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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 613 records · Page 34

Three-Dimensional Geothermal Fairway Mapping: Examples From the Western Great Basin, USA

Elevated permeability along fault systems provides pathways for circulation of geothermal fluids. Accurate location of such fluid flow pathways in the subsurface is crucial to future geothermal development in order to both accurately assess resource potential and mitigate drilling costs by increasing drilling success rates. Employing a variety of surface and subsurface data sets, we present detailed 3D geologic analyses of two Great Basin geothermal systems, the actively producing Brady’s geothermal system and a ‘greenfield’ geothermal prospect at Astor Pass, Nevada. 3D modeling provides the framework for quantitative structural analyses. We combine 3D slip and dilation tendency analysis along fault zones and calculations of fault intersection density in the two geothermal systems with the locations of lithologies capable of supporting dense, interconnected fracture networks. The collocation of these permeability promoting characteristics with elevated heat represent geothermal ‘fairways’, areas with ideal conditions for geothermal fluid flow. Location of geothermal fairways at high resolution in 3D space can help to mitigate the costs of geothermal exploration by providing discrete drilling targets and data-based evaluations of reservoir potential.

15 GEOTHERMAL ENERGY↗

Systems Integration (Fact Sheet)

The Systems Integration (SI) subprogram works closely with industry, universities, and the national laboratories to overcome technical barriers to the large-scale deployment of solar technologies. To support these goals, the subprogram invests primarily in four areas: grid integration, technology validation, solar resource assessment, and balance of system development.

systems integration, grid integration, solar, sola↗

Fast All-Sky Radiation Model for Solar Applications (FARMS): A Brief Overview of Mechanisms, Performance, and Applications: Preprint

Solar radiation can be computed using radiative transfer models, such as the Rapid Radiation Transfer Model (RRTM) and its general circulation model applications, and used for various energy applications. Due to the complexity of computing radiation fields in aerosol and cloudy atmospheres, simulating solar radiation can be extremely time-consuming, but many approximations--e.g., the two-stream approach and the delta-M truncation scheme--can be utilized. To provide a new fast option for computing solar radiation, we developed the Fast All-sky Radiation Model for Solar applications (FARMS) by parameterizing the simulated diffuse horizontal irradiance and direct normal irradiance for cloudy conditions from the RRTM runs using a 16-stream discrete ordinates radiative transfer method. The solar irradiance at the surface was simulated by combining the cloud irradiance parameterizations with a fast clear-sky model, REST2. To understand the accuracy and efficiency of the newly developed fast model, we analyzed FARMS runs using cloud optical and microphysical properties retrieved using GOES data from 2009-2012. The global horizontal irradiance for cloudy conditions was simulated using FARMS and RRTM for global circulation modeling with a two-stream approximation and compared to measurements taken from the U.S. Department of Energy's Atmospheric Radiation Measurement Climate Research Facility Southern Great Plains site. Our results indicate that the accuracy of FARMS is comparable to or better than the two-stream approach; however, FARMS is approximately 400 times more efficient because it does not explicitly solve the radiative transfer equation for each individual cloud condition. Radiative transfer model runs are computationally expensive, but this model is promising for broad applications in solar resource assessment and forecasting. It is currently being used in the National Solar Radiation Database, which is publicly available from the National Renewable Energy Laboratory at http://nsrdb.nrel.gov.

14 SOLAR ENERGY↗

Hydrothermal Liquefaction of Wastewater Treatment Plant Solids

Feedstock cost is the greatest barrier to the commercial production of biofuels. The merits of any thermochemical or biological conversion process are constrained by their applicability to the lowest cost feedstocks. At PNNL, a recent resource assessment of wet waste feedstocks led to the identification of waste water treatment plant (WWTP) solids as a cost-negative source of biomass. WWTP solids disposal is a growing environmental concern [1, 2] and can account for up to half of WWTP operating costs. The high moisture content is well-suited for hydrothermal liquefaction (HTL), avoiding the costs and parasitic energy losses associated with drying the feedstock for incineration. The yield and quality of biocrude and upgraded biocrude from WWTP solids is comparable to that obtained from algae feedstocks but the feedstock cost is $500-1200 less per dry ton. A collaborative project was initiated and directed by the Water Environment & Reuse Foundation (WERF) and included feedstock identification, dewatering, shipping to PNNL, conversion to biocrude by HTL, and catalytic hydrothermal gasification of the aqueous byproduct. Additional testing at PNNL included biocrude upgrading by catalytic hydrotreatment, characterization of the hydrotreated product, and a preliminary techno-economic analysis (TEA) based on empirical results. This short article will cover HTL conversion and biocrude upgrading. The WERF project report with complete HTL results is now available through the WERF website [3]. The preliminary TEA is available as a PNNL report [4].

biocrude upgrading↗

Development of a Dynamic Lidar Uncertainty Framework

As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote-sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote-sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote-sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards for quantifying remote sensing device uncertainty for power performance testing consider uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device and are generally fixed, leading to climatic uncertainty values that apply to the entire measurement campaign. However, real-world experience and a consideration of the fundamentals of the measurement process have shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we describe the development of a new dynamic lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from a field measurement site to assess the ability of the framework to predict errors in lidar-measured wind speed. The results show how uncertainty varies over time and can be used to help select data with different levels of uncertainty for different applications, for example, low uncertainty data for power performance testing versus all data for plant performance monitoring.

17 WIND ENERGY↗

Microalgae Feedstocks for Aviation Fuels

There is significant global interest in developing, testing, and using alternative jet fuels for both commercial and military use in an effort to create a sustainable and stable fuel supply while reducing greenhouse gas emissions. Currently, the aviation industry is entirely dependent on a finite-supply of petroleum based fuel sourced in part by politically and economically unstable regions of the world. Commercial jet fuel use within the contiguous United States (CONUS) was 17.8 billion gallons per year (BGY) in 2009, while jet fuel use in 2010 by the U.S. Air Force (USAF), Navy, and Army was 1.5 BGY, 0.6 BGY, and 0.8 BGY, respectively (Carter et al., 2011). U.S. commercial and military aviation sectors have set ambitious near-term alternative fuel and environmental performance targets. This includes a tentative Federal Aviation Administration (FAA) goal of 1 BGY alternative fuel use by commercial aircraft by 2018. The USAF has set a target of 50% for USAF domestic aviation via alternative fuels by 2016 (0.73 BGY), and 50% of the Navy’s total energy consumption afloat (0.3 BGY) will come from alternative fuels by 2020 (Carter et al., 2011). If these targets become policy, at least 2 BGY of domestically-produced alternative jet fuel will be required by 2020. The Energy Independence and Security Act (EISA) of 2007 established production requirements for domestic alternative fuels under the Renewable Fuel Standard (RFS). For example, 36 billion gallons of renewable fuel must be produced by 2022, of which 21 billion gallons shall be advanced biofuels. EISA defines advanced biofuels as non-corn starch derived biofuels having lifecycle greenhouse gas emissions 50% lower than gasoline. There a number of potential fuel pathways for meeting the RFS. One of these is biomass-based diesel, including jet fuel (Schnepf and Yacobucci, 2013). The U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) has a stated goal in its 2013 Multi-Year Program Plan (USDOE, 2013) to support the RFS through development of “…commercially viable biomass utilization technologies to encourage the creation of a new domestic bioenergy industry…”. BETO has also recognized the potential for aviation biofuels to support the bioenergy industry, seeing drop-in bio-based jet fuels one of the viable alternatives for the aviation industry and the military to meet their ambitious near-term GHG reduction targets (USDOE, 2014). One of the important Multi-year Program Plan Targets (USDOE, 2013) is to establish feedstock resource assessment models to evaluate the geographic, economic, quality and environmental criteria for which 20 million metric tons of ash free dry weight (AFDW) algal biomass can be produced by 2022. Toward meeting the EISA requirements, algal biofuels may offer a number of advantages. They can produce a range of biofuel feedstocks suitable for diesel and aviation fuels. Microalgae, on a strain-specific basis, can be cultivated using impaired water including saline, and/or brackish pumped groundwater or seawater, treated industrial wastewater, municipal sewage effluent, and produced water generated from oil and gas drilling operations. Additionally, microalgae require nitrogen and phosphates as essential nutrients and could provide water treatment co-benefits to municipalities, industry, and the environment.

algae↗