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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Techno-Economic Case Study: Low-Temperature Conversion Performance Based on Isolated Anatomical Fractions of Corn Stover

This report summarizes analysis conducted to support a case study under the Feedstock-Conversion Interface Consortium (FCIC) focused on techno-economic analysis (TEA) modeling to quantify the yield and cost ramifications for processing isolated anatomical fractions of corn stover through a low-temperature conversion (biochemical pathway) biorefinery. It is hypothesized that different individual anatomical fractions of corn stover vary in composition and recalcitrance, such that processing each fraction on its own e.g. through dedicated campaigns may enable economic benefits relative to processing the whole stover material. To investigate this concept, we worked with FCIC researchers to obtain data on compositional analysis, as well as processing conditions and yields, for conversion of whole corn stover plus three individual anatomical fractions (cobs, husks, and stalks) across key steps of the biorefinery conversion process within FCIC research scope, namely pretreatment and enzymatic hydrolysis. After running the data through the TEA models, fractionated cobs and husks achieved higher fuel yields and lower minimum fuel selling prices than whole corn stover, but stalks fared worse than whole stover on both metrics. The most direct takeaway from this assessment is that a biorefinery would stand to benefit economically from maximizing the use of cob and husk fractions while avoiding or minimizing the use of stalks, though recognizing practical constraints with this approach in maintaining an equivalent processing capacity (fixed at 2,000 dry metric tonne per day in all cases).

09 BIOMASS FUELS↗
DOE OSTI2023

Biochemical Conversion of Lignocellulosic Biomass to Hydrocarbon Fuels and Products: 2022 State of Technology and Future Research

The annual State of Technology (SOT) assessment is a key activity for biochemical platform research. It allows the impact of research progress (both directly achieved in-house at the National Renewable Energy Laboratory [NREL] and indirectly extrapolated from available public data) to be quantified in terms of economic improvements in the overall cellulosic biofuel production process for a particular conversion pathway. As such, initial benchmarks can be established for currently demonstrated performance and progress can be tracked toward out-year goals to ultimately demonstrate cost-competitive biofuel technology. Building upon efforts to progress NREL's biochemical platform R&D work toward ultimate 2030 goals to demonstrate less than $2.50/gallon gasoline equivalent (GGE) fuel selling prices, experimental and techno-economic analysis (TEA) activities have primarily focused on "advanced" biochemical processing strategies to fuels and coproducts, guided by TEA modeling to highlight key barriers and priorities toward achieving this goal across a number of potential bioconversion pathways. The purpose of the present effort is to benchmark the latest experimental developments for these pathways as quantified by modeled minimum fuel selling prices (MFSPs), as a measure of current status relative to those final targets. For this SOT, TEA models were run for two separate biological conversion pathways to fuels, based on available data for integrated biomass deconstruction and hydrolysate processing; namely carboxylic acids (primarily butyric acid) and diols (2,3-butanediol [BDO]), reflecting NREL's recently published 2018 biochemical design report focused on those two pathways. The models were run across two scenarios for lignin utilization, namely combustion and conversion to value-added coproducts.

09 BIOMASS FUELS↗
DOE OSTI2025

Positive Neutrino Masses with DESI DR2 via Matter Conversion to Dark Energy

The Dark Energy Spectroscopic Instrument (DESI) is a massively parallel spectroscopic survey on the Mayall telescope at Kitt Peak, which has released measurements of baryon acoustic oscillations determined from over 14 million extragalactic targets. We combine DESI Data Release 2 with CMB datasets to search for evidence of matter conversion to dark energy (DE), focusing on a scenario mediated by stellar collapse to cosmologically coupled black holes (CCBHs). In this physical model, which has the same number of free parameters as Λ⁢CDM, DE production is determined by the cosmic star formation rate density (SFRD), allowing for distinct early- and late-time cosmologies. Using two SFRDs to bracket current observations, we find that the CCBH model: accurately recovers the cosmological expansion history, agrees with early-time baryon abundance measured by BBN, reduces tension with the local distance ladder, and relaxes constraints on the summed neutrino mass ∑𝑚 𝜈 . For these SFRDs, we find a peaked positive ∑𝑚 𝜈 < 0.149 eV (95% confidence) and ∑𝑚 𝜈 = 0.106$^{+0.050}_{−0.069}$ eV, respectively, in good agreement with lower limits from neutrino oscillation experiments. A peak in ∑𝑚 𝜈 > 0 results from late-time baryon consumption in the CCBH scenario and is expected to be a general feature of any model that converts sufficient matter to dark energy during and after reionization.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Techno-Economic Case Study: Fermentation Cost Impacts from Selected Critical Material Attributes

This report summarizes analysis conducted to support a case study under the Feedstock-Conversion Interface Consortium (FCIC) focused on techno-economic analysis (TEA) modeling to quantify the economic implications of biomass hydrolysate substrate variability on fermentation performance and resultant biorefinery fuel yields. It is known that fermentation inhibitors or byproducts, as may either come from constituents in the biomass feedstock or imparted through biorefinery processing operations, can detrimentally impact fermentation rates and yields. However, it is often difficult to isolate fermentation impacts to individual components given the complex nature of biomass varying simultaneously in multiple attributes from one lot to another. For this study, we worked with FCIC researchers to obtain data on key fermentation performance metrics, namely productivity rates and conversion yields, across a number of material attribute species previously selected by the researchers as "critical" attributes which may be found in hydrolysate used as microbial carbon sources during fermentation. These data were run through TEA models to estimate resultant impacts on biorefinery economics, reported as minimum fuel selling price (MFSP). Overall, the trends in MFSP closely followed fuel yields, in turn tied to fermentation process yields and selectivity, with minimal economic impact from variations in fermentation productivity.

09 BIOMASS FUELS↗
DOE OSTI2022

Conversion of Resonance Parameters Between Wigner-Eisenbud R-matrix and Transition Matrix Pole Representation

The goal of this research is to develop a numerical code for translation between the current standard, Wigner-Eisenbud R-matrix parameters and a novel pole-representation of cross sections. The method follows Ducru et al. and constructs the conversion between these parametric representations of the scattering and reaction data. This pole representation, which expresses cross sections as a sum of simple poles (and their attendant residues), is examined in the context of the advantages provided by this compact, computationally efficient representation. These advantages include the ability to doppler broaden cross sections on-the-fly as well as a lower memory footprint when generating cross sections, an attractive feature to those interested in parallel GPU based Monte Carlo. Some conversion methods between R-matrix parameters and S-matrix poles have relied on curve fitting techniques. It is unknown weather these numerical methods necessarily preserve certain underlying physics properties of the standard R-matrix cross section model (such as unitarity). The direct conversion studied here aim to preserve such properties. This knowledge is of interest for future work into the generation of resonance parameter sensitivities.

CLUTCH↗
DOE OSTI2022

Evaluation of artificial neural network performance for classification of potato plants infected with potato virus Y using spectral data on multiple varieties and genotypes

Potato virus Y (Potyviridae, PVY) is a plant virus that poses a significant threat to potato producers on a global basis. The pathogen has disrupted seed potato supplies and negatively impacted yield and quality of commercial potato crops. The potato industry currently manages PVY infection levels via insecticide applications, regional seed certification programs that rely on field scouting to visually assess individual plants for infection status, and destructive and costly tissue sampling coupled with laboratory assays. Despite these efforts, PVY continues to confound potato industry stakeholders resulting in economic harm. Remote sensing and machine learning provide for the development of new tools to more accurately detect and spatially quantify PVY-infected plants versus the current state of the art. However, there is a need to understand how the occurrence of many different potato varieties impact the dynamics of developing models to detect potato plants impacted with PVY and their potential effectiveness. This study evaluates classification modelling outcomes using spectral datasets collected in different temporal and spatial environments (greenhouse and a production field) on multiple potato varieties consisting of labelled instances of plants infected with PVY and those not infected with the virus. A modelling framework was developed to support iterative modelling runs using artificial neural network (ANN) architectures configured as binary classifiers to develop sample populations to support statistical analysis on model performance using specific spectral subsets. When using spectral data to detect PVY-infected plants, ANN models achieved the highest mean accuracy of 0.894 on a single variety. Conversely, the same ANN model architecture only achieved a mean accuracy of 0.575 on a spectral data set representing 29 potato breeding lines. Additionally, statistical analysis indicates spectral regions including the red edge, near infrared and shortwave infrared contain more important spectral features for the ANN classifier introduced in this research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Specific Gamma-Ray Dose Constants with Current Emission Data

The specific gamma-ray dose constant represents the gamma effective dose rate due to a point source of unit activity of a given nuclide at 1 m. New tabulations of specific gamma-ray dose constants have been made using current gamma emission data from the SCALE 6.2.3 software package and International Commission on Radiological Protection Publication 107, combined with the effective dose per fluence conversion coefficients (antero-posterior orientation) of International Commission on Radiological Protection Publication 116. SCALE data cover 1,264 nuclides, and International Commission on Radiological Protection Publication 107 data include 1,192 nuclides, with only 777 nuclides in common between the two sets.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Detailed modeling of hydrogen release and particle shrinkage during pyrolysis of inhomogeneous wood

Hydrogen release during pyrolysis of woody biomass is studied considering anisotropicity and inhomogeneity of wood structure. A new anisotropic shrinkage model is proposed based on the decomposition of main wood constituents, i.e., cellulose, hemicellulose, and lignin. The new shrinkage model can predict the temporal evolution of the wood structure, and the differences between axial and radial shrinkage during pyrolysis. The model agrees very well with several experimental data from the literature. Based on particle temperature during conversion, the pyrolysis is partitioned into four stages, and the hydrogen release and H 2 formation from each stage are investigated. Stage (IV) of pyrolysis, from 1000 to 1273 K, is found to be efficient for H 2 production owing to the production of considerable mass of H with a minimal amount of tar species. Furthermore, the char quality is found to be different at the end of stages (II), (III), and (IV), where around 67.7, 80.5, and 93.4% wt. of solid residue is made of carbon, respectively. The model is also used to explain how the heating rate affects the temperature distribution inside the particle and how it shifts the peak of hydrogen release. Finally, the pyrolysis of two inhomogeneous wood samples — a beech twig with bark and a beech dowel with growth rings — are investigated. The bark can affect the pyrolysis rate, products, and flow pattern inside the particle. The growth rings do not have a considerable effect on the pyrolysis rate and products, but they have a significant impact on the flow pattern. This has an important implication for char conversion studies where the internal surface area and porosity field distribution have a significant effect on the gasification and oxidation rates.

09 BIOMASS FUELS↗
DOE OSTI2023

Voltage mapping and local defects identification in solar cells using non-contact method

Electroluminescence, infrared imaging, and current–voltage curve techniques are used to detect and map underperforming cells in a photovoltaic module or the modules in a photovoltaic string. In this work, we present a non-contact electrostatic voltmeter technique to detect and map the underperforming spots in a cell and the cells in a module. This non-contact technique directly maps the charged surface voltage (671mV) of the superstrate glass, and it had an 11-mV difference with the voltmeter values (660mV). Another data set of voltage values obtained by electroluminescence images conversion into a voltage map showed a difference of 7mV with the non-contact voltmeter values. Further, the direct voltage values obtained at various good and poor-performing spots of the cells using this technique are 3.69V and 3.79V and are validated using the voltage values obtained in electroluminescence analysis and the difference in voltage obtained by the two techniques is determined to be less than 2%. In this work, we combine the strengths of two complementary techniques of the electrostatic voltmeter (strength: quantitative) and electroluminescence (strength: spatial mapping) to obtain a quantitative spatial mapping of defects. Furthermore, this work is extendable to detect the poor-performing modules in solar PV power plants.

14 SOLAR ENERGY↗
DOE OSTI2024

Determining the Reaction Kinetics and Thermodynamics of a Diels–Alder Network Using Dynamic Gel Criteria

We undertook a detailed rheological investigation to evaluate the kinetic parameters of the forward and reverse Diels–Alder (DA) reactions of a model network cross-linked using a furan prepolymer and a common aromatic bismaleimide. At high temperature where the Winter–Chambon’s criterion of frequency-independence was more applicable, a multiwave technique permitted van’t Hoff analysis and calculation of the reaction thermodynamic parameters, specifically the enthalpy and entropy of the reaction: ΔH° = –38.3 ± 5.2 kJ mol –1 and ΔS° = –94.3 ± 13.4 J mol –1 . At mild temperatures where the G'–G" crossover point is experimentally convenient to measure gelation, isothermal tests were used to obtain reasonable fDA kinetic parameters from Eyring analysis such as the apparent activation enthalpy and entropy of ΔH$^{‡}_{fDA}$ = 76.8 ± 6.9 kJ mol –1 and ΔS$^{‡}_{fDA}$= –82.8 ± 22.2 J mol –1 K –1 . Comparable rheokinetic methods include cross-linking density measurements and stress relaxation tests to calculate effective kinetics, whereas the critical gel conversion was consistently applied here. As a result, rate data are fitted with the Arrhenius equation for comparison purposes and the Eyring equation to demonstrate its broader utility.

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

A Multiport DC Transformer to Enable Flexible Scalable DC as a Service

The rapid adoption of new DC loads and sources, including photovoltaic arrays, DC fast charging of electric vehicle, battery energy storage and data centers, requires a large amount of DC power conversion. A majority of new deployments also necessitate the integration of multiple DC loads and sources at one site. The traditional approach to serve these new applications relies on multiple standard power converters, each dedicated to a source or load, and results in highly customized systems, with challenging control coordination, complex protection strategies, and poor scalability. Instead, this paper proposes the concept of a multiport DC transformer (MDCT) as a modular building block for realizing a flexible, scalable DC as a Service system and address this rapidly growing need. The MDCT uses the S4T to achieve very tight control of cycle-by-cycle energy exchange between multiple ports, with high efficiency. A single multiport converter replaces 4-6 distinct converters, integrates all energy flows and manages protection. As a result, a new layered control architecture is introduced to ensure stability and scalability of the MDCT, with multiple S4T power converter building blocks connected in parallel to realize a fully modular system and reach the target power levels.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Refinery Integration Analysis: Pathways, Challenges, and Opportunities

Integrating biomass-derived intermediates into traditional petroleum refineries presents unique challenges and opportunities, requiring innovative analysis approaches that account for biofuel producers and refiners. Consequently, teams within the National Renewable Energy Laboratory (NREL) have developed a comprehensive refinery integration analysis framework that combines experimental data, detailed techno-economic analyses of bio-conversion pathways, and economic projections within refinery linear programming (LP) optimization models. These models enable the identification of promising bio-integration strategies tailored to specific refinery configurations, economic conditions, and production goals. They also capture upstream and downstream impacts, highlighting critical bottlenecks and research opportunities for increasing the share of biogenic feedstocks in traditional refining operations. Refinery models are also packaged into a broader bio-economy optimization framework which enables biofuel supply chain optimization with standalone biofuel production and refinery co-processing/repurposing options. This presentation discusses promising refinery bio-integration strategies along with key challenges and opportunities identified using NREL's refinery and bio-economy optimization frameworks.

09 BIOMASS FUELS↗
DOE OSTI2022

Self-Sensing, Stretchable, Active Circuit Arrays: Liquid Metal Paste as a Combination Interconnect and Strain Sensor

Stretchable electrical interconnects and substrate materials are increasingly used to create flexible and con-formable electronic systems for soft robotics, smart textiles, and wearable devices. Wires fabricated using composite or liquid conductive inks encapsulated in silicone enable high strain and are mechanically robust. The resistance of these inter-connects increases with strain, which can present challenges for power delivery and signaling among electronic components. However, this effect can be used directly to estimate strain within a stretchable circuit without the need for additional sensor components. In this work, we present an approach for fabricating fully-stretchable, multi-layer active circuit arrays in silicone using liquid metal paste interconnects, in which power and data wires are re-purposed as strain sensors to estimate substrate deformation. As a proof-of-principle, we demonstrate a 3×3 active circuit array that self-senses relative voltage supply at each node to estimate deformation and consumes less than 10 mA per node. Each node is digitally addressable and performs both analog measurement and digital conversion. All interconnects are fabricated using liquid metal paste, and power, data, and sensing are performed over a shared, four-wire interface in this multi-layer stretchable printed circuit board.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Reliability Assessment of Cooling Fans for PV Inverters: Testing, Modeling, and Case Studies

The reliability of photovoltaic (PV) inverters is critical for long-term solar system performance, with cooling fan failures frequently leading to costly downtime. While much research exists on general cooling fan reliability, little attention has been given to fans operating within PV inverters and their unique environmental challenges. Here, this article proposes a comprehensive methodology to address this gap. First, a failure mode and effects analysis is performed on fans to identify the key failure mechanisms in PV applications, their corresponding stressors, and the models necessary for lifetime prediction. Second, an accelerated life test is designed and conducted to collect valuable experimental data for PV inverter fans in a reasonable amount of time. Third, a mathematical conversion of dynamic mission profiles into effective constant stress levels is derived. Fourth, case studies are given, showcasing lifetime estimates that account for geographic variations in mission profile data. The results demonstrate that this integrated approach leads to an accurate reliability assessment for PV inverter cooling fans.

accelerated life testing (ALT)↗
DOE OSTI2022

Evaluated Nuclear Structure Data File (ENSDF)

Contains recommended nuclear structure and decay data for all the known nuclides, which are obtained following a critical review of all available experimental data, supplemented with systematic trend studies and theoretical models. ENSDF data include (i) nuclear level properties, such as observation source, energy, half-life, decay modes, spin and parity; (ii) gamma ray energies, intensities, multipolarities, mixing ratios and conversion coefficients; (iii) nuclear radiation energy and intensity as well as radiation-specific data for different radiation types, such as such as gammas, alphas, betas and neutrons. Data for about 220 nuclides are fully evaluated each year; additionally, many datasets are partially updated each year. Nearly all the evaluation work is supported by the US Nuclear Data Program. The National Nuclear Data Center at Brookhaven National Laboratory is responsible for coordinating the evaluation effort as well as its web and journal dissemination.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

1.1 eV GaInAs Cell Development for Dual-Use Solar and 1070 nm Laser Power Converters

Dual-use photovoltaic cells can receive solar and laser power simultaneously to generate current, an application relevant to space and terrestrial industries. This study investigates two concepts of solar cells optimized for dual-use 1070 nm laser and solar power conversion, a single-junction and triple-junction cell. The cell designs are based upon the 3- junction inverted metamorphic solar cell, previously shown highly efficient for solar conversion. Because it is closely bandgap-tuned for a 1070 nm laser, the 1 eV bottom junction is incorporated into each of the two designs, making its development key to the success of both concepts. However, each design requires some modification for efficient dual use. The single-junction device requires optimization to reduce short wavelength absorption of the broad solar spectrum. In both devices, the graded buffer layers in the GaInAs cell affect the cell's performance by reducing threading dislocations in the active junction. However, the buffer in the three-junction device also acts as a lateral transport layer and so affects the fill factor depending on its sheet resistance. By varying the buffer thickness, we demonstrate a direct relationship between buffer thickness and sheet resistance reduction, while considering implications to open-circuit voltages. We also performed resistance modeling to determine the optimal grid spacing and thickness of the grid fingers to minimize losses due to sheet resistance and grid shading. Efficiency data for a one junction GaInAs cell demonstrates a laser conversion efficiency of 38% at 1070 nm wavelength without an anti-reflection coating.

dual-use↗
DOE OSTI2020

Stability Analysis of Inline ZFP Compression for Floating-Point Data in Iterative Methods

Currently, the dominating constraint in many high performance computing applications is data capacity and bandwidth, in both internode communications and even moreso in intranode data motion. A new approach to address this limitation is to make use of data compression in the form of a compressed data array. Storing data in a compressed data array and converting to standard IEEE-754 types as needed during a computation can reduce the pressure on bandwidth and storage. However, repeated conversions (lossy compression and decompression) introduce additional approximation errors, which need to be shown to not significantly affect the simulation results. Here, we extend recent work that analyzed the error of a single use of compression and decompression of the ZFP compressed data array representation to the case of time-stepping and iterative schemes, where an advancement operator is repeatedly applied in addition to the conversions. We show that the accumulated error for iterative methods involving fixed-point and time evolving iterations is bounded under standard constraints. An upper bound is established on the number of additional iterations required for the convergence of stationary fixed-point iterations. An additional analysis of traditional forward and backward error of stationary iterative methods using ZFP compressed arrays is also presented. The results of several 1D, 2D, and 3D test problems are provided to demonstrate the correctness of the theoretical bounds.

97 MATHEMATICS AND COMPUTING↗