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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Estimation of economic impacts of cellulosic biofuel production: a comparative analysis of three biofuel pathways: Economic impacts of biofuel production

The development of a cellulosic biofuel industry utilizing domestic biomass resources is expected to create opportunities for economic growth resulting from the construction and operation of new biorefineries. We applied an economic input-output model to estimate potential economic impacts, particularly gross job growth, resulting from the construction and operation of biorefineries using three different technology pathways: 1) cellulosic ethanol via biochemical conversion in Iowa, 2) renewable diesel blendstock via biological conversion in Georgia, and 3) renewable diesel and gasoline blendstock via fast pyrolysis in Mississippi. Combining direct, indirect, and induced effects, capital investment associated with the construction of a biorefinery processing 2,000 dry metric tons of biomass per day (DMT/day) could yield between 5,960 and 8,470 full-time equivalent (FTE) jobs during the construction period. Fast pyrolysis biorefineries produce the most jobs on a project level thanks to the highest capital requirement among the three pathways. Normalized for one million dollars of capital investment, the fast pyrolysis biorefineries are estimated to yield slighter more jobs (12.1 jobs) than the renewable diesel (11.8 jobs) and the cellulosic ethanol (11.6 jobs) biorefineries. While operating biorefineries is not labor-intensive, the annual operation of a 2,000 DMT/day biorefinery could support between 720 and 970 jobs when the direct, indirect, and induced effects are considered. The major factor, which results in the variations among the three pathways, is the type of biomass feedstock used for biofuels. The agriculture/forest, services, and trade industries are the primary sectors that will benefit from the ongoing operation of biorefineries.

Biofuels↗
DOE OSTI2021

A novel defoamer for processing nuclear waste: Testing and performance

Abstract Legacy radioactive waste from nuclear weapons material processing is the biggest environmental challenge in the state of South Carolina, and one of the biggest in the United States. Although substantial progress has been made in processing and vitrifying high‐level radioactive waste at the Savannah River site, approximately 35 million gallons remains to be treated and dispositioned. In this article, we show the development of a new defoamer for use in the processing of high‐level radioactive waste. The application of the new defoamer is not only more effective at controlling foam but will shorten the batch processing time leading to safer and more efficient processing. This has the potential to help shorten the overall site mission lifetime, saving the federal government hundreds of millions of dollars. The novel aspect of the new defoamer is its effectiveness and stability in the harsh conditions needed for processing high‐level radioactive waste: high temperatures, pH 4–13, strong oxidizing and reducing agents, and numerous metal catalysts. The defoamer will replace an existing antifoam agent that decomposes to form multiple flammable gases. Because the existing antifoam agent decomposes quickly, processing changes increased processing time. Statement of novelty We demonstrate that a new defoamer has been developed for use in processing high‐level radioactive waste. This novel defoamer is effective and stable in the harsh processing conditions with no detectable flammable by‐products. Because the existing antifoam agent decomposes quickly, processing changes, including lowering acid addition rates and evaporation rates, increased processing time. The new defoamer is not only more effective at controlling foam but will shorten the batch processing time and lead to safer and more efficient processing by eliminating the production of flammable gases. Statement of industrial relevance Foaming is of great concern in many industrial processes involving three‐phase gas/liquid/fine‐solids systems, like in water evaporation, mineral floatation, air sparging in situ remediation techniques, and in those found in the paper industry.

Lambert, Dan P.↗
DOE OSTI2019

Does River Restoration Increase Fish Abundance and Survival or Concentrate Fish? The Effects of Project Scale, Location, and Fish Life History

Abstract Despite billions of dollars spent on various river restoration techniques, we still find ourselves debating whether habitat restoration increases fish abundance or concentrates fish. Based on the available literature, I discuss three important questions related specifically to the restoration of salmonid habitat: (1) “Does river restoration increase fish abundance or concentrate fish?”; (2) “Does river restoration increase fish survival or increase abundance?”; and (3) “Does the size or amount of river restoration influence fish response?” First, there is scant evidence to support the contention that river restoration leads to the concentration of fish at restoration projects. Second, the literature suggests that river restoration may lead to increased survival, increased abundance, or both. Third, recent studies have found little relationship between restoration project length and physical or biological response. The scientific literature does suggest that fish response to restoration varies greatly depending on the watershed template, location, and characteristics of the habitat restoration, and the life history of and limiting factors for a species. Thus, adequately determining whether changes in fish abundance observed in a restored area are due to increased movement, survival, or the amount of restoration will require detailed monitoring of these factors simultaneously.

Roni, Philip↗
DOE OSTI2025

Modelling the Effects of Wetland Restoration on Coastal Hydrology: A Case Study of Elkhorn Slough Watershed, California

ABSTRACT Coastal wetlands, some of the most productive ecosystems on Earth, provide critical ecosystem services, including support of biodiversity, carbon sequestration and flood protection. In recent decades, these ecosystems have experienced extensive coastal wetland loss. Coastal wetland restoration provides a beacon of hope, offering a chance to reclaim these important habitats. However, even with billions of dollars invested worldwide in restoring coastal wetlands, we still lack comprehensive knowledge about the effectiveness of these restoration efforts in recovering wetland ecosystem functions and how future climate change may affect these efforts. The ability to evaluate how these ecosystems will function in the future is vital for examining current investments and developing future protection and management plans. We selected Elkhorn Slough, a tidal estuary, in California, to investigate the impact of wetland restoration and sea level rise (SLR) on coastal hydrology using the process‐based coastal hydrologic model, Advanced Terrestrial Simulator (ATS), informed by site‐specific data. We designed a novel modelling workflow for incorporating wetland restoration features into land cover and soil properties for the model parameterization. The validation results demonstrate a strong agreement between modelled and observed data. We studied the characteristics of coastal watershed hydrology, then focused on the surface water dynamics at two wetland sites within Elkhorn Slough, a reference site and a restored site. Our simulation results indicate that the restored site successfully maintains surface elevation, resulting in reduced surface inundation. We also examined the impact of wetland restoration under expected SLR over the next few decades. The low‐lying Yampah Marsh, the reference site, is likely to be inundated due to future SLR when highest tides arrive, while a higher percentage of Hester Marsh, the restored site, would retain marsh vegetation in coming decades, regardless of tidal conditions. Our study provides important information for examining the outcome of restoration practices that include surface elevation in tidal wetlands under climate changes.

advanced terrestrial simulator↗
DOE OSTI2023

Permethylation as a strategy for high–molecular–weight polysaccharide structure analysis by nuclear magnetic resonance—Case study of Xylella fastidiosa extracellular polysaccharide

Current practices for structural analysis of extremely large-molecular-weight polysaccharides via solution-state nuclear magnetic resonance (NMR) spectroscopy incorporate partial depolymerization protocols that enable polysaccharide solubilization in suitable solvents. Non-specific depolymerization techniques utilized for glycosidic bond cleavage, such as chemical degradation or ultrasonication, potentially generate structural fragments that can complicate complete and accurate characterization of polysaccharide structures. Utilization of appropriate enzymes for polysaccharide degradation, on the other hand, requires prior structural knowledge and optimal enzyme activity conditions that are not available to an analyst working with novel or unknown compounds. Herein, we describe an application of a permethylation strategy that allows the complete dissolution of intact polysaccharides for NMR structural characterization. This approach is utilized for NMR analysis of Xylella fastidiosa extracellular polysaccharide (EPS), which is essential for the virulence of the plant pathogen that affects multiple commercial crops and is responsible for multibillion dollar losses each year.

13C↗
DOE OSTI2015

Is $50/MWh solar for real? Falling project prices and rising capacity factors drive utility-scale PV toward economic competitiveness

Recently announced low-priced power purchase agreements (PPAs) for US utility-scale photovoltaic (PV) projects suggest $50/MWh solar might be viable under certain conditions. To explore this possibility, this paper draws on an increasing wealth of empirical data to analyze trends in three of the most important PPA price drivers: upfront installed project prices, operations, and maintenance (O&M) costs, and capacity factors. Average installed prices among a sample of utility-scale PV projects declined by more than one third (from 5.8/W AC to 3.7/WAC) from the 2007–2009 period through 2013, even as costlier systems with crystalline-silicon modules, sun tracking, and higher inverter loading ratios (ILRs) have constituted an increasing proportion of total utility-scale PV capacity (all values shown here are in 2013 dollars). Actual and projected O&M costs from a very small sample of projects appear to range from $20–$40/kW AC -year. Furthermore, the average net capacity factor is 30% for projects installed in 2012, up from 24% for projects installed in 2010, owing to better solar resources, higher ILRs, and greater use of tracking among the more recent projects. Based on these trends, a pro-forma financial model suggests that $50/MWh utility-scale PV is achievable using a combination of aggressive-but-achievable technical and financial input parameters (including receipt of the 30% federal investment tax credit). Although the US utility-scale PV market is still young, the rapid progress in the key metrics documented in this paper has made PV a viable competitor against other utility-scale renewable generators, and even conventional peaking generators, in certain regions of the country.

14 SOLAR ENERGY↗
DOE OSTI2016

Offshore Wind Energy

In 1991, the Vindeby Offshore Wind Farm, the first offshore wind farm in the world, started feeding electricity to the grid off the coast of Lolland, Denmark. Since then, offshore wind energy has developed from this early experiment to a multibillion dollar market and an important pillar of worldwide renewable energy production. Unit sizes grew from 450 kW at Vindeby to the 7.5 MW-class offshore wind turbines (OWT ) that are currently (by October 2014) in the prototyping phase. This chapter gives an overview of the state of the art in offshore wind turbine (OWT) technology and introduces the principles of modeling and simulating an OWT. The OWT components -- including the rotor, nacelle, support structure, control system, and power electronics -- are introduced, and current technological challenges are presented. The OWT system dynamics and the environment (wind and ocean waves) are described from the perspective of OWT modelers and designers. Finally, an outlook on future technology is provided. The descriptions in this chapter are focused on a single OWT -- more precisely, a horizontal-axis wind turbine -- as a dynamic system. Offshore wind farms and wind farm effects are not described in detail in this chapter, but an introduction and further references are given.

17 WIND ENERGY↗
DOE OSTI2022

Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources

We live in momentous times. The science community is empowered with an arsenal of cosmic messengers to study the universe in unprecedented detail. Gravitational waves, electromagnetic waves, neutrinos, and cosmic rays cover a wide range of wavelengths and timescales. Combining and processing these datasets that vary in volume, speed, and dimensionality requires new modes of instrument coordination, funding, and international collaboration with a specialized human and technological infrastructure. In tandem with the advent of large-scale scientific facilities, the last decade has experienced an unprecedented transformation in computing and signal-processing algorithms. The combination of graphics processing units, deep learning, and the availability of open source, high-quality datasets has powered the rise of artificial intelligence. This digital revolution now powers a multibillion dollar industry, with far-reaching implications in technology and society. In this chapter, we describe pioneering efforts to adapt artificial intelligence algorithms to address computational grand challenges in multi-messenger astrophysics. We review the rapid evolution of these disruptive algorithms, from the first class of algorithms introduced in early 2017 to the sophisticated algorithms that now incorporate domain expertise in their architectural design and optimization schemes. We discuss the importance of scientific visualization and extreme-scale computing in reducing time-to-insight and obtaining new knowledge from the interplay between models and data.

Artificial Intelligence↗
DOE OSTI2022

Combining Simulation and Optimization to Derive Operating Policies for a Concentrating Solar Power Plant

Optimizing short-term decisions over a rolling horizon and/or using deterministic penalties to capture system stochasticity can lead to myopic policies that fail to consider unplanned events and their long-term adverse effects. We present a methodology that integrates an off-line optimization model with a simulation procedure to determine the profitability of different operating strategies; specifically, the latter is used to generate additional constraints for the former when failures occur according to system component operating lifetimes that (i) are subject to exogenous uncertainty, and (ii) may degrade more quickly under specific operating conditions. We use the feedback provided by the simulation model in a parametric analysis to obtain penalties that can be used in short-term operations scheduling to maximize the long-term revenues obtained by the optimization model. We apply this research to a concentrating solar power plant; our results show that the methodology can be used to choose an operating policy that balances maximizing profit while accounting for maintenance costs. Integrating the optimization model with a simulation procedure reveals that aggressive prices for cycling yield about 55% fewer startups and 30% fewer failures compared to using a more typical start-up operating strategy, and can save hundreds of thousands to millions of dollars in repair costs over the lifetime of the plant.

concentrating solar power↗
DOE OSTI2012

Defining and Computing a Valued Based Cyber-Security Measure

In earlier work, we presented a value based measure of cybersecurity that quantifies the security of a system in concrete terms, specifically, in terms of how much each system stakeholder stands to lose (in dollars per hour of operation) as a result of security threats and system vulnerabilities; our metric varies according to the stakes that each stakeholder has in meeting each security requirement. In this paper, we discuss the specification and design of a system that collects, updates, and maintains all the information that pertains to estimating our cybersecurity measure, and offers stakeholders quantitative means to make security-related decisions.

Algorithms↗
DOE OSTI2021

Attributable human-induced changes in the magnitude of flooding in the Houston, Texas region during Hurricane Harvey

Abstract The human influence on precipitation during tropical cyclones due to the global warming is now well documented in the literature. Several studies have found increases in Hurricane Harvey’s total precipitation over the Greater Houston area ranging from the Clausius-Clapeyron limit of 7% to as much as 38% locally. Here we use a hydraulic model to translate these attribution statements about precipitation to statements about the resultant flooding and associated damages. We find that while the attributable increase in the total volume of flood waters is the same as the attributable increase in precipitation, the attributable increase in the total area of the flood is less. However, we also find that in the most heavily flooded parts of Houston, the local attributable increases in flood area and volume are substantially larger than the increase in total precipitation. The results of this storyline attribution analysis of the Houston flood area are used to make an intuitive best estimate of the cost of Hurricane Harvey attributable to anthropogenic global warming as thirteen billion US dollars.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improving sustainable tropical forest management with voluntary carbon markets

Due to a rapidly changing climate, voluntary carbon markets are gaining momentum and should be leveraged to improve and expand tropical sustainable forest management plans, limiting carbon emissions and enhancing critical carbon sinks. By sequestering more carbon than any other terrestrial ecosystem — ~1 Pg C yr –1 — tropical forests provide crucial natural climate solutions and opportunities in the evolving voluntary carbon market. Here, we argue that some issues with the current sustainable management of tropical forests can be addressed using carbon-focused sustainable forest management (SFM + C) to leverage financial resources for tropical forest carbon storage and sequestration. We suggest an extended harvest cycle in SFM + C and calculate an associated potential increase in aboveground carbon stocks of commercial timber of 1.26 Mg C ha –1 after each cycle in the Brazilian Amazon. The additional carbon storage due to a longer harvest cycle can generate carbon credits worth 152.6 (SD 9.2) US dollars per hectare in 40 years. Considering an average cost of 180 BRL per m3 of commercial timber delivered to the sawmill, an SFM + C plan with a 40-year cycle could generate 28.7% (SD 2.5) more profit than 35-year cycles by combining timber and carbon revenues. A robust carbon price could incentivize the further extension of harvest cycles, providing a monetary return that offsets the opportunity cost intrinsic to harvesting under longer cycles. Lastly, we highlight research needs to support tropical SFM + C, which can be part of a global collective effort to limit global warming to below 2 °C above pre-industrial levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Optimizing adiabatic quantum program compilation using a graph-theoretic framework

Adiabatic quantum computing has evolved in recent years from a theoretical field into an immensely practical area, a change partially sparked by D-Wave System’s quantum annealing hardware. These multimillion-dollar quantum annealers offer the potential to solve optimization problems millions of times faster than classical heuristics, prompting researchers at Google, NASA and Lockheed Martin to study how these computers can be applied to complex real-world problems such as NASA rover missions. Unfortunately, compiling (embedding) an optimization problem into the annealing hardware is itself a difficult optimization problem and a major bottleneck currently preventing widespread adoption. Additionally, while finding a single embedding is difficult, no generalized method is known for tuning embeddings to use minimal hardware resources. To address these barriers, we introduce a graph-theoretic framework for developing structured embedding algorithms. Using this framework, we introduce a biclique virtual hardware layer to provide a simplified interface to the physical hardware. Additionally, we exploit bipartite structure in quantum programs using odd cycle transversal (OCT) decompositions. By coupling an OCT-based embedding algorithm with new, generalized reduction methods, we develop a new baseline for embedding a wide range of optimization problems into fault-free D-Wave annealing hardware. Furthermore, to encourage the reuse and extension of these techniques, we provide an implementation of the framework and embedding algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Efficiently embedding QUBO problems on adiabatic quantum computers

Adiabatic quantum computers like the D-Wave 2000Q can approximately solve the QUBO problem, which is an NP-hard problem, and have been shown to outperform classical computers on several instances. Solving the QUBO problem literally means solving virtually any NP-hard problem like the traveling salesman problem, airline scheduling problem, protein folding problem, genotype imputation problem, thereby enabling significant scientific progress, and potentially saving millions/billions of dollars in logistics, airlines, healthcare and many other industries. Yet, before QUBO problems are solved on quantum computers, they must be embedded (or compiled) onto the hardware of quantum computers, which in itself is a very hard problem. Here, we propose an efficient embedding algorithm, that lets us embed QUBO problems fast, uses less qubits and gets the objective function value close to the global minimum value. We then compare the performance of our embedding algorithm to that of D-Wave’s embedding algorithm, which is the current state of the art, and show that our embedding algorithm convincingly outperforms D-Wave’s embedding algorithm. Our embedding approach works with perfect Chimera graphs, i.e., Chimera graphs with no missing qubits.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Using yttrium as an indicator to estimate total rare earth element concentration: a case study of anthracite-associated clays from northeastern Pennsylvania

Abstract This study demonstrated using yttrium (Y) as an indicator to estimate the total rare earth element and Y contents (REY) in coal-associated samples and to facilitate selection of samples with high REY assays in a fast and inexpensive manner. More than 10 anthracite-associated samples were collected from each of three Pennsylvanian sites (sites B, J and C) based on Thorium gamma ray logging suggesting high REY content. Several samples from each site were analyzed by ICP-MS to determine the rare earth distribution patterns and to establish the site-specific linear equations of Y and REY. The Y contents of the remaining samples were measured by a portable X-ray fluorescence analyzer, and the REY values were estimated based on the site-specific linear equation developed earlier. R-squared values above 0.70 were obtained for all the estimation equations from all three sites on both a whole sample basis and an ash basis. Previously, ash content has been widely used as an indicator of high REY content. This may not be applicable for a specific site. Site B in this study is an example where ash contents could not be statistically correlated with REY, so using Y for estimation is more applicable. The demonstrated sample screening process is suitable for samples from sites that share more similar distribution patterns (either MREY or LREY or HREY) as well as for samples from sites that share multiple distribution patterns (LREY/MREY/HREY) depending on the desirable accuracy. The demonstrated process lowers the analytical cost from $70 to 80 dollars per sample to $10–15 per sample while significantly reducing the processing time and acid consumption for ICP digestion. This is particularly true when a relatively large sample size is involved, for example, 100 samples from one site analyzed by ICP-MS/OES.

Yang, Xiaojing↗
DOE OSTI2025

60 years of science in ICF: from conception to scientific breakeven on the National Ignition Facility

The recent achievements of a burning plasma, fusion ignition, and scientific energy gain with deuterium-tritium (DT) fuel at Lawrence Livermore National Laboratory’s National Ignition Facility (NIF) represents a major milestone in the development of inertial confinement fusion (ICF) and all of fusion research. In these experiments, fuel pressures well in excess of hundreds of GBars were achieved in the compressed fuel, and robust alpha heating of the fuel, far in excess of the energy provided by the implosion, were demonstrated for the first time. These achievements occurred 60 years after the inception of ICF and the first laser demonstration, and were made possible by more than five decades of research at laser facilities around the world. Advances in laser technology both in wavelength and precision, motivated by improved understanding of laser-plasma interaction physics and the demands of targets; improvements in target fabrication inspired by the need to control and minimize hydrodynamic instabilities in the implosion; and multi-dimensional simulations and diagnostics have been critical to this achievement. This paper will summarize the scientific and technical advances, the surprises, and the challenges that had to be overcome to achieve these goals.

fusion↗
DOE OSTI2018

Security of additive manufacturing: Attack taxonomy and survey

Additive manufacturing (AM) is a rapidly growing, multibillion dollar industry. AM is increasingly being used to manufacture functional parts, including components of safety critical systems in aerospace, automotive, and other industries. This makes AM an attractive attack target. AM Security is a fairly new field of research that addresses this novel threat. Here, this paper serves dual purposes: For researchers just entering AM security, we provide an in-depth introduction to this highly multi-disciplinary research field. And, for active researchers in the field, this paper provides a comprehensive, structured survey of the state of the art as well as our proposal for attack taxonomies.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Techno-Economic Analysis of Liquid Fuel Production from Woody Biomass via Hydrothermal Liquefaction (HTL) and Upgrading

A series of experimental work was conducted to convert woody biomass to gasoline and diesel range products via hydrothermal liquefaction (HTL) and catalytic hydroprocessing. Based on the best available test data, a techno-economic analysis (TEA) was developed for a large scale woody biomass based HTL and upgrading system to evaluate the feasibility of this technology. In this system, 2000 dry metric ton per day woody biomass was assumed to be converted to bio-oil in hot compressed water and the bio-oil was hydrotreated and/or hydrocracked to produce gasoline and diesel range liquid fuel. Two cases were evaluated: a stage-of-technology (SOT) case based on the tests results, and a goal case considering potential improvements based on the SOT case. Process simulation models were developed and cost analysis was implemented based on the performance results. The major performance results included final products and co-products yields, raw materials consumption, carbon efficiency, and energy efficiency. The overall efficiency (higher heating value basis) was 52% for the SOT case and 66% for the goal case. The production cost, with a 10% internal rate of return and 2007 constant dollars, was estimated to be $1.29 /L for the SOT case and $0.74 /L for the goal case. The cost impacts of major improvements for moving from the SOT to the goal case were evaluated and the assumption of reducing the organics loss to the water phase lead to the biggest reduction in the production cost. Sensitivity analysis indicated that the final products yields had the largest impact on the production cost compared to other parameters. Plant size analysis demonstrated that the process was economically attractive if the woody biomass feed rate was over 1,500 dry tonne/day, the production cost was competitive with the then current petroleum-based gasoline price.

Techno-economic analysis, Biomass, Hydrothermal li↗