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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Environmental Characterization Scans Using Sodium-Iodide Gamma Spectroscopy to Determine Ra-226 Concentration in Surface Soil - 16326

The recent natural gas drilling boom has brought heightened attention to the issue of TENORM waste management. Radioactive residues from the extraction, treatment, and purification of materials containing uranium and thorium, or their progeny, pose a public health hazard primarily in the form of ground water contamination. Hydraulic fracturing can liberate formation waters from shale; the high salinity of which can cause radium to move with the water to the surface. The disposal and handling of this water has been a subject of public controversy. For soil remediation projects, radium-226 is generally one of the radionuclides of concern due to its alpha emissions. However performing a survey scan for Ra-226 is difficult because its photon emissions are low energy and have minimal probability of emission per decay (186.2 keV, 3.3% abundance). Additionally resolving its emission from U-235 (185.7 keV, 57% abundance) with field instrumentation is not feasible. Therefore detection of Ra-226 relies on the presence and photon emissions of its progeny. This paper outlines methodology for calculating the minimum detectable concentration of Ra-226 in characterization scans using a sodium-iodide detector array coupled with a multi-channel analyzer. Using progeny ingrowth as a detection proxy requires knowing decay time in order to determine progeny emission rates. Knowledge of site history, process, and prior survey results can be key in determining an accurate decay time. However in the absence of such information in-situ measurements can be used to estimate decay time by comparing observed progeny emission ratios against established values. These values are determined using Oak Ridge National Laboratory's ORIGEN-ARP program to generate photon energy spectra for Ra-226 and its progeny at specified time intervals. Once decay time is established, the detector's minimum detectable concentration can be calculated by synthesizing the expected emission spectra and Los Alamos National Laboratory's Monte Carlo N-Particle transport code to simulate detector response. Traditionally, one of the steps in calculating a system's minimum detectable concentration is to place an appropriate button source under the detector, record the response, and then move the source by a specified increment. This process is repeated until the detector's spatial efficiency has been mapped. Due to the impracticality of performing this with Ra-226 button sources of varying decay times, Monte Carlo N-Particle transport code was utilized to determine the detector's spatial efficiency. A dime sized source with the established emission spectra was placed into the center of a rectangle of soil. This rectangle, including the source, was used as a lattice element to fill the region of space below the detector. The simulation was designed to track the energy distribution of pulses created in the sodium iodide crystal using the F8 tally, and was setup to isolate each source; thereby correlating detector response to source position. The simulation output required post-processing to determine conversion factors from counts per second to disintegrations per second. Post-processing accounted for subtraction of the Compton continuum, and average the data over the scanning pattern to obtain the expected spatial sensitivity during a characterization study. This was performed for the following photo-peaks: 609 keV (Bi-214), and 1764 keV (Bi-214). For calculation of the scan minimum detectable concentration, the surveyor efficiency coefficient from NUREG 1507 was supplanted in favor of a scan speed deviation factor. This was used because the detector utilizes computerized data collection (spatial and spectral). This report finds that, for two shielded 10.16 cm x 10.16 cm x 40.64 cm sodium-iodide crystals with integrated multi-channel analyzers, the minimum detectable concentration in surface soils is less than 1 pCi per gram Ra-226 for a 1 second survey measurement. These results assume a volumetric source with a maximum depth of 15.24 cm and a minimum decay time of 21 days. Verification of the system's capabilities was performed by sending soil samples from scanned areas, and locations where in-situ measurements were performed, to an independent laboratory for analysis. The laboratory results demonstrated that scanned area was principally comprised of soil containing less than 1 pCi per gram Ra-226. This borders the system MDC and it underestimated the concentration of radium in the soil. The probable causes of this is escape of radon gas from the surface soil. Radon is the daughter of radium, and has a high mobility in soil. If the gas escapes, then the progeny used as the detection proxy will be present in lower than expected concentrations. Radionuclide identification using high volume sodium-iodide crystals in low level characterization scans is demonstrated to be possible. Further system refinement will focus on developing a methodology to estimate a radon escape factor for site specific use. Accounting for radon escape in the top 15.24 cm of soil will allow the system to better estimate Ra-226 concentrations in soil. This is a significant advancement over the gross counting statistics used in most studies to satisfy MARSSIM survey requirements, because it will increase stakeholder confidence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

An Asynchronous Many-Task Implementation of In-Situ Statistical Analysis using Legion.

In this report, we propose a framework for the design and implementation of in-situ analy- ses using an asynchronous many-task (AMT) model, using the Legion programming model together with the MiniAero mini-application as a surrogate for full-scale parallel scientific computing applications. The bulk of this work consists of converting the Learn/Derive/Assess model which we had initially developed for parallel statistical analysis using MPI [PTBM11], from a SPMD to an AMT model. In this goal, we propose an original use of the concept of Legion logical regions as a replacement for the parallel communication schemes used for the only operation of the statistics engines that require explicit communication. We then evaluate this proposed scheme in a shared memory environment, using the Legion port of MiniAero as a proxy for a full-scale scientific application, as a means to provide input data sets of variable size for the in-situ statistical analyses in an AMT context. We demonstrate in particular that the approach has merit, and warrants further investigation, in collaboration with ongoing efforts to improve the overall parallel performance of the Legion system.

Pebay, Philippe Pierre↗
DOE OSTI2019

Chlorophyll–carotenoid excitation energy transfer and charge transfer in Nannochloropsis oceanica for the regulation of photosynthesis

Nonphotochemical quenching (NPQ) is a proxy for photoprotective thermal dissipation processes that regulate photosynthetic light harvesting. The identification of NPQ mechanisms and their molecular or physiological triggering factors under in vivo conditions is a matter of controversy. In this work, to view chlorophyll (Chl)–zeaxanthin (Zea) excitation energy transfer (EET) and charge transfer (CT) as possible NPQ mechanisms, we performed transient absorption (TA) spectroscopy on live cells of the microalga Nannochloropsis oceanica . We gained evidence for the operation of both EET and CT quenching by observing spectral features associated with the Zea S 1 and Zea •+ excited-state absorption (ESA) signals, respectively, after Chl excitation. Knockout mutants for genes encoding either violaxanthin de-epoxidase or LHCX1 proteins exhibited strongly inhibited NPQ capabilities and lacked detectable Zea S 1 and Zea •+ ESA signals in vivo, which strongly suggests that the accumulation of Zea and active LHCX1 is essential for both EET and CT quenching in N. oceanica .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning

Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is salinity, which is important for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the impact and efficacy of using salinity information in state-of-the-art forecasting, we use a statistical model consisting of a variety of machine learning (ML) methods. For salinity data, we use satellite measurements of pre-storm sea surface salinity (SSS) as a proxy for the salinity stratification. We train and test the model on various ocean basins, including the Atlantic, eastern North Pacific and western North Pacific. A calibrator is trained on top of the ML models to correct and enhance probability forecasts. The calibrator significantly improves probability forecasts relative to recent works. The ML model performance is improved with the addition of SSS in the Eastern North Pacific, western North Pacific, and the Caribbean subregion of the North Atlantic, and the overall model performance is better than previous studies. SSS decreases model skill for a model trained on the full Atlantic basin. In the Indian Ocean, SSS is also notably correlated with RI occurrence, but the TC samples are not sufficient to train ML models.

hurricane↗
NASA NTRSDate not supplied

Updates in Developing a Prototype Science Pipeline and Full-Volume, Global Hyperspectral Synthetic Data Sets for NASA’s Earth System Observatory’s Upcoming Surface, Biology and Geology Mission

The Surface Biology and Geology (SBG) mission recently passed mission confirmation review and has entered phase A – design and development. SBG will acquire high resolution solar-reflected spectroscopy and thermal infrared observations at a data rate of ~2.5 TB/day and generate products at ~40 TB/day. Given that the per-day volume is greater than NASA’s total extant airborne hyperspectral data collection, collecting, processing, disseminating, and exploiting the SBG data present new challenges. To meet these challenges, we have developed a prototype science pipeline and a full-volume global hyperspectral synthetic data set to help prepare for SBG’s flight (see poster GC42D-0730). Our science pipeline is based on the science processing technology developed for NASA’s Kepler and TESS planet-hunting missions. The pipeline infrastructure, Ziggy, provides a scalable architecture for robust, repeatable, and replicable science and application products that can be run on a range of systems from a laptop to the cloud or a supercomputer. Ziggy is compliant with NASA Procedural Requirement (NPR) 7150.2C, is at a technical readiness level (TRL) of 7 and has been released to github.com/nasa/ziggy. We integrated Ziggy with EO-1/Hyperion workflows to build a prototype pipeline and ingested the 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. We fully implemented the first stage and processed the entire 55 TB Hyperion data set from the raw data (Level 0) to top-of-the-atmosphere radiance (Level 1R). We are currently evaluating the ISOFIT atmospheric correction module to convert the L1R data to surface reflectance (Level 2) before reprocessing the full data set to L2. Crosschecks are being performed with RadCalNet as well as with coincident observations by AVIRIS. We are also investigating modern methods for georectifying the Hyperion scenes. Finally, we describe an analysis of the cost to conduct forward processing and reprocessing campaigns for SBG on HECC with dedicated compute and storage resources using the resurrected Hyperion pipeline as a proxy for full-volume SBG data. The analysis demonstrates that SBG L0 data can be processed to L2 on HECC with full reprocessing campaigns every two years for ~$2.6M over a 7-year lifespan. Moreover, 69% of the system capacity would be available for other activities, possibly enabling future open-source science activities, including algorithm development, L3+ processing, .etc.

ESD↗
DOE OSTI2015

NO TIME FOR DEAD TIME: TIMING ANALYSIS OF BRIGHT BLACK HOLE BINARIES WITH NuSTAR

Timing of high-count-rate sources with the NuSTAR Small Explorer Mission requires specialized analysis techniques. NuSTAR was primarily designed for spectroscopic observations of sources with relatively low count rates rather than for timing analysis of bright objects. The instrumental dead time per event is relatively long (∼2.5 msec) and varies event-to-event by a few percent. The most obvious effect is a distortion of the white noise level in the power density spectrum (PDS) that cannot be easily modeled with standard techniques due to the variable nature of the dead time. In this paper, we show that it is possible to exploit the presence of two completely independent focal planes and use the cospectrum, the real part of the cross PDS, to obtain a good proxy of the white-noise-subtracted PDS. Thereafter, one can use a Monte Carlo approach to estimate the remaining effects of dead time, namely, a frequency-dependent modulation of the variance and a frequency-independent drop of the sensitivity to variability. In this way, most of the standard timing analysis can be performed, albeit with a sacrifice in signal-to-noise ratio relative to what would be achieved using more standard techniques. We apply this technique to NuSTAR observations of the black hole binaries GX 339–4, Cyg X-1, and GRS 1915+105.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Impact of Ducting on Heat Pump Water Heater Space Conditioning Energy Use and Comfort

Increasing penetration of heat pump water heaters (HPWHs) in the residential sector will offer an important opportunity for energy savings, with a theoretical energy savings of up to 63% per water heater and up to 11% of residential energy use (EIA 2009). However, significant barriers must be overcome before this technology will reach widespread adoption in the Pacific Northwest region and nationwide. One significant barrier noted by the Northwest Energy Efficiency Alliance (NEEA) is the possible interaction with the homes’ space conditioning system for units installed in conditioned spaces. Such complex interactions may decrease the magnitude of whole-house savings available from HPWH installed in the conditioned space in cold climates and could lead to comfort concerns (Larson et al. 2011; Kresta 2012). Modeling studies indicate that the installation location of HPWHs can significantly impact their performance and the resultant whole-house energy savings (Larson et al. 2012; Maguire et al. 2013). However, field data are not currently available to validate these results. This field evaluation of two GE GeoSpring HPWHs in the PNNL Lab Homes is designed to measure the performance and impact on the Lab Home HVAC system of a GE GeoSpring HPWH configured with exhaust ducting compared to an unducted GeoSpring HPWH during heating and cooling season periods; and measure the performance and impact on the Lab Home HVAC system of the GeoSpring HPWH with both supply and exhaust air ducting as compared to an unducted GeoSpring HPWH during heating and cooling season periods. Important metrics evaluated in these experiments include water heater energy use, HVAC energy use, whole house energy use, interior temperatures (as a proxy for thermal comfort), and cost impacts. This technical report presents results from the PNNL Lab Homes experiment.

energy efficiency↗
NASA NTRS2010

Dst Index in the 2008 GEM Modeling Challenge - Model Performance for Moderate and Strong Magnetic Storms

The GEM 2008 modeling challenge efforts are expanding beyond comparing in-situ measurements in the magnetosphere and ionosphere to include the computation of indices to be compared. The Dst index measures the largest deviations of the horizontal magnetic field at 4 equatorial magnetometers from the quiet-time background field and is commonly used to track the strength of the magnetic disturbance of the magnetosphere during storms. Models can calculate a proxy Dst index in various ways, including using the Dessler-Parker Sckopke relation and the energy of the ring current and Biot-Savart integration of electric currents in the magnetosphere. The GEM modeling challenge investigates 4 space weather events and we compare models available at CCMC against each other and the observed values of Ost. Models used include SWMF/BATSRUS, OpenGGCM, LFM, GUMICS (3D magnetosphere MHD models), Fok-RC, CRCM, RAM-SCB (kinetic drift models of the ring current), WINDMI (magnetosphere-ionosphere electric circuit model), and predictions based on an impulse response function (IRF) model and analytic coupling functions with inputs of solar wind data. In addition to the analysis of model-observation comparisons we look at the way Dst is computed in global magnetosphere models. The default value of Dst computed by the SWMF model is for Bz the Earth's center. In addition to this, we present results obtained at different locations on the Earth's surface. We choose equatorial locations at local noon, dusk (18:00 hours), midnight and dawn (6:00 hours). The different virtual observatory locations reveal the variation around the earth-centered Dst value resulting from the distribution of electric currents in the magnetosphere during different phases of a storm.

Rastaetter, Lutz↗
NASA NTRS2011

GLM Proxy Data Generation: Methods for Stroke/Pulse Level Inter-Comparison of Ground-Based Lightning Reference Networks

In order to produce useful proxy data for the GOES-R Geostationary Lightning Mapper (GLM) in regions not covered by VLF lightning mapping systems, we intend to employ data produced by ground-based (regional or global) VLF/LF lightning detection networks. Before using these data in GLM Risk Reduction tasks, it is necessary to have a quantitative understanding of the performance of these networks, in terms of CG flash/stroke DE, cloud flash/pulse DE, location accuracy, and CLD/CG classification error. This information is being obtained through inter-comparison with LMAs and well-quantified VLF/LF lightning networks. One of our approaches is to compare "bulk" counting statistics on the spatial scale of convective cells, in order to both quantify relative performance and observe variations in cell-based temporal trends provided by each network. In addition, we are using microsecond-level stroke/pulse time correlation to facilitate detailed inter-comparisons at a more-fundamental level. The current development status of our ground-based inter-comparison and evaluation tools will be presented, and performance metrics will be discussed through a comparison of Vaisala s Global Lightning Dataset (GLD360) with the NLDN at locations within and outside the U.S.

Cummins, Kenneth L.↗
NASA NTRS2010

Evaluation of Anomaly Detection Capability for Ground-Based Pre-Launch Shuttle Operations

This chapter will provide a thorough end-to-end description of the process for evaluation of three different data-driven algorithms for anomaly detection to select the best candidate for deployment as part of a suite of IVHM (Integrated Vehicle Health Management) technologies. These algorithms were deemed to be sufficiently mature enough to be considered viable candidates for deployment in support of the maiden launch of Ares I-X, the successor to the Space Shuttle for NASA's Constellation program. Data-driven algorithms are just one of three different types being deployed. The other two types of algorithms being deployed include a "nile-based" expert system, and a "model-based" system. Within these two categories, the deployable candidates have already been selected based upon qualitative factors such as flight heritage. For the rule-based system, SHINE (Spacecraft High-speed Inference Engine) has been selected for deployment, which is a component of BEAM (Beacon-based Exception Analysis for Multimissions), a patented technology developed at NASA's JPL (Jet Propulsion Laboratory) and serves to aid in the management and identification of operational modes. For the "model-based" system, a commercially available package developed by QSI (Qualtech Systems, Inc.), TEAMS (Testability Engineering and Maintenance System) has been selected for deployment to aid in diagnosis. In the context of this particular deployment, distinctions among the use of the terms "data-driven," "rule-based," and "model-based," can be found in. Although there are three different categories of algorithms that have been selected for deployment, our main focus in this chapter will be on the evaluation of three candidates for data-driven anomaly detection. These algorithms will be evaluated upon their capability for robustly detecting incipient faults or failures in the ground-based phase of pre-launch space shuttle operations, rather than based oil heritage as performed in previous studies. Robust detection will allow for the achievement of pre-specified minimum false alarm and/or missed detection rates in the selection of alert thresholds. All algorithms will also be optimized with respect to an aggregation of these same criteria. Our study relies upon the use of Shuttle data to act as was a proxy for and in preparation for application to Ares I-X data, which uses a very similar hardware platform for the subsystems that are being targeted (TVC - Thrust Vector Control subsystem for the SRB (Solid Rocket Booster)).

Martin, Rodney Alexander↗
DOE OSTI2025

Challenges in spatial metabolomics and proteomics for functional tissue unit and single-cell resolution

While transcriptomics is the most broadly applied technology for global spatial and single cell measurements in healthy and diseased tissues. Transcripts are often used as a proxy for protein and even metabolite measurements, but it has become commonly accepted that extrapolating this kind of information is a poor proxy and not a substitute for direct measurement. Within the last decade advanced developments of mass spectrometry-based assays have made these direct measurements not only possible, but routine. Where mass spectrometry has become an enabling technology, and various methods can now detect hundreds of metabolites and thousands of proteins from samples. Not only can this be performed within bulk measurements, but much effort has been directed into translating these measurements to single cells and tissues at cellular resolution. The information obtained from mass spectrometry is now able to trace metabolic events and decipher feedback loops across anatomical regions, connecting genetic and metabolic networks that define phenotypes. Herein, we will broadly overview developments in the field over the past decade, leading into several case studies which highlight the direct measurement of metabolites, proteins, and proteoforms from thinly sliced tissues. Much of this work is feasible due to multidisciplinary team science, and we offer brief perspective on paths forward and the challenges that persist with adoption and application of spatial omics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Method of Performance-Aware Security of Unicast Communication in Hybrid Satellite Networks

A method and apparatus utilizes Layered IPSEC (LES) protocol as an alternative to IPSEC for network-layer security including a modification to the Internet Key Exchange protocol. For application-level security of web browsing with acceptable end-to-end delay, the Dual-mode SSL protocol (DSSL) is used instead of SSL. The LES and DSSL protocols achieve desired end-to-end communication security while allowing the TCP and HTTP proxy servers to function correctly.

Roy-Chowdhury, Ayan↗
DOE OSTI2024

Measuring Thread Timing to Assess the Feasibility of Early-Bird Message Delivery Across Systems and Scales

Early-bird communication is a communication/computation overlap technique that leverages fine-grained communication to improve application run-time. Communication is divided such that each individual thread can initiate transmission of its portion of the data upon completion rather than waiting for a dedicated communication phase. The benefit of early-bird communication depends on the completion timing of the individual threads: On the one hand, if all threads are complete at nearly the same time, the overheads of sending multiple messages will accumulate, leading to performance that is worse than if a single message had been sent. On the other hand, if thread completions are spread out in time, those that complete earlier can send data while others continue working, leading to performance that is better than if a single message had been sent. The challenge is that the completion times are currently unknown and can vary based on application, problem size, system software, and underlying hardware. In this paper, we address this lacuna by measuring and evaluating the potential overlap afforded by early-bird communication for a selection of proxy applications. These measurements help us understand whether a given application could benefit from early-bird communication. Here, we present our technique for gathering this data and evaluate data collected from three proxy applications: MiniFE, MiniMD, and MiniQMC. Each application is run on three systems with distinct CPU architectures and strong scales across three run sizes. To characterize the behavior of these workloads, we study the trends of thread timings at both a macro level, across all threads across all runs of an application, and a micro level, that is, within a single process of a single run. We observe that our tested applications exhibit significantly different thread arrival distributions. The machine used had a significant impact, with the window of potential overlap varying by as much as an order of magnitude.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Proxy-Based Bayesian Inversion Of Poroelastic Simulations To Interpret Strain Tensor Data Measured During Well Testing

The long runtimes of 3D poroelastic numerical simulators makes it impractical to interpret deformation datasets using many inversion schemes. Recent advances in instrumentation have made it possible to measure the strain tensor during well testing, but the lack of robust inversion methods is limiting the ability to interpret these data. We have developed an inversion workflow that reduces the number of computations required to complete a Bayesian inversion using DREAMzs. The workflow trains a KNN model using output from the poroelastic simulator, and then uses the KNN model as a proxy for the simulator during inversion. The workflow also includes a strategy for ensuring the results from the proxy model converge to the results from the simulator, ensuring the accuracy of the final results. An idealized example configured to represent a well test in a deep aquifer is used to verify that the workflow correctly identifies parameters and characterizes noise. Field data measured using strainmeters during an injection test at an oil reservoir in Oklahoma are used to evaluate performance with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), and the results are used to characterize posterior parameter distribution and evaluate the prediction uncertainty. This approach makes it feasible to invert strain data measured during well testing and this has the potential to improve the characterization of aquifers and reservoirs.

Roudini, Soheil↗
DOE OSTI2015

Intermittent Renewable Management Pilot Phase 2

The Intermittent Renewable Management Pilot - Phase 2 (IRM2) was designed to study the feasibility of demand-side resources to participate into the California Independent System Operator (CAISO) wholesale market as proxy demand resources (PDR). The pilot study focused on understanding the issues related with direct participation of third-parties and customers including customer acceptance; market transformation challenges (wholesale market, technology); technical and operational feasibility; and value to the rate payers, DR resource owners and the utility on providing an enabling mechanism for DR resources into the wholesale markets. The customer had the option of committing to either three contiguous hour blocks for 24 days or six contiguous hours for 12 days a month with day-ahead notification that aligned with the CAISO integrated forward market. As a result of their being available, the customer was paid $10/ kilowatt (kW)-month for capacity in addition to CAISO energy settlements. The participants were limited to no more than a 2 megawatt (MW) capacity with a six-month commitment. Four participants successfully engaged in the pilot. In this report, we provide the description of the pilot, participant performance results, costs and value to participants as well as outline some of the issues encountered through the pilot. Results show that participants chose to participate with storage and the value of CAISO settlements were significantly lower than the capacity payments provided by the utility as incentive payments. In addition, this pilot revealed issues both on the participant side and system operations side. These issues are summarized in the report.The Intermittent Renewable Management Pilot - Phase 2 (IRM2) was designed to study the feasibility of demand-side resources to participate into the California Independent System Operator (CAISO) wholesale market as proxy demand resources (PDR). The pilot study focused on understanding the issues related with direct participation of third-parties and customers including customer acceptance; market transformation challenges (wholesale market, technology); technical and operational feasibility; and value to the rate payers, DR resource owners and the utility on providing an enabling mechanism for DR resources into the wholesale markets.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Managing well leakage risks at a geologic carbon storage site with many wells

Potential geologic carbon storage (GCS) sites with a history of oil and gas production have well-characterized injectivity and storage capacity, but the presence of legacy wells increases leakage risk. Thus, the success of GCS operations at sites with many wells will require a thorough leakage risk assessment and a robust strategy for managing well leakage risk over the lifetime of the project. In this study, we demonstrate a workflow that uses the National Risk Assessment Partnership’s open-source Integrated Assessment Model to quantify well leakage risks and test the performance of various leakage risk management strategies at a heavily drilled GCS site. Here, our model simulates a 50-year basin-scale injection of CO 2 at a hypothetical site based on the Kimberlina Project Site in the Southern San Joaquin Valley of California. Brine and CO 2 leakage through 1,000 legacy wells into a USDW are stochastically simulated as a proxy for risk. We consider multiple scenarios that explore the efficacy of various well leakage risk management strategies with changes in well leakage behavior, reservoir behavior, and post-injection site care (PISC) length. Predicted leakage at the site after 100 years was small with a maximum CO 2 leakage of 102.1 tonnes (4.08×10 -5 % of the 250 Mt injected) and a maximum brine leakage of 2.4 tonnes. Leakage risk management strategies based on accurate prior information about well leak probability reduced leakage risks more effectively at the modeled site and were more robust with respect to reservoir uncertainty than strategies based on the distance of the legacy well from the injector. The importance of the PISC period length was not clear as it had a negligible impact on CO 2 leakage risk but a sizable impact on brine leakage risk in our model.

58 GEOSCIENCES↗
DOE OSTI2016

AGNfitter: a Bayesian MCMC approach to fitting spectral energy distributions of AGNs

We present AGNfitter, a publicly available open-source algorithm implementing a fully Bayesian Markov Chain Monte Carlo method to fit the spectral energy distributions (SEDs) of active galactic nuclei (AGNs) from the sub-millimeter to the UV, allowing one to robustly disentangle the physical processes responsible for their emission. AGNfitter makes use of a large library of theoretical, empirical, and semi-empirical models to characterize both the nuclear and host galaxy emission simultaneously. The model consists of four physical emission components: an accretion disk, a torus of AGN heated dust, stellar populations, and cold dust in star-forming regions. AGNfitter determines the posterior distributions of numerous parameters that govern the physics of AGNs with a fully Bayesian treatment of errors and parameter degeneracies, allowing one to infer integrated luminosities, dust attenuation parameters, stellar masses, and star-formation rates. We tested AGNfitter’s performance on real data by fitting the SEDs of a sample of 714 X-ray selected AGNs from the XMM-COSMOS survey, spectroscopically classified as Type1 (unobscured) and Type2 (obscured) AGNs by their optical–UV emission lines. We find that two independent model parameters, namely the reddening of the accretion disk and the column density of the dusty torus, are good proxies for AGN obscuration, allowing us to develop a strategy for classifying AGNs as Type1 or Type2, based solely on an SED-fitting analysis. Our classification scheme is in excellent agreement with the spectroscopic classification, giving a completeness fraction of ∼86% and ∼70%, and an efficiency of ∼80% and ∼77%, for Type1 and Type2 AGNs, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗