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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Comparison of a Traditional Probabilistic Risk Assessment Approach with Advanced Safety Analysis

As part of the Light Water Sustainability Program (LWRS) [1], the purpose of the Risk Informed Safety Margin Characterization (RISMC) [2] Pathway research and development (R&D) is to support plant decisions for risk-informed margin management with the aim to improve economics, reliability, and sustain safety of current NPPs. In this paper, we describe the RISMC analysis process illustrating how mechanistic and probabilistic approaches are combined in order to estimate a safety margin. We use the scenario of a “station blackout” (SBO) wherein offsite power and onsite power is lost, thereby causing a challenge to plant safety systems. We describe the RISMC approach, illustrate the station blackout modeling, and contrast this with traditional risk analysis modeling for this type of accident scenario. We also describe our approach we are using to represent advanced flooding analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Long-term measurements of submicrometer aerosol chemistry at the Southern Great Plains (SGP) using an Aerosol Chemical Speciation Monitor (ACSM)

In this study the long-term trends of non-refractory submicrometer aerosol (NR-PM1) composition and mass concentration measured by an Aerosol Chemical Speciation Monitor (ACSM) at the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site are discussed. NR-PM1 data was recorded at ~30 min intervals over a period of 19 months between November 2010 and June 2012. Positive Matrix Factorization (PMF) was performed on the measured organic mass spectral matrix using a rolling window technique to derive factors associated with distinct sources, evolution processes, and physiochemical properties. The rolling window approach also allows us to capture the dynamic variations of the chemical properties in the organic aerosol (OA) factors over time. Three OA factors were obtained including two oxygenated OA (OOA) factors, differing in degrees of oxidation, and a biomass burning OA (BBOA) factor. Back trajectory analyses were performed to investigate possible sources of major NR-PM1 species at the SGP site. Organics dominated NR-PM1 mass concentration for the majority of the study with the exception of winter, when ammonium nitrate increases due to transport of precursor species from surrounding urban and agricultural areas and also due to cooler temperatures. Sulfate mass concentrations have little seasonal variation with mixed regional and local sources. In the spring BBOA emissions increase and are mainly associated with local fires. Isoprene and carbon monoxide emission rates were obtained by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the 2011 U.S. National Emissions Inventory to represent the spatial distribution of biogenic and anthropogenic sources, respectively. The combined spatial distribution of isoprene emissions and air mass trajectories suggest that biogenic emissions from the southeast contribute to SOA formation at the SGP site during the summer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Vibration-Based Techniques for Concrete Structural Health Monitoring. Light Water Reactor Sustainability Program report

The objectives of this ongoing research project focus on health monitoring and data analytics of concrete slabs containing reactive aggregates and thus subjected to degradation due to alkali-silica reaction (ASR). A controlled concrete slab with four pockets of reactive aggregates (pure silica, and reactive aggregates from three different quarries) was cast at Vanderbilt University and cured in representative conditions to accelerate degradation due to ASR. A set of four concrete samples were also cast and cured at the University of Alabama for ASR testing. Of these four samples, two slabs contained reactive aggregates while the other two had the non-reactive aggregate counterparts mixed throughout the samples. Four additional slabs were cast and cured at the University of Nebraska- Lincoln. Of these four samples; one contained non-reactive aggregates and no reinforcement, one contained reactive aggregates and no reinforcement, one contained reactive aggregates and rebar reinforcement in one direction, and the last contained reactive aggregates and reinforcement in two directions. Single frequency and dual frequency tests were used on these slabs to locate ASR damage within the specimens containing reactive aggregates. The vibration tests were conducted with different sensor and actuator configurations to facilitate damage detection and localization. The results from the data analysis of the dynamic testing on concrete slabs are discussed in detail in this report. Results for damage localization are dependent on multiple parameters used in the tests. This report investigates different methods of data fusion including voting, raw averaging, damage index averaging, and Bayesian fusion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Efficient Topology Design Algorithms for Power Grid Stability

The dynamic response of power grids to small disturbances influences their overall stability. This letter examines the effect of network topology on the linearized time-invariant dynamics of electric power systems. The proposed framework utilizes H 2 -norm based stability metrics to study the optimal placement of lines on existing networks as well as the topology design of new networks. The design task is first posed as an NP-hard mixed-integer nonlinear program (MINLP) that is exactly reformulated as a mixed-integer linear program (MILP) using McCormick linearization. To improve computation time, graph-theoretic properties are exploited to derive valid inequalities (cuts) and tighten bounds on the continuous optimization variables. Moreover, a cutting plane generation procedure is put forth that is able to interject the MILP solver and augment additional constraints to the problem on-the-fly. Finally, the efficacy of our approach in designing optimal grid topologies is demonstrated through numerical tests on the IEEE 39-bus network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Dependence of the rate of LiF ion pairing on the description of molecular interaction

We present an analysis of the dynamics of ion-pairing of Lithium Fluoride (LiF) in aqueous solvent using both detailed molecular simulation as well as reduced models within a Gener- alized Langevin Equation (GLE) framework. We explored the sensitivity of the ion-pairing phenomena to the details of descriptions of molecular interaction, comparing two empirical potentials to explicit quantum based density functional theory. We find quantitative differences in the potentials of mean force for ion-pairing as well as time dependent frictions that lead to variations in the rate constant and reactive flux correlation functions. These details reflect differences in solvent response to ion-pairing between different representations of molecular interaction and influence anharmonicity of the dynamic response. We find that the short time anharmonic response is recovered with a GLE parameterization. Recovery of the details of long time response may require extensions to the reduced model. We show that the utility of using a reduced model leads to a straight forward application of variational transition state the- ory concepts to the condensed phase system. The significance of this is reflected in the analysis of committor distributions and the variation of planar hypersurfaces, leading to an improved understanding of factors that determine the rate of LiF ion-pairing. CJM and GKS are supported by the U.S. Department of Energy‘s (DOE) Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest Na- tional Laboratory (PNNL) is operated for the Department of Energy by Battelle. MDB is grateful for the support of Laboratory Directed Research and Development funding under the auspices of PNNL’s Laboratory Initiative Materials Synthesis and Simulation across Scales (MS3). Additional computing resources were generously allocated by PNNL’s Institutional Computing program. EP acknowledges support from PNNL’s Alternate Sponsored Fellowship program and IMPRS Dres- den.Support to P.J. from the Czech Science Foundation (grant P208/12/G016) and the Academy of Sciences (Praemium Academie award) is gratefully acknowledged.

Pluharova, Eva↗
DOE OSTI2015

Analysis of Strand-Specific RNA-Seq Data Using Machine Learning Reveals the Structures of Transcription Units in Clostridium thermocellum

The identification of transcription units (TUs) encoded in a bacterial genome is essential to elucidation of transcriptional regulation of the organism. To gain a detailed understanding of the dynamically composed TU structures, we have used four strand-specific RNA-seq (ssRNA-seq) datasets collected under two experimental conditions to derive the genomic TU organization of Clostridium thermocellum using a machine-learning approach. Our method accurately predicted the genomic boundaries of individual TUs based on two sets of parameters measuring the RNA-seq expression patterns across the genome: expression-level continuity and variance. A total of 2590 distinct TUs are predicted based on the four RNA-seq datasets. Moreover, among the predicted TUs, 44% have multiple genes. We assessed our prediction method on an independent set of RNA-seq data with longer reads. The evaluation confirmed the high quality of the predicted TUs. Functional enrichment analyses on a selected subset of the predicted TUs revealed interesting biology. To demonstrate the generality of the prediction method, we have also applied the method to RNA-seq data collected on Escherichia coli and achieved high prediction accuracies. The TU prediction program named SeqTU is publicly available athttps://code.google.com/p/seqtu/. We expect that the predicted TUs can serve as the baseline information for studying transcriptional and post-transcriptional regulation in C. thermocellum and other bacteria.

09 BIOMASS FUELS↗
DOE OSTI2024

Coassembly and binning of a twenty-year metagenomic time-series from Lake Mendota

Abstract The North Temperate Lakes Long-Term Ecological Research (NTL-LTER) program has been extensively used to improve understanding of how aquatic ecosystems respond to environmental stressors, climate fluctuations, and human activities. Here, we report on the metagenomes of samples collected between 2000 and 2019 from Lake Mendota, a freshwater eutrophic lake within the NTL-LTER site. We utilized the distributed metagenome assembler MetaHipMer to coassemble over 10 terabases (Tbp) of data from 471 individual Illumina-sequenced metagenomes. A total of 95,523,664 contigs were assembled and binned to generate 1,894 non-redundant metagenome-assembled genomes (MAGs) with ≥50% completeness and ≤10% contamination. Phylogenomic analysis revealed that the MAGs were nearly exclusively bacterial, dominated by Pseudomonadota (Proteobacteria, N = 623) and Bacteroidota (N = 321). Nine eukaryotic MAGs were identified by eukCC with six assigned to the phylum Chlorophyta. Additionally, 6,350 high-quality viral sequences were identified by geNomad with the majority classified in the phylum Uroviricota. This expansive coassembled metagenomic dataset provides an unprecedented foundation to advance understanding of microbial communities in freshwater ecosystems and explore temporal ecosystem dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A large-scale analysis of bioinformatics code on GitHub

In recent years, the explosion of genomic data and bioinformatic tools has been accompanied by a growing conversation around reproducibility of results and usability of software. However, the actual state of the body of bioinformatics software remains largely unknown. Here, the purpose of this paper is to investigate the state of source code in the bioinformatics community, specifically looking at relationships between code properties, development activity, developer communities, and software impact. To investigate these issues, we curated a list of 1,720 bioinformatics repositories on GitHub through their mention in peer-reviewed bioinformatics articles. Additionally, we included 23 high-profile repositories identified by their popularity in an online bioinformatics forum. We analyzed repository metadata, source code, development activity, and team dynamics using data made available publicly through the GitHub API, as well as article metadata. We found key relationships within our dataset, including: certain scientific topics are associated with more active code development and higher community interest in the repository; most of the code in the main dataset is written in dynamically typed languages, while most of the code in the high-profile set is statically typed; developer team size is associated with community engagement and high-profile repositories have larger teams; the proportion of female contributors decreases for high-profile repositories and with seniority level in author lists; and, multiple measures of project impact are associated with the simple variable of whether the code was modified at all after paper publication. In addition to providing the first large-scale analysis of bioinformatics code to our knowledge, our work will enable future analysis through publicly available data, code, and methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Long‐Term Large‐Scale Atmospheric Forcing Data From Three‐Dimensional Constrained Variational Analysis for the ARM SGP Site

Here, this study presents a long‐term three‐dimensional large‐scale forcing data set (VARANAL3D) derived from the three‐dimensional constrained variational analysis (3DCVA) method at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site from 2004 to 2018. Building on the same input data sets as the conventional continuous forcing data set (VARANAL), VARANAL3D maintains overall consistency in domain‐averaged fields while introducing spatial variability, offering critical insights into the influence of mesoscale synoptic systems on cloud‐related processes. Evaluations are conducted across four cloud and precipitation regimes: Clear‐sky, Shallow‐clouds, Afternoon‐precipitation, and Nocturnal‐precipitation, presenting high consistency of the domain‐mean forcing data sets while emphasizing the role of subdomain forcing variability particularly in precipitating regimes. Single column model (SCM) simulations demonstrate that subdomain VARANAL3D forcing improves cloud and precipitation representation, with the ensemble outperforming domain‐mean forcing in three cloudy and precipitating regimes. Overall, these results highlight VARANAL3D's value for investigating the impacts of spatial variability of large‐scale forcing on atmospheric processes. The VARANAL3D data set provides new opportunities for evaluating model physics, advancing the development of scale‐aware parameterizations and deepening our understanding of cloud and precipitation dynamics.

Environmental sciences↗
DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. The effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗
DOE OSTI2015

Mitigation of Syngas Cooler Plugging and Fouling

This Final Report summarizes research performed to develop a technology to mitigate the plugging and fouling that occurs in the syngas cooler used in many Integrated Gasification Combined Cycle (IGCC) plants. The syngas cooler is a firetube heat exchanger located downstream of the gasifier. It offers high thermal efficiency, but its’ reliability has generally been lower than other process equipment in the gasification island. The buildup of ash deposits that form on the fireside surfaces in the syngas cooler (i.e., fouling) lead to reduced equipment life and increased maintenance costs. Our approach to address this problem is that fouling of the syngas cooler cannot be eliminated, but it can be better managed. The research program was funded by DOE using two budget periods: Budget Period 1 (BP1) and Budget Period 2 (BP2). The project used a combination of laboratory scale experiments, analysis of syngas cooler deposits, modeling and guidance from industry to develop a better understanding of fouling mechanisms and to develop and evaluate strategies to mitigate syngas cooler fouling and thereby improve syngas cooler performance. The work effort in BP 1 and BP 2 focused on developing a better understanding of the mechanisms that lead to syngas cooler plugging and fouling and investigating promising concepts to mitigate syngas cooler plugging and fouling. The work effort focused on the following: • analysis of syngas cooler deposits and fuels provided by an IGCC plant collaborating with this project; • performing Jet cleaning tests in the University of Utah Laminar Entrained Flow Reactor to determine the bond strength between an ash deposit to a metal plate, as well as implementing planned equipment modifications to the University of Utah Laminar Entrained Flow Reactor and the one ton per day, pressurized Pilot Scale Gasifier; • performing Computational Fluid Dynamic modeling of industrially relevant syngas cooler configurations to develop a better understanding of deposit formation mechanisms; • performing Techno-Economic-Analysis for a representative IGCC plant to investigate the impact on plant economics, in particular the impacts on the Cost of Electricity (COE), due to plant shutdowns caused by syngas cooler plugging and fouling and potential benefits to plant economics of developing strategies to mitigate syngas cooler fouling; and • performing modeling and pilot scale tests to investigate the potential benefits of using a sorbent (fuel additive) to capture the vaporized metals that result in syngas cooler fouling. All project milestones for BP 1 and BP 2 were achieved. DOE was provided a briefing on our accomplishments in BP1 and BP2 and our proposed plans for Budget Period 3 (BP 3). Based on our research the mitigation technology selected to investigate in BP 3 was the use of a sorbent that can be injected into the gasifier with the fuel slurry to capture vaporized metals that lead to the deposit formation in the syngas cooler. The work effort proposed for BP 3 would have focused on addressing concerns raised by gasification industry personnel for the impacts on gasifier performance of sorbent injection, so that at the end of BP 3 the use of sorbent injection would be at “pre-commercial” stage and ready for use in a Field Demonstration that could be funded by industry or DOE. A Budget Continuation Application (BCA) was submitted to obtain funding for BP3 DOE but DOE chose to not fund the proposed BP3 effort.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. Here, the effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗
DOE OSTI2014

SU-E-T-163: Evaluation of Dose Distributions Recalculated with Per-Field Measurement Data Under the Condition of Respiratory Motion During IMRT for Liver Cancer

Purpose: The dose distributions within the real volumes of tumor targets and critical organs during internal target volume-based intensity-modulated radiation therapy (ITV-IMRT) for liver cancer were recalculated by applying the effects of actual respiratory organ motion, and the dosimetric features were analyzed through comparison with gating IMRT (Gate-IMRT) plan results. Methods: The 4DCT data for 10 patients who had been treated with Gate-IMRT for liver cancer were selected to create ITV-IMRT plans. The ITV was created using MIM software, and a moving phantom was used to simulate respiratory motion. The period and range of respiratory motion were recorded in all patients from 4DCT-generated movie data, and the same period and range were applied when operating the dynamic phantom to realize coincident respiratory conditions in each patient. The doses were recalculated with a 3 dose-volume histogram (3DVH) program based on the per-field data measured with a MapCHECK2 2-dimensional diode detector array and compared with the DVHs calculated for the Gate-IMRT plan. Results: Although a sufficient prescription dose covered the PTV during ITV-IMRT delivery, the dose homogeneity in the PTV was inferior to that with the Gate-IMRT plan. We confirmed that there were higher doses to the organs-at-risk (OARs) with ITV-IMRT, as expected when using an enlarged field, but the increased dose to the spinal cord was not significant and the increased doses to the liver and kidney could be considered as minor when the reinforced constraints were applied during IMRT plan optimization. Conclusion: Because Gate-IMRT cannot always be considered an ideal method with which to correct the respiratory motional effect, given the dosimetric variations in the gating system application and the increased treatment time, a prior analysis for optimal IMRT method selection should be performed while considering the patient's respiratory condition and IMRT plan results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Overview of the Biomass Scenario Model

Biofuels are promoted in the United States through legislation, as one part of an overall strategy to lessen dependence on imported energy as well as to reduce the emissions of greenhouse gases (Office of the Biomass Program and Energy Efficiency and Renewable Energy, 2008). For example, the Energy Independence and Security Act of 2007 (EISA) mandates 36 billion gallons of renewable liquid transportation fuel in the U.S. marketplace by the year 2022 (U.S. Government, 2007). Meeting the volumetric targets has prompted an unprecedented increase in funding for biofuels research, much of it focused on producing ethanol and other fuel types from cellulosic feedstocks as well as additional biomass sources (such as oil seeds and algae feedstock). In order to help propel the biofuels industry, the U.S. government has enacted a variety of incentive programs (including subsidies, fixed capital investment grants, loan guarantees, vehicle choice credits, and corporate average fuel economy standards) -- the short-and long-term ramifications of which are not well understood. Efforts to better understand the impacts of incentive strategies can help policy makers to develop a policy suite which will foster industry development while reducing the financial risk associated with government support of the nascent biofuels industry.

09 BIOMASS FUELS↗
DOE OSTI2017

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM development aims for advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability for reactor transient analyses. To facilitate the code development, SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SAM focuses on modeling advanced reactor concepts such as SFRs (sodium fast reactors), LFRs (lead-cooled fast reactors), and FHRs (fluoride-salt-cooled high temperature reactors) or MSRs (molten salt reactors). These advanced concepts are distinguished from light-water reactors in their use of single-phase, low-pressure, high-temperature, and low Prandtl number (sodium and lead) coolants. As a new code development, the initial effort has been focused on modeling and simulation capabilities of heat transfer and single-phase fluid dynamics responses in Sodium-cooled Fast Reactor (SFR) systems. The system-level simulation capabilities of fluid flow and heat transfer in general engineering systems and typical SFRs have been verified and validated. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As the code is still under ongoing development, this SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

TEAMER: MADWEC Techno-Economic Analysis

The objective of this project was for the facility to conduct a techno-economic assessment (TEA) of the Maximal Asymmetric Drag Wave Energy Converter (MADWEC), developed by the University of Massachusetts Dartmouth (UMass Dartmouth). MADWEC is used for powering remote monitoring and Autonomous Underwater Vehicle (AUV) charging systems compared to other existing power supply options. The assessment estimates capital expenditures (CapEx), operational expenditures (OpEx), and power performance for 18 scenarios with the purpose of identifying key cost drivers, comparing total system cost, and comparing the power performance of the power supply options in terms of required installed capacity and estimated theoretical annual energy performance. The 18 assessed scenarios include two end-uses: 1) AUV charging and 2) offshore remote monitoring); three power sources: 1) MADWEC), 2) photovoltaic (PV) solar buoy, 3) and traditional battery swapping); and three locations; 1) nearshore, 2) far-offshore, and 3) high-latitude). In addition, other project goals included developing high level installation, operation, and maintenance plans for each scenario. The techno-economic model, created in Microsoft Excel, estimates CapEx, OpEx, and the power performance of each power supply source. The model has a dynamic format that allows custom inputs to accommodate future changes to the systems being assessed. This is a TEA for the MADWEC project, TEAMER RFTS 7 (request for technical support) program.

16 TIDAL AND WAVE POWER↗
DOE OSTI2015

The Sloan Digital Sky Survey Reverberation Mapping Project: No evidence for evolution in the M{sub ∙}−σ{sub ∗} RELATION TO z∼1

We present host stellar velocity dispersion measurements for a sample of 88 broad-line quasars at 0.1 0.6) from the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project. High signal-to-noise ratio coadded spectra (average S/N≈30 per 69 km s{sup −1} pixel) from SDSS-RM allowed for the decomposition of the host and quasar spectra and for measurements of the host stellar velocity dispersions and black hole (BH) masses using the single-epoch (SE) virial method. The large sample size and dynamic range in luminosity (L{sub 5100}=10{sup 43.2−44.7} erg s{sup −1}) lead to the first clear detection of a correlation between SE virial BH mass and host stellar velocity dispersion far beyond the local universe. However, the observed correlation is significantly flatter than the local relation, suggesting that there are selection biases in high-z luminosity-threshold quasar samples for such studies. Our uniform sample and analysis enable an investigation of the redshift evolution of the M{sub ∙}−σ{sub ∗} relation relatively free of caveats by comparing different samples/analyses at disjoint redshifts. We do not observe evolution of the M{sub ∙}−σ{sub ∗} relation in our sample up to z∼1, but there is an indication that the relation flattens toward higher redshifts. Coupled with the increasing threshold luminosity with redshift in our sample, this again suggests that certain selection biases are at work, and simple simulations demonstrate that a constant M{sub ∙}−σ{sub ∗} relation is favored to z∼1. Our results highlight the scientific potential of deep coadded spectroscopy from quasar monitoring programs, and offer a new path to probe the co-evolution of BHs and galaxies at earlier times.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The Potential Role of Concentrating Solar Power within the Context of DOE's 2030 Solar Cost Targets

For solar electricity generating technologies to be cost competitive at a large scale with conventionally generated electricity, cost reductions are needed for both concentrating solar power (CSP) and solar photovoltaic (PV) systems. In 2011, the U.S. Department of Energy (DOE) established solar cost targets that corresponded to reducing CSP and PV prices by approximately 75% in order to achieve a levelized cost of electricity (LCOE) of $0.06 per kilowatt-hour (kWh) for both utility-scale PV and high-capacity factor CSP-TES systems in 2020. Utility-scale PV achieved its 2020 cost target in 2017, and recent estimates for the LCOE of CSP-TES with a molten-salt power tower system are approximately $0.10/kWh for projects that are expected to come online in 2020, which represents a substantial reduction since 2010 - when the LCOE for CSP-TES was around $0.21/kWh. To continue the momentum for cost reductions in solar technologies, DOE recently established cost targets for 2030 that would make solar one of the lowest-cost sources of new electricity in the United States. For CSP-based systems, the new targets correspond to an LCOE in 2030 of $0.05/kWh for a dispatchable, high-capacity factor CSP-TES plant configuration. This aggressive target would have been unimaginable a decade ago. However, building on the previously described reduction in CSP-TES costs over the past decade, recent announcements suggest the next phase of projects will continue this downward trend through lower installation costs, attractive financing, longer-duration PPAs, and the ability to capitalize on the value that the flexibility of storage brings CSP. This presentation summarizes a recent report that evaluates the potential impacts of simultaneously achieving the 2030 cost targets for PV and CSP-TES, and it includes a detailed evaluation of the role that CSP-TES could play in realizing those impacts. The scenarios in this analysis are designed to isolate and assess the potential impacts of achieving DOE's 2030 cost targets for CSP-TES and PV, and they do not reflect the potential benefits or system impacts associated with success in other DOE research programs. The low-cost solar scenarios include DOE's 2030 solar cost targets--which are represented via a roughly 50% reduction in LCOE by 2030 (from current levels) with additional cost reductions thereafter representing technology learning and/or improvements that could result from innovation - coupled with a variety of market, technology, and demand assumptions. With these assumptions, the evolution of the contiguous U.S. electricity system is evaluated with NREL's Renewable Energy Deployment System (ReEDS) model, which was specifically designed to represent the temporal and locational value of renewable generation technologies in the U.S. power system. ReEDS relies on system-wide least-cost optimization to estimate the type and location of future generation and transmission capacity. In addition, it accounts for the locational and temporal variations in variable renewable technologies, including the need for new transmission, curtailment, dynamic capacity value, and the need to hold operating reserves to account for the uncertainty and variability of these technologies. This presentation summarizes the key findings that arise from a detailed evaluation of the impacts of achieving DOE's 2030 cost targets for CSP-TES and PV systems, noting again the inherent challenges associated with modeling future scenarios of the large, complex system electricity system in the contiguous United States within the context of various market features.

14 SOLAR ENERGY↗