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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

A theoretical study of the electronic transition moment for the C2 Swan band system

Large-scale self-consistent-field plus configuration-interaction calculations have been performed for the a 3Pi u and d 3Pi g states of C2. The theoretical potential curves are in good agreement with those found by a Klein-Dunham analysis of measured molecular constants in terms of shape and excitation energy. The sum of the squares of the theoretical transition moments between the states at 2.44 bohr is 4.12 a.u. which agrees with the results of shock tube measurements. The variation in the sum of the squares of the theoretical moments with internuclear separation agrees with the values of Danylewych and Nicholls (1974). Based on the data for C2 and mother molecules, it is suggested that CI calculations using near Hartree-Fock quality Slater basis sets produce highly reliable transition moments.

Arnold, J. O.↗
DOE OSTI2020

Comparison of Numerical Methods for Modeling the Wave Field Effects Generated by Individual Wave Energy Converters and Multiple Converter Wave Farms

This numerical study compares the wave field generated by the spectral wave action balance code, SNL-SWAN, to the linear-wave boundary-element method (BEM) code, WAMIT. The objective of this study is to assess the performance of SNL-SWAN for modeling wave field effects produced by individual wave energy converters (WECs) and wave farms comprising multiple WECs by comparing results from SNL-SWAN with those produced by the BEM code WAMIT. BEM codes better model the physics of wave-body interactions and thus simulate a more accurate near-field wave field than spectral codes. In SNL-SWAN, the wave field’s energy extraction is modeled parametrically based on the WEC’s power curve. The comparison between SNL-SWAN and WAMIT is made over a range of incident wave conditions, including short-, medium-, and long-wavelength waves with various amounts of directional spreading, and for three WEC archetypes: a point absorber (PA), a pitching flap (PF) terminator, and a hinged raft (HR) attenuator. Individual WECs and wave farms of five WECs in various configuration were studied with qualitative comparisons made of wave height and spectra at specific locations, and quantitative comparisons of the wave fields over circular arcs around the WECs as a function of radial distance. Results from this numerical study demonstrate that in the near-field, the difference between SNL-SWAN and WAMIT is relatively large (between 20% and 50%), but in the far-field from the array the differences are minimal (between 1% and 5%). The resultant wave field generated by the two different numerical approaches is highly dependent on parameters such as: directional wave spreading, wave reflection or scattering, and the WEC’s power curve.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

The Performance of a Spectral Wave Model at Predicting Wave Farm Impacts

For renewable ocean wave energy to support global energy demands, wave energy converters (WECs) will likely be deployed in large numbers (farms), which will necessarily change the nearshore environment. Wave farm induced changes can be both helpful (e.g., beneficial habitat and coastal protection) and potentially harmful (e.g., degraded habitat, recreational, and commercial use) to existing users of the coastal environment. It is essential to estimate this impact through modeling prior to the development of a farm, and to that end, many researchers have used spectral wave models, such as Simulating WAves Nearshore (SWAN), to assess wave farm impacts. However, the validity of the approaches used within SWAN have not been thoroughly verified or validated. Herein, a version of SWAN, called Sandia National Laboratories (SNL)-SWAN, which has a specialized WEC implementation, is verified by comparing its wave field outputs to those of linear wave interaction theory (LWIT), where LWIT is theoretically more appropriate for modeling wave-body interactions and wave field effects. The focus is on medium-sized arrays of 27 WECs, wave periods, and directional spreading representative of likely conditions, as well as the impact on the nearshore. A quantitative metric, the Mean Squared Skill Score, is used. Results show that the performance of SNL-SWAN as compared to LWIT is “Good” to “Excellent”.

environmental impacts↗
DOE OSTI2023

Multi-decade high-resolution regional hindcasts for wave energy resource characterization in U.S. coastal waters

Long-term, high-resolution, regional wave hindcast datasets were generated using unstructured-grid Simulating WAves Nearshore (SWAN) models for the U.S. coastal waters to support nearshore wave energy development in the U.S. including those bordering U.S. territorial islands. The model domains resolved the entire U.S. exclusive economic zones, with a spatial resolution of approximately 200 m nearshore. The regional SWAN models were driven by the global WAVEWATCH III® model outputs and run for a 42-year period from 1979 to 2020. Extensive model validations were performed using buoy observations and altimeter data. Regional resource characterization was performed based on hindcast data points at 2 km from shore and along the 100 m isobath. Aggregations of wave resource parameters were produced, and spatial and seasonal variations were analyzed for all the regions. Wave resource metrics recommended by international standards, including a 3-hour time series of six resource parameters, hourly frequency- and directionally resolved wave spectra at selected “virtual buoy” locations, and average-annual values of omni-directional wave power, significant wave height, and energy period are publicly disseminated through an Amazon Web Service and a Marine Energy Atlas web application tool to facilitate wave energy research and a wide range of coastal ocean applications.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels: 2021 State of Technology

Each year the U.S. Department of Energy Bioenergy Technologies Office (BETO) assesses progress in their research and development efforts toward sustainable production of renewable fuels (DOE 2016) through the annual state of technology (SOT) assessment. The SOT assessment evaluates the impact of the year’s research progress on the modeled minimum fuel selling price (MFSP) for selected biofuel conversion pathways and measures the current state of the technology relative to defined goal case projections. Supply chain sustainability analysis to track and guide research toward improved greenhouse gas (GHG) emissions, energy usage, water usage and other environmental metrics for the pathway is performed by Argonne National Laboratory (Cai et al. 2018, 2020). Technical and cost targets for a projected goal case set for the year 2022 were previously established for the wet waste hydrothermal liquefaction (HTL) and biocrude upgrading pathway and summarized in a design report (Snowden-Swan et al. 2017). Process performance advancements made for HTL and biocrude hydrotreating have resulted yearly reductions in the modeled MFSP relative to the initial SOT (2018) (Snowden-Swan et al. 2020, 2021). This report summarizes the research and associated techno-economic analysis (TEA) for the pathway 2021 SOT. Methods and economic assumptions for the nth plant analysis used for the TEA are consistent with the design report (Snowden-Swan et al. 2017), with the exception of updates in the modeled cost year (2016) and income tax rate (21%).

09 BIOMASS FUELS↗
NASA NTRS1977

Statistical equilibrium in cometary C2. I

Swan-band emission from the C2 molecule provides important information for a study of the physical processes occurring in comets. It is, therefore, a disturbing factor that many quantitative Swan-band observations are in clear contradiction of predictions of resonance fluorescence excitation of the Swan bands. A description is presented of an investigation involving an application of resonance fluorescence theory to C2. The investigation takes into account all important electronic transitions which determine the population distribution of the lowest energy states. It is found that the previous discrepancy for the brighter band sequences disappears.

Swamy, K. S. K.↗
NASA NTRS1995

On the nature of spectral features in peculiar DQ white dwarfs

Spectropolarimetric measurements are presented for the DQ white dwarfs ESO 439-162, LHS 1126, and G225-68, whose spectroscopic features in the optical have been interpreted in the past as pressure-shifted or magnetically shifted C2 Swan bands. The results convincingly demonstrate that none of these objects is strongly magnetic, with upper limits of 30, 3, and 2 MG respectively. Since Bergeron et al. (B 94) have recently ruled out the pressure-shift interpretation for LHS 1126 as well, we discuss alternative physical mechanisms for displacing the Swan bands. Although possibilities for explaining the observed shifts may exist, a comparison of the optical spectra (and that of a similar DQ star, LP 77-57) indicates that the locations and shapes of the profiles in all four objects are virtually identical. This last result suggests instead that a different molecular species could be responsible. A detailed chemical equilibrium analysis of H/He/C mixtures under the physical conditions encountered in the atmospheres of these peculiar objects reveals that C2H is a molecule preferentially formed in the photospheric regions. The nature and evolution of these objects are discussed.

Schmidt, Gary D.↗
NASA NTRS1999

Diagnostics of Laser Produced Plume Under Carbon Nanotube Growth Conditions

This paper presents diagnostic data obtained from the plume of a graphite composite target during carbon nanotube production by the double-pulse laser oven method. The insitu emission spectrum (300 to 650 nm) is recorded at different locations upstream of the target and at different delay times from the lasers (IR and green). Spectral features are identified as emissions from C2 (Swan System: a (sup 3)pi(sub g) - delta (sup 3)pi(sub u) and C3 (Comet Head System: A (sup 1)pi(sub u) - chi (sup 1)sigma(sub u) (sup +). Experimental spectra are compared with computed spectra to estimate vibrational temperatures of excited state C2 in the range of 2500 to 4000 kappa The temporal evolution of the 510 nm band of C2 is monitored for two target positions in various locations which shows confinement of the plume in the inner tube and increase in plume velocity with temperature. The excitation spectra of C2 are obtained by using a dye laser to pump the (0,1) transition of the Swan System and collecting the Laser Induced Fluorescence signal from C2 These are used to obtain "ground-state" rotational and vibrational temperatures which are close to the oven temperature. Images of the plume are also collected and are compared with the spectral measurements.

Arepalli, Sivaram↗
DOE OSTI2020

A High-resolution Regional Wave Resource Characterization For The U.S. West Coast

Objectives/Scope: Wave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies. Methods, Procedures, Process: The wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP’s Climate Forecast System Reanalysis (CFSR) product. Results, Observations, Conclusions: The standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model’s satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast. Novel/Additive Information: The results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA’s 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.

Wang, Taiping↗
DOE OSTI2020

Characteristics and Variability of the Nearshore Wave Resource on the U.S. West Coast

Characterizing the nearshore wave resource at a regional scale poses a great challenge because high-quality wave data are required. This paper presents a detailed analysis of nearshore wave climate and resource characterization on the U.S. West Coast based on a 32-year, regional wave hindcast. Resource characterization closely followed the International Electrotechnical Commission standards. The wave hindcast data were generated from an unstructured-grid SWAN model with approximately 300 m grid resolution in the nearshore region. Statistics of six IEC wave resource parameters at the 50 m water depth were calculated for four sub-regions along the coast, including Washington, Oregon, and Northern and Southern California. Results indicate that the Washington and Oregon coast has a similar nearshore wave resource. The wave resource in Southern California is significantly less than that of the Washington and Oregon coast. Alongshore and cross-shore variabilities of wave power were assessed. Temporal variability, at seasonal, inter-annual, and decadal scales were analyzed. Overall, strong seasonal variation is observed; high wave energy occurs in the winter months and calm seas in the summer. Finally, extreme environmental conditions, i.e., the 100-year extreme environmental contours, for different locations along the West Coast were investigated.

wave resource characterization, nearshore, west co↗
DOE OSTI2021

Wave resource characterization at regional and nearshore scales for the U.S. Alaska coast based on a 32-year high-resolution hindcast

A wave resource characterization was performed for the southern coast of Alaska based on a 32-year hindcast covering the period from 1979 to 2010. The characterization closely followed International Electrotechnical Commission (IEC) Technical Specifications. An unstructured-grid Simulating WAves Nearshore (SWAN) model, which had an approximate spatial resolution of 300 m within 30 km from the nearest shoreline, was developed. Additionally, extensive model validation and error characterization was performed. The model was found to perform well with an average absolute percent error of 8.6% in significant wave height, averaged over 18 buoys. Statistics for the six IEC wave resource parameters were calculated and aggregated at 20 km from shore to quantify the incident wave power and its variability at a regional scale. The southern coast of the Aleutian Archipelago was found to have the most available wave energy in the region. A nearshore resource assessment was performed by evaluating resource hotspots located 1 km from shore. More than 900 nearshore stations had an Optimum Hotspot Identifier value of 5 (kW/m) at diverse water depths, thereby positioning Alaska as a promising location for wave energy development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Wave climate and energy resources in American Samoa from a 42-year high-resolution hindcast

Here, this paper presents an analysis of the wave climate and a characterization of the wave energy resources in American Samoa, a U.S. territory covering seven south central Pacific islands and atolls. A numerical wave model based on WAVEWATCH III® and unstructured SWAN was developed, validated, and executed for 1979–2020 to generate a hindcast dataset suitable for resource characterization. Model-data comparisons were performed with measurements collected in situ and from satellite-based altimeters. The model was found to perform well with a bias in significant wave height of -0.14 m and -0.06 m against buoy and altimeters, respectively. The multimodal sea state of American Samoa is investigated by identifying the sources of energy reaching the islands and partitioning the wave spectrum accordingly. The wave resources characterization follows the International Electrotechnical Commission Technical Specifications to be compatible with studies performed for other U.S. regions. The average omnidirectional wave power at 2 km from shore around Tutuila, the main island of American Samoa, is 14 kW/m. Locations east and west of the islands have a more consistent resource throughout the year because the northwest and southwest swells that are dominant during different seasons complement each other.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels: 2020 State of Technology

Data from Pacific Northwest National Laboratory’s conversion hydrothermal liquefaction (HTL) program for wet waste was used to update the pathway techno-economic analysis (TEA) for the fiscal year 2020 State of Technology (2020 SOT). The modeled fuel blendstock MFSP for the 2020 SOT is estimated at $4.50/GGE (with ammonia stripping of the AP), a reduction of $0.61/GGE, or 12%, relative to the 2019 SOT (Snowden-Swan et al. 2020). Progress in the HTL area includes increased reactor LHSV from 3.6 to 4.0 and a newly designed staged approach for the sludge pumping and heating, resulting in a 1 cent and 26 cent reduction in modeled MFSP, respectively. The newly designed heat exchanger configuration is less material and capital intensive than the previous SOT, and provides a system design that is more scalable with regard to practical fabrication limitations. Further improvements may be possible with the use of core inserts to enhance tube velocity and heat transfer rates. Biocrude hydrotreating research progress improved weight hourly space velocity (WHSV) from 0.67 to 0.72 hr-1 in the guard bed and from 0.39 to 1.02 hr-1 in the main hydrotreating bed, a 7% and 162% improvement, respectively. Hydrotreating performance was not sacrificed at the higher throughput rates and catalyst activity remained stable over the run. The demonstrated increase in WHSVs reduced the modeled MFSP by $0.34/GGE.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels: 2022 State of Technology

Data from Pacific Northwest National Laboratory’s (PNNL) conversion hydrothermal liquefaction (HTL) program for wet waste was used to update the pathway techno-economic analysis (TEA) for the fiscal year 2022 State of Technology (2022 SOT). Figure S.1 shows the modeled minimum fuel selling price (MFSP) for the 2022 SOT, along with the previous years’ SOTs (Snowden-Swan et al. 2020, 2021, 2022). These costs are for a HTL plant scale of 110 dry ton/day sludge feed and a larger centralized upgrading plant scale of 38 million gallons/year biocrude feed, commensurate with the design case. All costs were updated to 2020 dollars. Corresponding cost breakdowns and technical parameters for each case are given in Appendix B. In previous years’ analyses options with and without ammonia (NH 3 ) stripping treatment of the HTL aqueous phase recycle stream were included in the analysis to account for cases with direct recycle of untreated HTL aqueous phase back to the wastewater treatment plant. In the FY21 SOT assessment however, system boundaries for the analysis were adjusted to reflect separate ownership/operatorship for the HTL plant and with that, nutrient surcharge fees associated with disposal of the aqueous phase wastewater to a municipal sewer system were incorporated to provide an improved accounting of true disposal costs for a standalone plant. With these changes, there is no significant cost difference between the case including ammonia removal and the case excluding ammonia removal and therefore the “no NH3 removal” options will not be included in the 2022 and future SOTs.

09 BIOMASS FUELS↗
DOE OSTI2021

Modeling Sea Ice Effects for Wave Energy Resource Assessments

Wave-generated power has potential as a valuable coastal resource, but the wave climate needs to be mapped for feasibility before wave energy converters are installed. Numerical models are used for wave resource assessments to quantify the amount of available power and its seasonality. Alaska is the U.S. state with the longest coastline and has extensive wave resources, but it is affected by seasonal sea ice that dampens the wave energy and the full extent of this dampening is unknown. To accurately characterize the wave resource in regions that experience seasonal sea ice, coastal wave models must account for these effects. The aim of this study is to determine how the dampening effects of sea ice change wave energy resource assessments in the nearshore. Here, we show that by combining high-resolution sea ice imagery with a sea ice/wave dampening parameterization in an unstructured grid, the Simulating Waves Nearshore (SWAN) model improves wave height predictions and demonstrates the extent to which wave power decreases when sea ice is present. The sea ice parametrization decreases the bias and root mean square errors of wave height comparisons with two wave buoys and predicts a decrease in the wave power of up to 100 kW/m in areas around Prince William Sound, Alaska. The magnitude of the improvement of the model/buoy comparison depends on the coefficients used to parameterize the wave–ice interaction.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Influence of Time and Frequency Domain Wave Forcing on the Power Estimation of a Wave Energy Converter Array

Industry-specific tools for analyzing and optimizing the design of wave energy converters (WECs) and associated power systems are essential to advancing marine renewable energy. This study aims to quantify the influence of phase information on the device power output of a virtual WEC array. We run the phase-resolving wave model FUNWAVE-TVD (Total Variation Diminishing) to generate directional waves at the PacWave South site offshore from Newport, Oregon, where future WECs are expected to be installed for testing. The two broad cases presented correspond to mean wave climates during warm months (March–August) and cold months (September–February). FUNWAVE-TVD time series of sea-surface elevation are then used in WEC-Sim, a time domain numerical model, to simulate the hydrodynamic response of each device in the array and estimate their power output. For comparison, WEC-Sim is also run with wave energy spectra calculated from the FUNWAVE-TVD simulations, which do not retain phase information, and with wave spectra computed using the phase-averaged model Simulating WAves Nearshore (SWAN). The use of spectral data in WEC-Sim requires a conversion from frequency to time domain by means of random superposition of wave components, which are not necessarily consistent because of the linear assumption implicit in this method. Thus, power response is characterized by multiple realizations of the wave climates.

13 HYDRO ENERGY↗