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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sizing and Location Selection of Medium‐Voltage Back‐to‐Back Converters for DER‐Dominated Distribution Systems

Medium‐voltage back‐to‐back (MVB2B) converters can connect two distribution systems and quantifiably transfer power between them. This function can enable the MVB2B converter to exchange distributed energy resource (DER)‐generated power between two systems and bring significant value to enhancing distribution system DER adoption. Our previous work analysed and demonstrated the value MVB2B converter can bring to DER integration. As continuous work, this paper presents a methodology that helps address the MVB2B converter sizing and location selection problem in distribution systems with high DER penetrations. The proposed methodology aims to address three critical problems for MVB2B converter implementation in the real world: (1) which distribution systems are better to be connected, (2) what converter size is appropriate for connecting the distribution systems, and (3) where the optimal connection points are in the systems for connecting the MVB2B converter. The proposed methodology has been demonstrated by case studies that include various scenarios involving distribution systems with different dominated load types and high photovoltaic penetrations. The results demonstrate that selecting the optimal converter size based on net revenue and time of return considerations leads to a balance between maximizing energy savings and minimizing financial payback periods. Furthermore, feeder pair selection based on load profile standard deviation effectively identifies systems that derive the greatest value from MVB2B integration. Finally, an optimized connection point selection approach using a voltage load sensitivity matrix ensures minimal system impact while facilitating efficient power exchange. These findings provide practical insights for the real‐world deployment of MVB2B converters to enhance DER hosting capacity and improve grid resilience.

14 SOLAR ENERGY↗
DOE OSTI2019

Tracking Excited States in Wave Function Optimization Using Density Matrices and Variational Principles

We introduce an approach for finding individual excited states' energy stationary points in complete active space self-consistent field theory that is compatible with standard optimization methods and highly effective at overcoming difficulties due to root flipping and near-degeneracies. Inspired by both the maximum overlap method and recent progress in excited-state variational principles, our approach combines these ideas in order to track individual excited states throughout the orbital optimization process. In a series of tests involving root flipping, near-degeneracies, charge transfers, and double excitations, we show that this approach is more effective for state-specific optimization than either the naive selection of roots on the basis of energy ordering or a more direct generalization of the maximum overlap method. We offer evidence that this state-specific approach improves the performance of complete active space perturbation theory for vertical excitation energies. Furthermore, we find that the state-specific optimization can help avoid state-averaging-induced discontinuities on potential energy surfaces. With a simple implementation, a low cost, and compatibility with large active space methods, the approach is designed to be useful in a wide range of excited-state investigations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

PHOTOMETRIC SELECTION OF A MASSIVE GALAXY CATALOG WITH z ≥ 0.55

We present the development of a photometrically selected massive galaxy catalog, targeting Luminous Red Galaxies (LRGs) and massive blue galaxies at redshifts of z⩾0.55. Massive galaxy candidates are selected using infrared/optical color–color cuts, with optical data from the Sloan Digital Sky Survey (SDSS) and infrared data from “unWISE” forced photometry derived from the Wide-field Infrared Survey Explorer (WISE). The selection method is based on previously developed techniques to select LRGs with z>0.5, and is optimized using receiver operating characteristic curves. The catalog contains 16,191,145 objects, selected over the full SDSS DR10 footprint. The redshift distribution of the resulting catalog is estimated using spectroscopic redshifts from the DEEP2 Galaxy Redshift Survey and photometric redshifts from COSMOS. Restframe U − B colors from DEEP2 are used to estimate LRG selection efficiency. Using DEEP2, the resulting catalog has an average redshift of z = 0.65, with a standard deviation of σ=2.0, and an average restframe of U−B=1.0, with a standard deviation of σ=0.27. Using COSMOS, the resulting catalog has an average redshift of z = 0.60, with a standard deviation of σ=1.8. We estimate 34% of the catalog to be blue galaxies with z⩾0.55. An estimated 9.6% of selected objects are blue sources with redshift z<0.55. Stellar contamination is estimated to be 1.8%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Chapter 6: Surrogate Model Guided Optimization Algorithms and Their Potential Use in Autonomous Experimentation

This chapter reviews the basics of derivative-free optimization methods based on surrogate models and outlines how these methods can straightforwardly be applied to autonomously steering experimentation. It summarizes general solution approaches that use surrogate models and active learning. Surrogate modeling is often combined with active learning strategies, where in each iteration of the optimization algorithm, the surrogate model is used to identify which new inputs should be evaluated next and given the new input-output pair, the surrogate model is updated. Regardless of feasibility, the surrogate models for the constraints are updated in each iteration of the optimization algorithm, while the surrogate model for the objective function is only updated when a feasible point has been found. Similarly to the case of computationally cheap constraints, the surrogate models of the constraints should be incorporated into the definition of the auxiliary optimization problem that is solved to select new sample points.

active learning↗
DOE OSTI2019

A GIS-Based Suitability Analysis of a Phytomanagment Strategy for TCE in Groundwater and Soil Niagara Falls Storage Site, New York - 19385

The large number of complexly contaminated sites throughout the nation has propagated the application of phytoremedial techniques in a wide array of environmental remediation strategies. The use and breeding of vegetation for the in-situ treatment of environmental media (soil, groundwater, sediment) contaminated with organic or inorganic contaminants has shown to provide a low-cost alternative to conventional means of remediating contaminated sites (e.g., groundwater extraction, chemical oxidation or reduction, bioremediation, excavation, etc.). One impediment to effective phytoremediation is the selection of proper plant-species, which is complicated due to the many variables that are required for plant-species viability (i.e. range of soil pH, annual precipitation values, depth to groundwater table, etc.). This study employed the use of a Geographic Information Systems (GIS) to first define the spatial extent of contaminated media (soil and groundwater) at a project site and then support an effective means to optimize phytoremediative techniques to manage these impacts prior to final remediation. Spatial analyses and analytical calculations were coupled to determine an optimal plant species and spacing to maximize the effectiveness of a phytomanagement plan. The incorporation of fuzzy membership functions and fuzzy overlay provide an innovative method to help select the optimal plant-species for phytomanagement planning. Fuzzy membership functions were used to represent the plant growth requirements and provided an intuitive method to represent the uncertainty associated with plant-growth requirements. The fuzzy overlay function then employed a raster-based suitability analysis that together provided decision makers with a scientific solution to optimally design a phytomanagement strategy for site-related volatile organic compound (VOC) impacts. The Niagara Falls Storage Site (NFSS) VOC-impacted groundwater is contained in clayey glacial sediments, which commonly are technically impractical to remediate. Prior on-site studies show that native poplar (cottonwood variants) preferentially translocate or phytoextract the VOCs from the site soils and thus provide a proven mechanism to manage the multi-media impacts. Consequently, the Army Corps of Engineers Buffalo District evaluated phytoremediative approaches as a passive tool to manage the VOCs during the project life cycle prior to final remediation. The fuzzy membership functions and fuzzy overlay modeling of candidate species narrowed the selection to an optimal species and subsequent transpiration modeling estimated the plant spacing for the overall phytomanagement plan. The method employed for this study is easy applied to other phytoremediative and phytomanagement actions derived from hazardous waste decision making. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Automated descriptor selection, volcano curve generation, and active site determination using the DescMAP software

The material space for catalyst discovery is expansive. Volcano curves are traditionally employed to provide physical insights into optimal catalyst characteristics for new material selection. Their generation lies on a single descriptor picked using expert knowledge. Here we present DescMAP, a Python-based software, to automate the selection of descriptors, the generation of volcano maps, and the identification of active sites for structure-sensitive reactions. Here, we consider traditional energy-based and geometric descriptors for structure-sensitive reactions. DescMAP is integrated with the Virtual Kinetic Laboratory (VLab) to provide multiple functionalities. It inputs spreadsheets or template files for flexibility and outputs interactive graphs for post-processing. We demonstrate its features using the non-oxidative dehydrogenation of ethane to ethylene over (111) closed-packed surfaces and the methane total oxidation over various Pt facets. It can be easily applied to other complex chemistries and achieves quick screening of potential catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

High-efficiency solar thermophotovoltaic system using a nanostructure-based selective emitter

Herein, we present the design, fabrication, optimization, and experimental results of a high-efficiency planar solar thermophotovoltaic (STPV) system utilizing a micro-textured absorber and a nanostructure multilayer metal-dielectric coated selective emitter fabricated on a tungsten (W) substrate. Light absorptance of more than 90% was achieved at visible and near-infrared wavelengths using the microtextured absorbing surface. The nanostructure selective emitter consists of two thin-film optical coatings of silicon nitride (Si3N4) and a layer of W in between to increase the surface emissivity in spectral regimes matching the quantum efficiency of the thermophotovoltaic (TPV) cells. Gallium antimonide (GaSb)-based TPV cells are used in our STPV design. The experiment was conducted at different operating temperatures using a high-power continuous wave laser diode stack as a simulated source of concentrated incident radiation. Our experimental setup measured a maximum electrical output power density of 1.71 W/cm 2 at 1676 K STPV temperature, and the overall power conversion efficiency of 8.4% after normalizing the output power density to the emitter area. This is the highest STPV system efficiency reported so far for any experimental STPV device. The incident optical laser power on the absorber side was 131 W. This is equivalent to a solar concentration factor of ~2100, which is within the practical limit and readily achievable with Fresnel lens setup.

14 SOLAR ENERGY↗
DOE OSTI2018

Optimizing Labor Resources at Manufacturing Enterprises

Attention focuses on the selection of mathematical models and the formulation of algorithms for organizational decision making in optimizing labor resources at manufacturing enterprises. Examples of labor optimization are presented.

42 ENGINEERING↗
DOE OSTI2017

Highly Selective Recognition of Cd{sup 2+} by an Indole Derivative Chemosensor

A novel chemosensor exhibiting highly selective recognition of Cd {sup 2+} over other metal ions with significant fluorescence quenching was designed and synthesized by a click reaction of dialkyne and indole azide precursors. The compound was identified by {sup 1}H NMR, {sup 13}C NMR, MS, and UV-vis spectroscopy. The fluorescence quenching phenomenon was observed with the addition of Cd {sup 2+}. The reaction conditions, including the selectivity, the amount of Cd {sup 2+}, reaction time, and temperature, were optimized in the article. The product exerted highly selective fluorescence change in the presence of Cd {sup 2+} over other metal ions, such as Li{sup +}, Na{sup +}, K{sup +}, Pb{sup 2+}, Ni{sup 2+}, Zn{sup 2+}, Mn{sup 2+}, Hg{sup 2+}, Cr{sup 3+}, Cu{sup 2+}, and Fe{sup 3+}. Under the optimal conditions, a linearly proportional relationship between fluorescence intensity and the concentration of Cd{sup 2+} was revealed in the range from 0 to 7.226 × 10{sup –5} M. The limit of detection was 2.69 μM. The results suggest that the substance synthesized with 2-methylindole is a novel and quick detector for Cd {sup 2+}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Solar-Thermal Ammonia Production Via a Nitride Looping Cycle [Slides]

Solar Thermal Ammonia Production has the potential to synthesize ammonia in a green, renewable process that can greatly reduce the carbon footprint left by conventional Haber-Bosch reaction. Ternary nitrides in the family A 3 B x N (A=Co, Ni, Fe; B=Mo; x=2,3) have been identified as a potential candidate for NH 3 production. Experiments with Co 3 Mo 3 N in Ammonia Synthesis Reactor demonstrate cyclable NH 3 production from bulk nitride under pure H 2 . Production rates were fairly flat in all the reduction steps with no evident dependence on the consumed solid-state nitrogen, as would be expected from catalytic Mars-van Krevelen mechanism. Material can be re-nitridized under pure N 2 . Bulk nitrogen per reduction step average between 25 – 40% of the total solid-state nitrogen. Selectivity to NH 3 stabilized at 55 – 60% per cycle. Production rates (NH 3 and N 2 ) become apparent above 600 °C at P(H 2 ) = 0.5 – 2 bar. Optimal point of operation to keep selectivity high without compromising NH 3 rates currently estimated at 650 °C and 1.5 - 2 bar. The next steps are to optimize production rates, examine effect of N 2 addition in NH 3 synthesis reaction, and test additional ternary nitrides.

14 SOLAR ENERGY↗
DOE OSTI2021

Optimal Control of the Energy-Saving Hybrid Hydraulic-Electric Architecture (HHEA) for Off-Highway Mobile Machines

Most off-highway constructions and agriculture equipment use hydraulics, which has unmatched power density, for power transmission and throttling as a means for control. A novel hybrid hydraulic-electric architecture (HHEA) has recently been proposed to improve efficiency for high-power machines that would have been cost-prohibitive to electrify directly. HHEA uses a set of common pressure rails (CPRs) to transmit the majority of power hydraulically and small electric motor drives to modulate that power and to achieve precise control. This article proposes a computationally efficient Lagrange multiplier method (LMM) for computing the optimal sequence of pressure rail selections to minimize energy use. This is needed to evaluate HHEA's energy-saving potential and for iterative architecture design and sizing. An interesting complication is that the cost function is not fully defined until the candidate control sequence is fully specified. This issue is dealt with by decomposing the original problem into a set of sub-problems with additional constraints that can be solved efficiently. Computational effort can be further reduced if actuators are optimized individually instead of together. However, additional steps are required to prevent the constraint functions from becoming discontinuous with respect to the Lagrange multipliers, which is necessary for meeting the constraints. Lastly, a case study of a construction machine demonstrates the efficacy of the method and shows that the HHEA reduces energy consumption by 68%-73% compared to the baseline load-sensing architecture.

Lagrange multiplier↗
DOE OSTI2024

Lanthanide binding peptide surfactants at air–aqueous interfaces for interfacial separation of rare earth elements

Rare earth elements (REEs) are critical materials to modern technologies. They are obtained by selective separation from mining feedstocks consisting of mixtures of their trivalent cation. We are developing an all-aqueous, bioinspired, interfacial separation using peptides as amphiphilic molecular extractants. Lanthanide binding tags (LBTs) are amphiphilic peptide sequences based on the EF-hand metal binding loops of calcium-binding proteins which complex selectively REEs. We study LBTs optimized for coordination to Tb 3+ using luminescence spectroscopy, surface tensiometry, X-ray reflectivity, and X-ray fluorescence near total reflection, and find that these LBTs capture Tb 3+ in bulk and adsorb the complex to the interface. Molecular dynamics show that the binding pocket remains intact upon adsorption. We find that, if the net negative charge on the peptide results in a negatively charged complex, excess cations are recruited to the interface by nonselective Coulombic interactions that compromise selective REE capture. If, however, the net negative charge on the peptide is −3, resulting in a neutral complex, a 1:1 surface ratio of cation to peptide is achieved. Surface adsorption of the neutral peptide complexes from an equimolar mixture of Tb 3+ and La 3+ demonstrates a switchable platform dictated by bulk and interfacial effects. The adsorption layer becomes enriched in the favored Tb 3+ when the bulk peptide is saturated, but selective to La 3+ for undersaturation due to a higher surface activity of the La 3+ complex.

Ortuno Macias, Luis E. (ORCID:0000000284342192)↗
DOE OSTI2025

Characterization of Kariya ( Hildegardia barteri (Mast.) Kosterm) Seed Oil Fatty Acid Methyl Ester Prepared from Basic Catalytic Transesterification

The rising global energy demand, alongside concerns regarding environmental deterioration due to the use of fossil fuels, has spurred extensive investigation into renewable energy alternatives. Biomass-derived biodiesel, especially from lesser-known oil sources, emerges as a promising option. This research focuses on analyzing the fatty acid methyl esters (FAMEs) derived from Kariya (Hildegardia barteri (Mast.) Kosterm) seed oil through basic catalytic transesterification using gas chromatography–flame ionization detector (GC–FID) analysis, assessing its potential as a biodiesel feedstock. Oil extraction from Kariya seeds was carried out using three solvents (n-hexane, ethanol, and a 1:1 blend of hexane and ethanol), followed by transesterification with methanol. Gas chromatography–mass spectrometry (GC–MS) and GC–FID analyses were utilized to identify and quantify FAMEs in the resulting biodiesel. The results revealed various FAMEs, including methyl myristate, methyl palmitate, methyl stearate, methyl oleate, methyl linoleate, and methyl linolenate. Significant differences in FAME composition were observed among the samples, with hexane–ethanol Kariya oil biodiesel (HE-KOB) showing the highest FAME content (76.1%). This combination of solvents exhibited synergistic effects on the composition of HE-KOB, suggesting potential optimization strategies for biodiesel production. Fourier transform infrared spectroscopy (FTIR) provided additional insights into the molecular composition of the biodiesel samples, confirming their biodiesel nature through the identified functional groups such as methyl, methylene, hydrocarbon, ester, aldehyde, and alkene. Thermogravimetric analysis (TGA) for thermal decomposition also gave an insight into FAME composition and its contribution to the degree of conversion of biodiesel to energy. These findings highlight the feasibility of utilizing Kariya seed oil as a biodiesel feedstock, emphasizing the importance of solvent selection and transesterification conditions in optimizing FAME yield and composition. This research contributes to the exploration of underutilized oil sources for sustainable biodiesel production, aligning with the global shift towards cleaner and renewable energy sources.

09 BIOMASS FUELS↗
DOE OSTI2024

Rapid Optimization of Total Variation with Applications in Imaging, Additive Manufacturing, and Qualification

Total Variation optimization penalizes the gradient of a control variable or state. While this work focuses on image processing in particular, it has also found applications in inverse problems and topology optimization. In image processing, the goal is to maintain faithfulness to the original image while denoising and/or deblurring. Additionally, bilevel optimization over the spatially varying regularization weights can illuminate interfaces such as damage regions and other anomalies. We will address two fundamental challenges with TV-optimization: (i) the typical slow convergence of existing TV-optimization methods, and (ii) the selection of spatially varying TV parameters to promote interface detection. Additionally, we will apply such techniques to image data collected in additive manufacturing. In said context, stochasticity in build events induces flaws in the manufactured piece, compromising the integrity of said part. There is a critical need for in-situ monitoring to spot anomalies once they form, and in this setting we apply our total variation and hyperparameter solvers. We will develop a customized algorithm based on for extreme-scale TV-optimization that achieves super-linear or quadratic-convergence, a critical property for real-time, image-by-image analysis. A worst-case outcome is a preprocessing step that enhances image quality in-situ, specifically for out-of-focus and noisy images.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The SDSS-IV MaNGA Sample: Design, Optimization, and Usage Considerations

We describe the sample design for the SDSS-IV MaNGA survey and present the final properties of the main samples along with important considerations for using these samples for science. Our target selection criteria were developed while simultaneously optimizing the size distribution of the MaNGA integral field units (IFUs), the IFU allocation strategy, and the target density to produce a survey defined in terms of maximizing signal-to-noise ratio, spatial resolution, and sample size. Our selection strategy makes use of redshift limits that only depend on i-band absolute magnitude (M {sub i}), or, for a small subset of our sample, M {sub i} and color (NUV − i). Such a strategy ensures that all galaxies span the same range in angular size irrespective of luminosity and are therefore covered evenly by the adopted range of IFU sizes. We define three samples: the Primary and Secondary samples are selected to have a flat number density with respect to M {sub i} and are targeted to have spectroscopic coverage to 1.5 and 2.5 effective radii (R {sub e}), respectively. The Color-Enhanced supplement increases the number of galaxies in the low-density regions of color–magnitude space by extending the redshift limits of the Primary sample in the appropriate color bins. The samples cover the stellar mass range 5×10{sup 8}⩽M{sub ∗}⩽3×10{sup 11} M{sub ⊙} h{sup −2} and are sampled at median physical resolutions of 1.37 and 2.5 kpc for the Primary and Secondary samples, respectively. We provide weights that will statistically correct for our luminosity and color-dependent selection function and IFU allocation strategy, thus correcting the observed sample to a volume-limited sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

On the hydrophilicity of electrodes for capacitive energy extraction

The so-called Capmix technique for energy extraction is based on the cyclic expansion of electrical double layers to harvest dissipative energy arising from the salinity difference between freshwater and seawater. Its optimal performance requires a careful selection of the electrical potentials for the charging and discharging processes, which must be matched with the pore characteristics of the electrode materials. While a number of recent studies have examined the effects of the electrode pore size and geometry on the capacitive energy extraction processes, there is little knowledge on how the surface properties of the electrodes affect the thermodynamic efficiency. In this paper, we investigate the Capmix processes using the classical density functional theory for a realistic model of electrolyte solutions. The theoretical predictions allow us to identify optimal operation parameters for capacitive energy extraction with porous electrodes of different surface hydrophobicity. Finally, in agreement with recent experiments, we find that the thermodynamic efficiency can be much improved by using most hydrophilic electrodes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Radioiodine sorbent selection criteria

Methods for preventing radioiodine from entering the environment are needed in processes related to nuclear energy and medical isotope production. The development and performance of many different types of sorbents to capture iodine have been reported on for decades; however, there is yet to be a concise overview on the important parameters that should be considered when selecting a material for chemically capturing radioiodine. This paper summarizes several criteria that should be considered when selecting candidate sorbents for implementation into real-world systems. The list of selection criteria discussed are 1) optimal capture performance, 2) kinetics of adsorption, 3) performance under relevant process conditions, 4) properties of the substrate that supports the getter, and 5) environmental stability and disposition pathways for iodine-loaded materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Spectrally-engineered solar thermal photovoltaic devices

A solar thermal photovoltaic device, and method of forming same, includes a solar absorber and a spectrally selective emitter formed on either side of a thermally conductive substrate. The solar absorber is configured to absorb incident solar radiation. The solar absorber and the spectrally selective emitter are configured with an optimized emitter-to-absorber area ratio. The solar thermal photovoltaic device also includes a photovoltaic cell in thermal communication with the spectrally selective emitter. The spectrally selective emitter is configured to permit high emittance for energies above a bandgap of the photovoltaic cell and configured to permit low emittance for energies below the bandgap.

Lenert, Andrej↗