Search NASA⌕ Search

SEARCH · Search NASA

Results for “simultaneous 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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

Optimal Adsorbents for Low-Cost Storage of Natural Gas and Hyd: Computational Identification, Experimental Demonstration, and System-Level Projection

This research program will develop best-in-class natural gas (NG) and hydrogen adsorbents based on metal-organic frameworks (MOFs). More specifically, high-throughput computational screening coupled to machine learning will be used to identify MOFs that simultaneously achieve high usable gravimetric and volumetric capacities for methane and hydrogen. The most promising materials pinpointed by computation will be synthesized and characterized experimentally. In addition, the final stage of the project will critically evaluate the use of methane as a model for NG and consider which structural features are most important in making a viable NG storage system.

03 NATURAL GAS↗
DOE OSTI2023

Engineering chirality at wafer scale with ordered carbon nanotube architectures

Creating artificial matter with controllable chirality in a simple and scalable manner brings new opportunities to diverse areas. Here we show two such methods based on controlled vacuum filtration - twist stacking and mechanical rotation - for fabricating wafer-scale chiral architectures of ordered carbon nanotubes (CNTs) with tunable and large circular dichroism (CD). By controlling the stacking angle and handedness in the twist-stacking approach, we maximize the CD response and achieve a high deep-ultraviolet ellipticity of 40 ± 1 mdeg nm -1 . Our theoretical simulations using the transfer matrix method reproduce the experimentally observed CD spectra and further predict that an optimized film of twist-stacked CNTs can exhibit an ellipticity as high as 150 mdeg nm -1 , corresponding to a g factor of 0.22. Furthermore, the mechanical rotation method not only accelerates the fabrication of twisted structures but also produces both chiralities simultaneously in a single sample, in a single run, and in a controllable manner. The created wafer-scale objects represent an alternative type of synthetic chiral matter consisting of ordered quantum wires whose macroscopic properties are governed by nanoscopic electronic signatures and can be used to explore chiral phenomena and develop chiral photonic and optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Parallel high-frequency magnetic sensing with an array of flux transformers and multi-channel optically pumped magnetometer for hand MRI application

Here, we investigate an approach for parallel high-frequency magnetic sensing based on a multi-channel radio frequency (RF) optically pumped magnetometer (OPM) coupled to multiple flux transformers (FTs) with a focus on hand magnetic resonance imaging (MRI) application at ultra-low field (ULF). Multiple RF OPM sensing channels are realized by using a single large-area alkali-metal vapor cell and two laser beams for pumping and probing, shared for all the channels. This design leads to significant cost reduction when multi-channel sensing is desirable, as in the case of ULF MRI. The FT, composed of two connected coils, serves as a transmitter of a target magnetic field to the OPM, while decoupling the OPM from untargeted magnetic fields in the sensing area that can limit the OPM performance. For hand MRI application, theoretical and numerical analysis is performed to determine an optimal geometry for the FT array that could improve signal-to-noise ratio (SNR) and sufficiently reduce crosstalk between FTs. We estimate that the optimized multi-channel FT-OPM sensor can achieve a magnetic field sensitivity of the order of 1 fT / Hz 1 / 2 above 100 kHz, which would be sufficient for 1 mm resolution MRI. In general, the multi-channel capability enables simultaneous magnetic measurements, thus reducing the sensing time and improving the SNR, and we anticipate many applications of the multi-channel FT-OPM sensor beyond the targeted here hand MRI: anatomical parallel ULF MRI of the human brain and other parts of the body, airport security screening, magnetic material imaging, and many others.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers

Abstract This work presents the PORTALS framework (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), which leverages surrogate modeling and optimization techniques to enable the prediction of core plasma profiles and performance with nonlinear gyrokinetic simulations at significantly reduced cost, with no loss of accuracy. The efficiency of PORTALS is benchmarked against standard methods, and its full potential is demonstrated on a unique, simultaneous 5-channel (electron temperature, ion temperature, electron density, impurity density and angular rotation) prediction of steady-state profiles in a DIII-D ITER Similar Shape plasma with GPU-accelerated, nonlinear CGYRO (Candy et al 2016 J. Comput. Phys. 324 73–93). This paper also provides general guidelines for accurate performance predictions in burning plasmas and the impact of transport modeling in fusion pilot plants studies.

Physics↗
DOE OSTI2022

Electronic and vibrational properties of bulk Cr 2 Ge 2 Te 6 from first-principles calculations

Here we use density functional theory based ab initio calculations to investigate the structural, vibrational, magnetic, and electronic properties of the layered ferromagnet Cr 2 Ge 2 Te 6 (CGT) that has attracted attention for potential spintronic applications. We optimize the structure for a fixed c/a ratio. Our results are in excellent agreement with experimental data on structure, phonons, and electronic properties. The use of van der Waals interactions and relativistic spin-orbit coupling yields accurate lattice constants and interlayer distances. Simultaneously, the adopted theoretical methods lead to a rigorous description of the vibrational normal modes, as well as the valence bands, that are in excellent agreement with Raman spectroscopy and angle-resolved photoemission spectroscopy spectra, respectively. The magnetic moment is slightly overestimated, and the magnetic anisotropy has the correct sign but is greater in magnitude than that in experiment. We find that inclusion of the on-site Coulomb repulsion on Cr−3d orbitals worsens agreement with experiment, in contrast to previous studies. Our results provide a path toward ab initio analysis of magnetic heterostructures based on CGT.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Hierarchical Volt-var Optimization with Discrete Variables in Unbalanced Distribution Systems

This paper proposes a framework to determine the optimal active and reactive power dispatch of distributed photovoltaic (PV) generation, switched capacitors, and voltage regulators in multi-phase unbalanced distribution systems. The objectives of the optimal dispatch are minimization of the energy loss, PV real power curtailment, and switching operations of capacitors and voltage regulators, in addition to elimination of voltage violation and reverse power flow. The optimization problem is formulated in rectangular coordinates as a nonlinear, nonconvex problem with discrete variables. A hierarchical twostage framework is proposed to effectively handle those discrete variables and reduce the computational time compared to the unified approach in which all variables are solved simultaneously. The efficacy of the proposed approach and the accuracy of the obtained numerical solution is validated using the unbalanced multi-phase IEEE 34-bus with 15-minute load and PV data.

Nguyen, Quan H.↗
DOE OSTI2025

The Spectroscopic Stage-5 Experiment

The existence, properties, and dynamics of the dark sectors of our universe pose fundamental challenges to our current model of physics, and large-scale astronomical surveys may be our only hope to unravel these long-standing mysteries. In this white paper, we describe the science motivation, instrumentation, and survey plan for the next-generation spectroscopic observatory, the Stage-5 Spectroscopic Experiment (Spec-S5). Spec-S5 is a new all-sky spectroscopic instrument optimized to efficiently carry out cosmological surveys of unprecedented scale and precision. The baseline plan for Spec-S5 involves upgrading two existing 4-m telescopes to new 6-m wide-field facilities, each with a highly multiplexed spectroscopic instrument capable of simultaneously measuring the spectra of 13,000 astronomical targets. Spec-S5, which builds and improves on the hardware used for previous cosmology experiments, represents a cost-effective and rapid approach to realizing a more than 10$\times$ gain in spectroscopic capability compared to the current state-of-the-art represented by the Dark Energy Spectroscopic Instrument project (DESI). Spec-S5 will provide a critical scientific capability in the post-Rubin and post-DESI era for advancing cosmology, fundamental physics, and astrophysics in the 2030s.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Fuel Properties and Kinetics

The Co-Optimization of Fuels and Engines (CoOptima) program is focused on a two-pronged approach to develop new, lower net-carbon fuels and advanced engine technologies in tandem. This effort brings nine national labs and several university and industry partners together to simultaneously identify new fuel candidates and to further engine technology development in the light-, medium-, and heavy-duty vehicle sectors with a focus on fuel economy and emission reduction. The fuel properties and kinetics project is aimed at achieving a better understanding of fuel property kinetics and how they impact engine performance such that more efficient and lower emitting engines can be made a reality. Several promising biofuel candidates were identified through tiered screening approaches and were evaluated utilizing unique bench-scale measurement techniques. Kinetic models were developed to describe autoignition and soot pre-cursor formation mechanisms to identify the most promising candidates that advanced various combustion strategies.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Plastic Parallel Pathways Platform - 4P Model

Global momentum is building towards a circular economy capable of keeping plastics in use and out of waste streams. Given that 79% of all plastic produced since 1950 has accumulated in landfills or the natural environment,rapid implementation of various end-of-life (EoL) management technologies will be needed to reach this target. However, it can be challenging to develop an effective plastic EoL strategy when the available options - chemical or molecular recycling, energy recovery, upcycling, downcycling, closed-loop (plastic-to-plastic) or open-loop (plastic-to-x) recycling, among others - can generate products ranging from low-grade to virgin-quality plastic and from fuels to value-added chemicals. We present a flexible material flow model capable of analyzing the effects of both plastic-to-plastic and plastic-to-x EoL management strategies on the U.S. PET economy. This Plastic Parallel Pathways Platform (4P) assesses the environmental impacts, costs, and circularity of a PET system in which waste is managed through six potential EoL pathways: landfill, incineration with energy recovery, pyrolysis to fuel oil, upcycling to glass fiber reinforced plastic (GFRP), mechanical recycling to low-grade PET, and chemical recycling (glycolysis) to bottle-grade PET. We compare the pathways across multiple metrics using multi-criteria decision analysis (MCDA) and then use a brute force algorithm to predict an optimal combination of EoL pathways to minimize greenhouse gas (GHG) emissions and costs and maximize circularity. This work highlights the need to implement a diverse portfolio of EoL strategies in parallel to enable a PET economy that meets environmental, economic, and circularity requirements simultaneously.

downcycling↗
DOE OSTI2023

Rheo-electric measurements of carbon black suspensions containing polyvinylidene difluoride in N -methyl-2-pyrrolidone

Lithium-ion battery cathode slurries have a microstructure that depends sensitively on how they are processed due to carbon black's (CB) evolving structure when subjected coating flows. While polyvinylidene difluoride (PVDF), one of the main components of the cathode slurry, plays an important role in modifying the structure and rheology of CB, a quantitative understanding is lacking. In this work, we explore the role of PVDF in determining the structural evolution of Super C65 CB in N-methyl-2-pyrrolidinone (NMP) with rheo-electric measurements. We find that PVDF enhances the viscosity of NMP resulting in a more extensive structural erosion of CB agglomerates with increasing polymer concentration and molecular weight. We also show that the relative viscosity of all suspensions can be collapsed by the fluid Mason number (Mnf), which compares the hydrodynamic forces imposed by the medium to cohesive forces holding CB agglomerates together. Using simultaneous rheo-electric measurements, we find at high Mnf, the dielectric strength (Δε) scales with Mnf, and the power-law scaling can be quantitatively predicted by considering the self-similar break up of CB agglomerates. The collapse of the relative viscosity and scaling of Δε both suggest that PVDF increases the hydrodynamic force of the suspending medium without directly changing the CB agglomerate structure. These findings are valuable for optimizing the rheology of lithium ion battery cathode slurries. We also anticipate that these findings can be extended to understand the microstructure of similar systems under flow.

Mechanics↗
DOE OSTI2025

Dual‐Functional High‐Entropy Polymer Exhibiting Giant Cross‐Energy Couplings at Low Fields

A key component of cooling devices is the transfer of entropy from the cold load to heat sink. An electrocaloric (EC) polymer capable of generating both large electrocaloric effect (ECE) and substantial electroactuation can enable EC cooling devices to pump heat without external mechanisms, resulting in compact designs and enhanced efficiency. However, achieving both high ECE and significant electroactuation remains challenging. Herein, it is demonstrated that poly(vinylidene fluoride‐trifluoroethylene‐chlorofluoroethylene‐double bond) [P(VDF‐TrFE‐CFE‐DB)] tetrapolymers can simultaneously generate high electrocaloric effects and electroactuations under low fields. These P(VDF‐TrFE‐CFE‐DB) tetrapolymers are synthesized through the dehydrochlorination of P(VDF‐TrFE‐CFE) terpolymer. By facile tuning the composition of the initial terpolymer to avoid pure relaxor state, tetrapolymers with optimal DB compositions are achieved, near the critical endpoint of normal ferroelectric phase with diffused phase transition. The nearly vanishing energy barriers between the nonpolar to polar phases result in a strong electrocaloric response and significant electroactuation. Specifically, the P(VDF‐TrFE‐CFE‐DB) tetrapolymer exhibits an EC entropy change Δ S of 100 J kg −1 K −1 under 100 MV m −1 : comparable to state‐of‐the‐art (SOA) EC polymers, while delivering nearly twice the electroactuation of the SOA EC polymers. This work presents a general strategy for developing EC materials that combine large electrocaloric effect and electroactuation at low electric fields.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mechanistic insights into structural parameters maximizing energy storage density in Si mesoporous electrodes for Li-ion batteries

Mesoporous Si electrodes have an interesting set of structural parameters, which, when carefully optimized, can lead to ultrahigh energy density Si electrodes for Li-ion batteries. We present here in this paper details of a systematic research leading to the discovery of an “ideal” structure of mesoporous Si electrode, which results in exceptional cracking/damage resistance, while simultaneously having very high specific (>2000 mAh g-1) and total (>1.5 mAh cm-2) capacities for large number of cycles. The electrodes near the “ideal” value of the characteristic structural parameter (the ratio of Si wall thickness to pore diameter) are free from first-cycle capacity degradation, and are efficient in accommodating the volume changes during lithiation by uniformly filling up the porous space between Si walls. Interestingly, these electrodes are also found to be structurally damage-resistant, surviving through many lithiation-delithiation cycles. Using charge-discharge cycling and electron microscopy we show that ideal structure is the key for achieving ultrahigh energy storage density in Si mesoporous electrodes for Li-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Bifunctional nanoprecipitates strengthen and ductilize a medium-entropy alloy

Single-phase high- and medium-entropy alloys with face-centred cubic (fcc) structure can exhibit high tensile ductility and excellent toughness, but their room-temperature strengths are low. Dislocation obstacles such as grain boundaries, twin boundaries, solute atoms and precipitates can increase strength. However, with few exceptions, such obstacles tend to decrease ductility. Interestingly, precipitates can also hinder phase transformations. Here, using a model, precipitate-strengthened, Fe–Ni–Al–Ti medium-entropy alloy, we demonstrate a strategy that combines these dual functions in a single alloy. The nanoprecipitates in our alloy, in addition to providing conventional strengthening of the matrix, also modulate its transformation from fcc-austenite to body-centred cubic (bcc) martensite, constraining it to remain as metastable fcc after quenching through the transformation temperature. During subsequent tensile testing, the matrix progressively transforms to bcc-martensite, enabling substantial increases in strength, work hardening and ductility. This use of nanoprecipitates exploits synergies between precipitation strengthening and transformation-induced plasticity, resulting in simultaneous enhancement of tensile strength and uniform elongation. Further, our findings demonstrate how synergistic deformation mechanisms can be deliberately activated, exactly when needed, by altering precipitate characteristics (such as size, spacing, and so on), along with the chemical driving force for phase transformation, to optimize strength and ductility.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advanced Compact Generation Module with Fish Safe Runner Technology

Hydropower is an important contributor of stable, load-leveling renewable energy to our national grid. Increasingly, the development of new hydropower facilities or the retrofit of existing ones hinges not only on minimizing costs but also environmental impact. In this report, the analysis and testing of a modular and scalable low-head hydropower generation design using Natel Energy’s Restoration Hydro Turbine is described. This design leverages many established industry approaches for compactness and efficiency while simultaneously allowing for safe downstream fish passage through the turbines themselves. This unique approach reduces overall hydropower facility costs and enables a simpler inclusive method of project design and operation. To assess this design, mechanical and fluid computational analyses were used to study and optimize key parameters. Passage tests of important migratory species (salmonids, American eel) were conducted through representative turbines. The unique propeller geometry of the fish-safe Restoration Hydro Turbine was subjected to detailed design and testing using advanced manufacturing composite techniques. Comprehensive module cost models were developed and assessed alongside hydraulic efficiency. The results of this project show promising and economical applications for downstream passage offish through Restoration Hydro Turbine modules.

13 HYDRO ENERGY↗
DOE OSTI2024

Techno-Economic Optimization of a Solvent Absorption Process for CO2 Capture with 3D-Printed Intensified Packing

Presentation given at the 2024 annual AICHE meeting held October 27-31, 2024. The presentation focuses on modeling performance and economics of a solvent absorption system for CO2 capture with towers utilizing intensified packing. The packing is an alternative to traditional structured packing by incorporating cooling channel for simultaneous mass and heat transfer.

Summits, Stephen↗
DOE OSTI2025

A Novel Gene Stacking Method in Plant Transformation Utilizing Split Selectable Markers

Gene stacking, the process of introducing multiple genes into a single plant to enhance desired traits, is essential for plant genetic improvement through both conventional breeding and genetic transformation. In general, transformation-based gene stacking can be achieved through either co-transformation to simultaneously introduce multiple genes or sequential multi-round transformation. While co-transformation is generally faster and more efficient than sequential multi-round transformation, it often requires two selectable marker genes, which confer resistance to antibiotics, for selecting transgenic events. However, in most cases, there is only one best selectable marker gene for a specific plant species or genotype. Also, it is harder to optimize the concentrations of two antibiotics for co-transformation than using one antibiotic for selecting transgenic events. To overcome this challenge, we recently developed an innovative split selectable marker system for plant co-transformation, allowing the use of one selectable marker gene to select transgenic events. This method involves constructing two binary vectors, each carrying a subset of genes of interest and a partial fragment of the selectable marker gene, which is connected to a partial intein fragment. Following Agrobacterium -mediated co-transformation, plants harboring both binary vectors are selected using a single antibiotic, such as kanamycin. This split-marker system can be used to co-transform multiple genes into both herbaceous and woody plants, accelerating genetic improvement of polygenic traits or integrative improvement of multiple traits to simultaneously increase crop yield and quality.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials science, and engineering. Multispectral QPI measures quantitative phase information across multiple spectral bands, permitting the examination of wavelength‐specific phase and dispersion characteristics of samples. Herein, the design of a diffractive processor is presented that can all‐optically perform multispectral quantitative phase imaging of transparent phase‐only objects within a snapshot. The design utilizes spatially engineered diffractive layers, optimized through deep learning, to encode the phase profile of the input object at a predetermined set of wavelengths into spatial intensity variations at the output plane, allowing multispectral QPI using a monochrome focal plane array. Through numerical simulations, diffractive multispectral processors are demonstrated to simultaneously perform quantitative phase imaging at 9 and 16 target spectral bands in the visible spectrum. The generalization of these diffractive processor designs is validated through numerical tests on unseen objects, including thin Pap smear images. Due to its all‐optical processing capability using passive dielectric diffractive materials, this diffractive multispectral QPI processor offers a compact and power‐efficient solution for high‐throughput quantitative phase microscopy and spectroscopy.

36 MATERIALS SCIENCE↗