms. Two metals (i.e., Fe and Ni) in the dual‐metal site likely generate a synergy to enable more optimal *COOH adsorption and *CO desorption than single‐metal sites (FeN 4 or NiN 4 ) with improved intrinsic catalytic activity and selectivity.

Li, Yi↗
DOE OSTI2023

Changing Directions: Influence of Ligand Electronics on the Directionality and Kinetics of Photoinduced Charge Transfer in Cu(I)Diimine Complexes

A key challenge to the effective utilization of solar energy is to promote efficient photoinduced charge transfer, specifically avoiding unproductive, circuitous electron-transfer pathways and optimizing the kinetics of charge separation and recombination. We hypothesize that one way to address this challenge is to develop a fundamental understanding of how to initiate and control directional photoinduced charge transfer, particularly for earth-abundant first-row transition-metal coordination complexes, which typically suffer from relatively short excited-state lifetimes. Here, in this paper, we report a series of functionalized heteroleptic copper(I)bis(phenanthroline) complexes, which have allowed us to investigate the directionality of intramolecular photoinduced metal-to-ligand charge transfer (MLCT) as a function of the substituent Hammett parameter. Ultrafast transient absorption suggests a complicated interplay of MLCT localization and solvent interaction with the Cu(II) center of the MLCT state. This work provides a set of design principles for directional charge transfer in earth-abundant complexes and can be used to efficiently design pathways for connecting the molecular modules to catalysts or electrodes and integration into systems for light-driven catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Energy–Geometry Dependency of Molecular Structures: A Multistep Machine Learning Approach

There is growing interest in estimating quantum observables while circumventing expensive computational overhead for facile in silico materials screening. Machine learning (ML) methods are implemented to perform such calculations in shorter times. In this paper, we introduce a multistep method based on machine learning algorithms to estimate total energy on the basis of spatial coordinates and charges for various chemical structures, including organic molecules, inorganic molecules, and ions. This method quickly calculates total energy with 0.76 au in root-mean-square error (RMSE) and 1.5% in mean absolute percent error (MAPE) when tested on a database of optimized and unoptimized structures. Using similar molecular representations, experimental thermochemical properties were estimated, with MAPE as low as 6% and RMSE of 8 cal/mol·K for heat capacity in a 10-fold cross-validation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A National Roadmap for Grid-Interactive Efficient Buildings

The way electricity is generated and consumed in the US is quickly changing, including in terms of the rapid growth in variable power generation resources and the need for large-scale investments to replace aging infrastructure and modernize the grid. Buildings that coordinate electricity use with grid conditions are a flexible and cost-effective resource to address the evolving power system challenges. Outfitted with smart technologies, GEBs are energy-efficient buildings with smart technologies characterized by the active use of distributed energy resources to optimize energy use for grid services, occupant needs and preferences, and cost reductions in a continuous and integrated way. In doing so, GEBs can play a key role in promoting greater affordability, resilience, environmental performance, and reliability. The report finds that, over the next two decades, GEBs could deliver between $100 and $200 billion in savings to the US power system and cut CO 2 emissions by 80 million tons per year by 2030, or 6% of total power sector CO 2 emissions. The report also provides 14 recommendations for addressing the top barriers to overcome barriers to GEB adoption and deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1977

The navigation system of the JPL robot

The control structure of the JPL research robot and the operations of the navigation subsystem are discussed. The robot functions as a network of interacting concurrent processes distributed among several computers and coordinated by a central executive. The results of scene analysis are used to create a segmented terrain model in which surface regions are classified by traversibility. The model is used by a path planning algorithm, PATH, which uses tree search methods to find the optimal path to a goal. In PATH, the search space is defined dynamically as a consequence of node testing. Maze-solving and the use of an associative data base for context dependent node generation are also discussed. Execution of a planned path is accomplished by a feedback guidance process with automatic error recovery.

Thompson, A. M.↗