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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 307 records · Page 17

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NASA NTRS1995

Nutritional value of protein hydrolysis products (oligopeptides and free amino acids) as a consequence of absorption and metabolism kinetics

When pigs were submitted to duodenal infusion of solutions containing a large percentage of small peptides (PEP) or free amino acids with the same pattern (AAL) amino acids appear in the portal blood more rapidly and more uniformly after infusion of PEP then after infusion of AAL, with the notable exception of methionine for which the opposite was true. These differences were lowered when a carbohydrate (maltose dextrin) was present in the solution, but nevertheless remained significant for the first hour after the infusion. The long-term (8-hour) uptake of free amino acids into the liver and the peripheral tissues differed in profile according to the nature of the duodenal infusion. Peripheral uptake was appreciably less well balanced after infusion of free amino acids (deficiency of threonine and phenylalanine) than after infusion of small peptides (deficiency of methionine). Accordingly, in the rat, under conditions of discontinuous enteral nutrition the mixture of small peptides was of greater nutritive value than the mixture of free amino acids. It thus appears that the absorption kinetics which results in important variations in the temporal distribution of free amino acids in the tissues may be at the origin of transitory imbalances in tissue amino acid uptake, and as a result of a lower nutritive value.

Intestinal Absorption/drug effects↗

NASA NTRS1993

Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning

Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuous-valued attribute into multiple intervals.

discretization continuous-valued attributes classi↗

NASA NTRS2017

Relevance of the American Statistical Society's Warning on P-Values for Conjunction Assessment

On March 7, 2016, the American Statistical Association (ASA) issued an online editorial paper on the "context, process, and purpose of p-values." According to the paper, "the statement articulates in non-technical terms a few select principles that could improve the conductor interpretation of quantitative science, according to widespread consensus in the statistical community." This "consensus" statement was accompanied by 21 "commentaries" expressing a diversity of opinions among the panel of experts ASA convened. In the present work, we express our view that the ASA p-value warning has relevance to the space object Conjunction Assessment (CA) community.

p-values↗

NASA NTRS2019

The Value of Near Real-Time Earth Observations for Improved Flood Disaster Response

Information is a critical resource in disaster response scenarios. Data regarding the geographic extent, severity, and socioeconomic impacts of a disaster event can help guide emergency responders and relief operations, particularly when delivered within hours of data acquisition. Information from remote observations provides a valuable tool for assessing conditions "on the ground" more quickly and efficiently. Here, we evaluate the social value of a near real-time flood impact system using a disaster response case study, and quantify the Value of Information (VOI) of satellite-based observations for rapid response using a hypothetical flooding disaster in Bangkok, Thailand. MODIS imagery from NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) system is used to produce operational estimates of inundation depths and economic damages.These rapid Earth observations are coupled with a decision-analytical model to inform decisions on emergency vehicle routing. Emergency response times from vehicles routed using flood damage data are compared with baseline routes without the benefit of advance information on road conditions. Our results illustrate how the application of near real-time Earth observations can improve the response time and reduce potential encounters with flood hazards when compared with baseline routing strategies. Results indicate a potential significant economic benefit (i.e.,millions of dollars) from applying near real-time Earth observations for improved flood disaster response and management.

emergency response↗

NASA NTRSDate not supplied

Use of Spectral Analysis of Singular Values as a Test Metric for IMMAT Trials

One of many challenges in the implementation of multiple exciter testing is establishing a reasonable set of test metrics to measure the quality of testing. This is especially true in the application of Impedance Matched Multi-Axis Testing; in that it is possible to have very large spectral density matrices that serve as reference criteria. While there exist plotting schemes to view a spectral density matrix, it is often necessary to break the overlay of reference and test results into subsections of the matrices to get sufficient resolution to interpret the data. In addition, as one attempts to control multiple locations on a structure, implementation of classical single degree-of freedom test tolerances across all channels and associated cross spectra is simply not feasible. Hence it is challenging to evaluate overall test quality. The use of spectral views of the dominant singular values from the singular value decomposition of the spectral density matrices and metrics based upon them is proposed for establishing a set of compact metrics for evaluating test quality. A laboratory experiment will be included to demonstrate this proposed technique.

Impedance Matched Multi-Axis Testing↗

NASA NTRSDate not supplied

Use of Spectral Analysis of Singular Values as a Test Metric for Impedance Matched Multi-Axis Test Trials

Vibration Testing↗

DOE OSTI2021

Value-Added Process Intensification in the Supply Chain

The project goal is to assess opportunities for value-adds in the supply chain through designing a feedstock logistics systems that uses moisture during the residence time in storage to protect and increase feedstock value.

09 BIOMASS FUELS↗

DOE OSTI2020

Briquetting characteristics of woody and herbaceous biomass blends: Impact on physical properties, chemical composition, and calorific value

Abstract Intercropping (or polyculture) is gaining a lot of interest as it increases yields, allows better utilization of resources (water and nutrients), and provides better land management. The objective of this study is to understand the briquetting characteristics of woody and herbaceous biomass blends, which might result from intercropping. Tests were conducted on blends of lodgepole pine, switchgrass, and corn stover biomass using three hammer mill screen sizes (i.e., 4.8, 12.7, and 19.05 mm), three blend moistures (12%, 15%, and 18%, w.b.), and two‐ and three‐blend ratios (i.e., 1:1 and 1:1:1) using a pilot‐scale hydraulic briquette press. The briquette properties, such as unit and bulk density, durability rating after 5 days of storage (as they tend to attain stable density), and the energy consumption of the process were measured. The results indicate that moisture content of 12% and 15% (w.b.) and smaller hammer mill screen size of 4.8 mm increased the unit and bulk densities to >750 and >430 kg/m 3 and moisture content (15% and 18% (w.b.)) and hammer mill screen size of 12.7 and 19.05 mm produced briquettes with durability rating values of >95%. The higher moisture content of 18% (w.b.) and the hammer mill screen size of 12.7 and 19.05 mm had the highest energy consumption. The proximate and ultimate analysis showed that energy content improved by blending lodgepole pine with both corn stover and switchgrass and also showed increased calorific value and reduced ash content. Scanning electron microscopy micrographs showed interlocking of particles and cracks in the briquettes. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

Tumuluru, Jaya Shankar↗

DOE OSTI2024

Toward Rational Design of Nickel Catalysts for Thermocatalytic Decomposition of Methane for Carbon Dioxide-Free Hydrogen and Value-Added Carbon Co-Product: A Review

Thermocatalytic decomposition of methane provides opportunities for hydrogen (H2) production with no emission of carbon dioxide. However, high-value carbon products need to be produced for economic deployment of thermocatalytic decomposition and to achieve a minimum H 2 selling price below the U.S, Department of Energy target of $ 1/kg H 2 . In this review, we re-evaluate data on catalyst development reported in the literature and propose correlations between catalyst characteristics, catalytic stability, and properties of carbon co-products. In the first part of the review, growth mechanisms for carbon nanotubes using state-of-the-art chemical vapor deposition are reviewed to catalog the effects of catalyst characteristics, the influence of carbon sources, interactions between metal particles and supports, and metal particle sizes on carbon growth. In the second part, representative developments in mono-, bi-, and tri-metallic nickel catalysts are highlighted. We present kinetic analysis of reactions catalyzed by mono-metallic nickel catalysts, which generates a correlation between metal particle size and catalyst stability. Rational design of Ni-based catalysts for TCD of methane requires attention to the size of the metal particle and effective normalization of the reaction rates. Further attention to the distribution of the metal particle sizes may help identify catalyst properties that contribute longevity and selectivity to processes that use them. While it is tempting to focus on the highest valued carbon products (e.g., CNTs and CFs), analysis of the markets for other carbon products suggests that a more flexible approach may generate comparable returns without the risk associated with specialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Transgenic Sugarcane–Oilcane: An Alternative Feedstock for the Production of Drop-in Fuel and Value-Added Bioproducts

The utilization of plants and other agricultural produce can partly offset petroleum dependency for energy requirements and can potentially provide sustainable solutions to global environmental problems. To this end, synthetic biology has shown great potential in developing transgenic bioenergy grasses such as sugarcane, sorghum, miscanthus, and energy cane that hyperaccumulate energy-rich lipid molecules in their vegetative tissues, such as leaves, stems, and roots. These perennial high-biomass transgenic C4 grasses are not targeted to grow on prime agricultural land and can be dedicatedly used to produce biofuels and other value-added bioproducts. Recently, sugarcane has been metabolically engineered to sequestrate carbon from juice towards biosynthesis of lipid molecules in the vegetative tissues. Transgenic sugarcane is referred to as “oilcane.” Transgenic sugarcane–oilcane has improved energy density due to an elevated lipid content in the vegetative tissues. Transgenic bioenergy crops cater to both cellulosic sugars and vegetative lipids, hence resulting in higher biofuel yield (biodiesel/renewable diesel and bioethanol) per unit area of cultivable land. In this book chapter, the genetic engineering of sugarcane and its bioprocessing are discussed to illustrate its development and use as an alternative feedstock for the production of biofuels (bio-jet fuel, biodiesel, and bioethanol) and value-added bioproducts.

Maitra, Shraddha↗

DOE OSTI2022

A Market Feedback Framework for Improved Estimates of the Arbitrage Value of Energy Storage Using Price-Taker Models

Price-taker (PT) models are often used to assess the potential value or revenue of energy arbitrage opportunities for energy storage in wholesale markets. But as greater amounts of energy storage are deployed on the grid, current PT models fail to predict the effects that energy storage itself can have on market prices. This can lead to an overestimation of the economic value of storage and an inability to capture price suppression. In this paper, we propose the use of a modified PT model to simulate the impact of increased storage deployment on energy prices and the resulting impact on revenue. Our method uses a gradient-boosting regressor to estimate the impact on prices, and we apply our method on historical price data from the PJM and California Independent System Operator wholesale markets. We use this approach to explore possible causes of electricity price suppression that occur from storage capacity additions, which is generally not possible with PT models.

arbitrage↗

DOE OSTI2022

The value of in-reservoir energy storage for flexible dispatch of geothermal power

Geothermal systems making use of advanced drilling and well stimulation techniques have the potential to provide tens to hundreds of gigawatts of clean electricity generation in the United States by 2050. With near-zero variable costs, geothermal plants have traditionally been envisioned as providing “baseload” power, generating at their maximum rated output at all times. However, as variable renewable energy sources (VREs) see greater deployment in energy markets, baseload power is becoming increasingly less competitive relative to flexible, dispatchable generation and energy storage. Herein we conduct an analysis of the potential for future geothermal plants to provide both of these services, taking advantage of the natural properties of confined, engineered geothermal reservoirs to store energy in the form of accumulated, pressurized geofluid and provide flexible load-following generation. We develop a linear optimization model based on multi-physics reservoir simulations that captures the transient pressure and flow behaviors within a confined, engineered geothermal reservoir. We then optimize the investment decisions and hourly operations of a power plant exploiting such a reservoir against a set of historical and modeled future electricity price series. Further, we find that operational flexibility and in-reservoir energy storage can significantly enhance the value of geothermal plants in markets with high VRE penetration, with energy value improvements of up to 60% relative to conventional baseload plants operating under identical conditions. Across a range of realistic subsurface and operational conditions, our modeling demonstrates that confined, engineered geothermal reservoirs can provide large and effectively free energy storage capacity, with round-trip storage efficiencies comparable to those of leading grid-scale energy storage technologies. Optimized operational strategies indicate that flexible geothermal plants can provide both short- and long-duration energy storage, prioritizing output during periods of high electricity prices. Sensitivity analysis assesses the variation in outcomes across a range of subsurface conditions and cost scenarios.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Variable renewable energy deployment in low-emission scenarios: The role of technology cost and value

While rapid deployment of variable renewable energy (VRE) technologies, namely wind and solar PV, is often projected in 2C pathways generated by integrated assessment models, there is a wide range in projected VRE deployment by mid-century. Such differences could be the result of differences in assumptions about future technology costs and/or differences in model approaches for capturing other aspects of technology competitiveness. Here we introduce a consistent competitiveness metric, profitability-adjusted levelized cost of electricity (or PLCOE), to an integrated assessment model (EPPA) to evaluate the representation of technology competition, including VRE, in low-emission scenarios. We show that representing the value of technology (alongside cost) may significantly impact VRE deployment relative to scenarios without such an adjustment. In addition, we show that varying VRE costs by about 35% in 2050 results in differences in VRE deployment that span much of the range in outcomes (over the same period) observed in likely 2C scenarios assessed by the IPCC, suggesting that both cost and value are key drivers of VRE deployment in such scenarios. Given the central role that VRE technologies play in the electricity mix across most scenarios, we also find that alternative cost assumptions for VRE technologies can lead to changes in electricity prices, the associated demand for electricity, and total final and primary energy consumption. However, the demand for fuels other than electricity is relatively insensitive to VRE assumptions in the 2C scenarios considered here.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Estimating the economic value of hydropeaking externalities in regulated rivers

Hydropower is a flexible form of electricity generation providing both baseload and balancing power to accommodate intermittent renewables in the energy mix. However, hydropower also generates various externalities. This study investigates individuals' preferences for policies aiming to reduce short-term regulations (i.e., hydropeaking in regulated rivers) while accounting for associated externalities with a discrete choice experiment. This is the first valuation study focusing on hydropeaking that considers both negative and positive externalities. The results imply that most individuals prefer stronger restrictions on short-term regulations to mitigate local environmental impacts. Individuals especially value improvements in recreational use, fish stocks, and the ecological state. On the other hand, potential increases in CO 2 emissions are linked with a clear disutility. The estimated benefits obtained from an improved state of the river environment due to such restrictions exceed the disutility caused by increased CO 2 emissions. Furthermore, the results also reveal unobserved preference heterogeneity among individuals, which should be accounted for in the willingness-to-pay (WTP) estimation using a model specification with correlated utility coefficients. Overall, the findings can inform policy-makers and environmental managers on the economic value of hydropeaking externalities and further guide the sustainable management of rivers regulated for hydropower generation.

13 HYDRO ENERGY↗

DOE OSTI2023

Chemical-free production of multiple high-value bioproducts from metabolically engineered transgenic sugarcane ‘oilcane’ bagasse and their recovery using nanofiltration

Bioenergy crops have potential for being a sustainable and renewable feedstock for biofuels and various value- added bioproducts. The study utilizes recently developed transgenic sugarcane (‘oilcane’) bagasse for chemical- free coproduction of high-value bioproducts, i.e., furfurals, HMF, acetic acid, cellulosic sugars, and vegetative lipids. Hydrothermal pretreatment was optimized at 210°C for 5 min to coproduce 6.91%, 2.67%, 5.07%, 2.42% and 37.82% (w/w) furfurals, HMF, acetic acid, vegetative lipids, and cellulosic sugars, respectively from lignocellulosic biomass. Additionally, nanofiltration system in-series was successfully established to recover sugars, furfurals, HMF, and acetic acid from the pretreatment liquor. 1st nanofiltration with Duracid NF mem- brane rejected ~99% sugars. Concentrated sugars with significantly reduced inhibitory products were obtained in retentate for fermentation. 2nd nanofiltration with NF90 membrane used permeate of 1st nanofiltration as feed and rejected ~ 86% furfurals. Furthermore, the work demonstrates the feasibility of coproducing and recovering multiple biochemicals from lignocellulosic biomass.

09 BIOMASS FUELS↗

DOE OSTI2022

Group additivity values for the heat of formation of C 2 –C 8 alkanes, alkyl hydroperoxides, and their radicals

A set of 58 group additivity values (GAV) for the calculation of the heat of formation is derived from an extensive and accurate database of 192 ab initio heats of formation. The ab initio values are from companion calculations at the CCSD(T)–F12/cc-pVTZ-F12//B2PLYPD3/cc-pVTZ level of theory employing second order connectivity based hierarchy reference reactions with ANL energies for the reference species. This database of 192 species consists of alkanes (RH), alkyl radicals ($\dot{\text {R}}$), alkyl hydroperoxides (RO 2 H), alkyl-peroxy (R$\dot{\text {O}}$ 2 ) radicals, and hydroperoxy-alkyl ($\dot{\text {Q}}$OOH) radicals of all of the isomers of C 2 –C 5 alkane fuels and a select set of C 6 –C 8 isomers. The GAV and ab initio based enthalpies for this dataset show excellent agreement, with an estimated 2σ uncertainty of 0.9 kcal mol –1 . Among the 58 GAV terms, 40 are refinements of previously reported terms, while 18 are newly developed. These new GAV terms are mainly non-next-nearest neighbor interactions (NNI) and β-corrections. The inclusion of these new groups significantly improves the accuracy of the GAV estimates of the heats of formation. Finally, the updated GAVs can be used with increased confidence to estimate the heats of formation of combustion relevant hydrocarbons and oxygenated hydrocarbons and their corresponding radicals, which are important in predicting low-temperature chemistry and are critical in the development of accurate chemical kinetic models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Hedonic Price Estimates of Lake Water Quality: Valued Attribute, Instrumental Variables, and Ecological-Economic Benefits

We estimate the effect of lake water quality on residential housing prices using cross-sectional data on water clarity from 113 lakes across the United States. An instrumental-variables approach is developed to address potential endogeneity bias in the water-clarity variable. Three lake-based physical variables serve as instrumental variables: total nitrogen concentration in lake water, total phosphorus concentration in lake water, and water temperature near the lake surface. The econometric results include three methodological findings: the instruments are valid and strong; the ordinary-least-squares estimate of the coefficient on the water-clarity variable is unbiased; and water clarity is the attribute of water quality valued in the housing market. The estimated water-clarity effect shows that a one-tenth of a meter change in water clarity leads to a one-percent change in housing price, or an elasticity of 0.20 at mean clarity. Coupling this effect with estimates of an ecological production function, a lake-specific benefit index is developed that shows the effect on housing values of bringing lakes into compliance with the US Environmental Protection Agency's regional recommendations for phosphorous concentration in lake waters.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Utilization of an Advanced Sensor network to determine fuel heating value and Real-Time net unit heat rate during transient operation

Coal-fired utility boilers are being increasingly used as variable electricity generation to resolve the imbalance in the energy market from the expansion of intermittent renewable energy. The frequent transient operation required to meet residual energy demand has created a challenge for coal-fired units to operate efficiently. This work utilizes an advanced sensor network (ASN) to calculate net unit heat rate (NUHR) of a coal-fired boiler in real time through combustion calculations and statistical correlations to provide the tools for optimizing dynamic operation. Real-time heating values that were necessary to determine fuel input energy to calculate accurate NUHR were found using both fundamental and data-driven methods. Real-time NUHR shows distinct shifts that reflect changes in process conditions that will improve the ability to optimize transient operation. Data-driven heating value correlations had 24% lower root mean square error (RMSE) than the fundamental combustion calculation approach when compared to daily retrospective proximate analysis. Furthermore, the data-driven method RMSE improved by 7% with the inclusion of ASN data. Future work is to validate by comparing unit performance with and without the inclusion of NUHR as a control parameter for the dynamic neural network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗