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At least 793 records · Page 44

Aerosciences Implications for Uranus Aerocapture

Exploration of Uranus has been indicated as the highest priority new flagship planetary science missions for NASA in the 2022 Decadal Survey. Due to Uranus’ location as the second furthest planet from the Sun, interplanetary flight times of a traditional propulsive-capture orbiter can expect to take 13-15 years to reach Uranus while requiring up to two-thirds of the launch mass budget to be allocated to propellant alone. Aerocapture presents an alternative means to capture orbit around Uranus by using aerodynamic forces generated from flight through the planetary atmosphere to decelerate to orbital insertion while reducing time in interplanetary transit time and increasing on-orbit payload mass. To date, only one spacecraft (Voyager 2) has visited Uranus, and there have been no missions which have entered its atmosphere. While knowledge of planetary entry at rocky terrestrial planets with Air (N2/O2) and CO2 dominated atmospheres has greatly advanced over the past decades with a variety of missions to learn from, the H2/He composition and much larger atmosphere of ice giants such as Uranus poses new aerosciences implications which are not fully understood. These implications must be better understood not only for aerocapture, but for planetary entry at Uranus as a whole (such as a Uranus probe, as proposed by the 2022 Decadal Survey), as well as other ice giants like Neptune. To conduct a proper analysis of aerocapture methods, aerodynamic and aerothermal analysis of flight trajectories in Uranus atmosphere are required. Previous work has investigated aerocapture at Neptune (with similar atmosphere to Uranus) using a Mid-L/D configuration. Additional previous work considers the convective heating experienced in H2/He atmospheres. The current work looks to use heritage Low-L/D configurations, adding technical depth and maturation to analysis previously performed by Girija. Atmospheric flight at ice giants presents unique challenges, including but not limited to: fidelity of atmospheric models, large entry velocities due to location in the solar system, extended flight in rarefied flow conditions due to atmospheric scale, and unusual aerodynamic flow properties specific to Uranus and Ice Giant atmospheres.

Eli Shellabarger↗

One in a Million Given the Accident: Assuring Nuclear Weapon Safety

Since the introduction of nuclear weapons, there has not been a single instance of accidental or unauthorized nuclear detonation, but there have been numerous accidents and “close calls.” As the understanding of these environments has increased, the need for a robust nuclear weapon safety philosophy has grown. This paper describes some of the methods used by the Nuclear Weapon Complex today to assure nuclear weapon safety, including testing, modeling, analysis, and design features. Lastly, it also reviews safety’s continued role in the future and examines how nuclear safety’s present maturity can play a role in strengthening security and other areas and how increased coordination can improve safety and reduce long-term cost.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Process-Based Cost Estimation for Ramjet/Scramjet Engines

Process-based cost estimation plays a key role in effecting cultural change that integrates distributed science, technology and engineering teams to rapidly create innovative and affordable products. Working together, NASA Glenn Research Center and Boeing Canoga Park have developed a methodology of process-based cost estimation bridging the methodologies of high-level parametric models and detailed bottoms-up estimation. The NASA GRC/Boeing CP process-based cost model provides a probabilistic structure of layered cost drivers. High-level inputs characterize mission requirements, system performance, and relevant economic factors. Design alternatives are extracted from a standard, product-specific work breakdown structure to pre-load lower-level cost driver inputs and generate the cost-risk analysis. As product design progresses and matures the lower level more detailed cost drivers can be re-accessed and the projected variation of input values narrowed, thereby generating a progressively more accurate estimate of cost-risk. Incorporated into the process-based cost model are techniques for decision analysis, specifically, the analytic hierarchy process (AHP) and functional utility analysis. Design alternatives may then be evaluated not just on cost-risk, but also user defined performance and schedule criteria. This implementation of full-trade study support contributes significantly to the realization of the integrated development environment. The process-based cost estimation model generates development and manufacturing cost estimates. The development team plans to expand the manufacturing process base from approximately 80 manufacturing processes to over 250 processes. Operation and support cost modeling is also envisioned. Process-based estimation considers the materials, resources, and processes in establishing cost-risk and rather depending on weight as an input, actually estimates weight along with cost and schedule.

Singh, Brijendra↗

High-Fidelity Modeling and Experiments to Inform Safety Analysis Codes for Heat Pipe Microreactors

Heat pipe microreactors are reactor designs that primarily use liquid-metal heat pipes to cool the core. The main interest in heat pipes is the fact that they can remove heat passively. This, along with the use of liquid metal, allows the reactor to operate at higher temperatures. Although the use of heat pipes in nuclear reactors is new, liquid-metal heat pipe technology is mature. Nevertheless, experimental data on heat pipes are scarce, and very little is known about their behavior during abnormal operations and close to their thermal limits. Therefore, new experiments and accurate heat pipe simulations are needed to develop reliable closure models. This work describes a joint experimental and numerical investigation into heat pipes that attempts an initial closure of this gap. Further, the numerical and experimental efforts are currently proceeding in parallel, aimed at different aspects of heat pipes. The numerical part is focused on gaps in local closures, and the experiments capture the overall heat pipe behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Dynamic Household Vehicle Decision Modeling Considering Plug-in Electric Vehicles

Plug-in electric vehicles (PEVs) offer alternatives to traditional vehicles that rely on petroleum-based fuels. While PEV customers can enjoy significant reductions in fuel costs, they incur a larger capital cost than users of traditional vehicles because PEV technology is still maturing. Therefore, consumers adopting PEVs face a trade-off between fuel cost savings with environmental benefits and extra capital cost. It is thus crucial for policy makers and PEV manufacturers to understand people's vehicle decision-making process while considering their socio-economic and travel pattern characteristics as well as the built-environment factors. This paper presents a connected, two-stage, dynamic model of PEV adoption and vehicle-transaction decision-making. Two connected nested logit (NL) models are estimated. The upper level is a two-level NL model to predict choice of vehicle type between four fuel types: gasoline, diesel, hybrid gasoline-electric, and PEV. The lower level is an NL model of vehicle-transaction choice which accommodates four transaction decisions of buy, trade, dispose, and do nothing, while accounting for the log-sum from the vehicle-type choice model, and is estimated using two waves of a panel data set. We find that households with higher levels of income and education are more likely to adopt a PEV. We also found that primarily decision makers take into account the accessibility to charging stations as a critical factor in choosing PEVs.

Nazari, Fatemeh↗

Maturation of Rhodobacter capsulatus Multicopper Oxidase CutO Depends on the CopA Copper Efflux Pathway and Requires the cutF Product (Final Report)

The goal is to achieve a comprehensive understanding of the nature, mechanism of function and biogenesis of c-type cytochromes and their oligomeric complexes. These cytochrome are ubiquitous heme proteins that are required for cellular bioenergetics, including photosynthesis (Ps) and respiration (Res), which are central to chemical energy (ATP) production by oxidative- and photophosphorylation. We contribute to the molecular characterization of individual and membrane-integral cytochromes as parts of Ps and Res electron transport (ET) pathways, using the facultative phototrophic bacteria of as excellent models for multidisciplinary investigations. Supported by this grant we discovered novel membrane-bound cytochromes and cyts c complexes that are important for Ps- and Res-ET. We worked out their biogenesis including maturation (covalent heme addition) and assembly of mature subunits into complexes. These involve fundamental process found virtually in all organisms and are fundamental processes with major significance to the “Photosynthetic Systems” program of DOE-BES, because the cytochromes are integral components of natural energy production systems. Elucidation of basic principles, and the knowledge gained by their study greatly impact on our ability to design, engineer, and create new natural, bio-hybrid, bio-inspired and artificial systems to better capture light, transduce and store its energy with improved efficacy and are of broad significance.

14 SOLAR ENERGY↗

High-Throughput Material Characterization using the Virtual Fields Method

Modeling material and component behavior using finite element analysis (FEA) is critical for modern engineering. One key to a credible model is having an accurate material model, with calibrated model parameters, which describes the constitutive relationship between the deformation and the resulting stress in the material. As such, identifying material model parameters is critical to accurate and predictive FEA. Traditional calibration approaches use only global data (e.g. extensometers and resultant force) and simplified geometries to find the parameters. However, the utilization of rapidly maturing full-field characterization techniques (e.g. Digital Image Correlation (DIC)) with inverse techniques (e.g. the Virtual Feilds Method (VFM)) provide a new, novel and improved method for parameter identification. This LDRD tested that idea: in particular, whether more parameters could be identified per test when using full-field data. The research described in this report successfully proves this hypothesis by comparing the VFM results with traditional calibration methods. Important products of the research include: verified VFM codes for identifying model parameters, a new look at parameter covariance in material model parameter estimation, new validation techniques to better utilize full-field measurements, and an exploration of optimized specimen design for improved data richness.

36 MATERIALS SCIENCE↗

Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective

Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both prognostic and therapeutic purposes has exploded thanks to increasing availability of electronic data and genomics. One promising direction that medical modeling is moving toward is adopting the same machine learning methods used by companies such as Google and Facebook to combat disease. Broadly defined, machine learning is a branch of computer science that deals with making predictions from complex data through statistical models. These methods serve to uncover patterns in data and are actively used in areas such as speech recognition, handwriting recognition, face recognition, “spam” filtering (junk email), and targeted advertising. Although multiple radiation oncology research groups have shown the value of applied machine learning (ML), clinical adoption has been slow due to the high barrier to understanding these complex models by clinicians. Here, we present a review of the use of ML to predict radiation therapy outcomes from the clinician's point of view with the hope that it lowers the “barrier to entry” for those without formal training in ML. We begin by describing 7 principles that one should consider when evaluating (or creating) an ML model in radiation oncology. We next introduce 3 popular ML methods—logistic regression (LR), support vector machine (SVM), and artificial neural network (ANN)—and critique 3 seminal papers in the context of these principles. Although current studies are in exploratory stages, the overall methodology has progressively matured, and the field is ready for larger-scale further investigation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Rosette core fungal resistance in Arabidopsis thaliana

Main conclusion: Unlike rosette leaves, the mature Arabidopsis rosette core can display full resistance to Botrytis cinerea revealing the importance for spatial and developmental aspects of plant fungal resistance. Abstract: Arabidopsis thaliana is a model host to investigate plant defense against fungi. However, many of the reports investigating Arabidopsis fungal defense against the necrotrophic fungus, Botrytis cinerea, utilize rosette leaves as host tissue. Here we report organ-dependent differences in B. cinerea resistance of Arabidopsis. Although wild-type Arabidopsis rosette leaves mount a jasmonate-dependent defense that slows fungal growth, this defense is incapable of resisting fungal devastation. In contrast, as the fungus spreads through infected leaf petioles towards the plant center, or rosette core, there is a jasmonate- and age-dependent fungal penetration blockage into the rosette core. In this paper, we report evidence for induced and preformed resistance in the rosette core, as direct rosette core inoculation can also result in resistance, but at a lower penetrance relative to infections that approach the core from infected leaf petioles. The Arabidopsis rosette core displays a distinct transcriptome relative to other plant organs, and BLADE ON PETIOLE (BOP) transcripts are abundant in the rosette core. The BOP genes, with known roles in abscission zone formation, are required for full Arabidopsis rosette core B. cinerea resistance, suggesting a possible role for BOP-dependent modifications that may help to restrict fungal susceptibility of the rosette core. Finally, we demonstrate that cabbage and cauliflower, common Brassicaceae crops, also display leaf susceptibility and rosette core resistance to B. cinerea that can involve leaf abscission. Thus, spatial and developmental aspects of plant host resistance play critical roles in resistance to necrotrophic fungal pathogens and are important to our understanding of plant defense mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

Accurate model annotation of a near-atomic resolution cryo-EM map

Electron cryomicroscopy (cryo-EM) has been used to determine the atomic coordinates (models) from density maps of biological assemblies. These models can be assessed by their overall fit to the experimental data and stereochemical information. However, these models do not annotate the actual density values of the atoms nor their positional uncertainty. Here, we introduce a computational procedure to derive an atomic model from a cryo- EM map with annotated metadata. The accuracy of such a model is validated by a faithful replication of the experimental cryo-EM map computed using the coordinates and associated metadata. The functional interpretation of any structural features in the model and its utilization for future studies can be made in the context of its measure of uncertainty. We applied this protocol to the 3.3-Å map of the mature P22 bacteriophage capsid, a large and complex macromolecular assembly. With this protocol, we identify and annotate previously undescribed molecular interactions between capsid subunits that are crucial to maintain stability in the absence of cementing proteins or cross-linking, as occur in other bacteriophages.

59 BASIC BIOLOGICAL SCIENCES↗

The International Heat Stress Genotype Experiment for Modeling Wheat Response to Heat: Field Experiments and AgMIP-Wheat Multi-Model Simulations

The data set contains a portion of the International Heat Stress Genotype Experiment (IHSGE) data used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat crop models and quantify the impact of heat on global wheat yield productivity. It includes two spring wheat cultivars grown during two consecutive winter cropping cycles at hot, irrigated, and low latitude sites in Mexico (Ciudad Obregon and Tlaltizapan), Egypt (Aswan), India (Dharwar), the Sudan (Wad Medani), and Bangladesh (Dinajpur). Experiments in Mexico included normal (November-December) and late (January-March) sowing dates. Data include local daily weather data, soil characteristics and initial soil conditions, crop measurements (anthesis and maturity dates, anthesis and final total above ground biomass, final grain yields and yields components), and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models.

Wheat; Field Experimental Data; Heat Stress; Simul↗

Advances in Grid Computing for the FabrIc for Frontier Experiments Project at Fermialb

The FabrIc for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientic Computing Division charged with leading the computing model for Fermilab experiments. Work within the FIFE project creates close collaboration between experimenters and computing professionals to serve high-energy physics experiments of diering size, scope, and physics area. The FIFE project has worked to develop common tools for job submission, certicate management, software and reference data distribution through CVMFS repositories, robust data transfer, job monitoring, and databases for project tracking. Since the projects inception the experiments under the FIFE umbrella have signicantly matured, and present an increasingly complex list of requirements to service providers. To meet these requirements, the FIFE project has been involved in transitioning the Fermilab General Purpose Grid cluster to support a partitionable slot model, expanding the resources available to experiments via the Open Science Grid, assisting with commissioning dedicated high-throughput computing resources for individual experiments, supporting the eorts of the HEP Cloud projects to provision a variety of back end resources, including public clouds and high performance computers, and developing rapid onboarding procedures for new experiments and collaborations. The larger demands also require enhanced job monitoring tools, which the project has developed using such tools as ElasticSearch and Grafana. in helping experiments manage their large-scale production work ows. This group in turn requires a structured service to facilitate smooth management of experiment requests, which FIFE provides in the form of the Production Operations Management Service (POMS). POMS is designed to track and manage requests from the FIFE experiments to run particular work ows, and support troubleshooting and triage in case of problems. Recently a new certicate management infrastructure called Distributed Computing Access with Federated Identities (DCAFI) has been put in place that has eliminated our dependence on a Fermilab-specic third-party Certicate Authority service and better accommodates FIFE collaborators without a Fermilab Kerberos account. DCAFI integrates the existing InCommon federated identity infrastructure, CILogon Basic CA, and a MyProxy service using a new general purpose open source tool. We will discuss the general FIFE onboarding strategy, progress in expanding FIFE experiments presence on the Open Science Grid, new tools for job monitoring, the POMS service, and the DCAFI project.

Herner, K.↗

Wind Tunnel Model Design for Sonic Boom Studies of Nozzle Jet Flows with Shock Interactions

NASA and the U.S. aerospace industry are performing studies of supersonic aircraft concepts with low sonic boom pressure signatures. The computational analyses of modern aircraft designs have matured to the point where there is confidence in the prediction of the pressure signature from the front of the vehicle, but uncertainty remains in the aft signatures due to boundary layer and nozzle exhaust jet effects. Wind tunnel testing without inlet and nozzle exhaust jet effects at lower Reynolds numbers than in-flight make it difficult to accurately assess the computational solutions of flight vehicles. A wind tunnel test in the NASA Ames 9- by 7-Foot Supersonic Wind Tunnel is planned for February 2016 to address the nozzle jet effects on sonic boom. The experiment will provide pressure signatures of test articles that replicate waveforms from aircraft wings, tails, and aft fuselage (deck) components after passing through cold nozzle jet plumes. The data will provide a variety of nozzle plume and shock interactions for comparison with computational results. A large number of high-fidelity numerical simulations of a variety of shock generators were evaluated to define a reduced collection of suitable test models. The computational results of the candidate wind tunnel test models as they evolved are summarized, and pre-test computations of the final designs are provided.

Wind Tunnel↗

Reduced-Order Aerodynamic Modeling Based on CFD Frequency Responses from Multisine Inputs

A system identification analysis was performed to determine reduced-order models of a computational fluid dynamics (CFD) solver for linear aeroelastic analysis and control design. The application was to the FUN3D code and the flexible half-span wind tunnel test article, in transonic flow conditions, used in the NASA-Boeing collaboration called the Integrated Adaptive Wing Technology Maturation (IAWTM) project. Multiple inputs (structural mode displacements and control surface deflections) were simultaneously excited with orthogonal phase-optimized multisines and multiple outputs (generalized aerodynamic forces) were recorded, from which the matrix of frequency responses were computed using a single CFD run. A state-space model was then fit to the frequency response data using a maximum-likelihood estimator.

System identification↗

Fusion and fission events regulate endosome maturation and viral escape

Endosomes are intracellular vesicles that mediate the communication of the cell with its extracellular environment. They are an essential part of the cell’s machinery regulating intracellular trafficking via the endocytic pathway. Many viruses, which in order to replicate require a host cell, attach themselves to the cellular membrane; an event which usually initiates uptake of a viral particle through the endocytic pathway. In this way viruses hijack endosomes for their journey towards intracellular sites of replication and avoid degradation without host detection by escaping the endosomal compartment. Recent experimental techniques have defined the role of endosomal maturation in the ability of enveloped viruses to release their genetic material into the cytoplasm. Endosome maturation depends on a family of small hydrolase enzymes (or GTPases) called Rab proteins, arranged on the cytoplasmic surface of its membrane. Here, we model endosomes as intracellular compartments described by two variables (its levels of active Rab5 and Rab7 proteins) and which can undergo coagulation (or fusion) and fragmentation (or fission). The key element in our approach is the “per-cell endosomal distribution” and its dynamical (Boltzmann) equation. The Boltzmann equation allows us to derive the dynamics of the total number of endosomes in a cell, as well as the mean and the standard deviation of its active Rab5 and Rab7 levels. We compare our mathematical results with experiments of Dengue viral escape from endosomes. The relationship between endosomal active Rab levels and pH suggests a mechanism that can account for the observed variability in viral escape times, which in turn regulate the viability of a viral intracellular infection.

59 BASIC BIOLOGICAL SCIENCES↗

Pilot Testing of a Highly Efficient Pre-combustion Sorbent-based Carbon Capture System

TDA developed and demonstrated a highly efficient pre-combustion carbon capture system. The overall objective of this work was to develop a new sorbent-based pre-combustion carbon capture technology for Integrated Gasification Combined Cycle (IGCC) power plants. In this project our goal was to demonstrate the techno-economic viability of the new technology by 1) demonstrating it in large-scale slipstream tests, and 2) carrying out a high fidelity engineering and cost analysis. TDA’s process used an advanced physical adsorbent that selectively removes CO 2 from coal-derived synthesis gas above the dew point of the gas at temperatures as high as 300°C. The sorbent consists of a mesoporous carbon whose surface was grafted with functional groups that remove CO 2 via a well-known acid-base interaction. As documented in bench-scale experiments and field tests with actual coal gas, the sorbent achieved a very high capacity for CO 2 at temperatures as high as 300°C. The sorbent bound CO 2 more strongly than common physical adsorbents, providing the chemical potential needed for the high temperature operation. However, because CO 2 does not form a true covalent bond with the surface sites (as is the case with chemical absorbents), the sorbent regeneration could be carried out with only a very small energy input. The heat input to regenerate our sorbent was only 4.9 kcal per mol of CO 2 , which is much lower than that for chemical absorbents (e.g., 29.9 kcal/mol CO 2 for sodium carbonate) and was similar to the requirements of physical solvents (e.g., 4 kcal/mol CO 2 for Selexol TM ). Because the sorbent operates above the dew point of the synthesis gas (unlike the Selexol TM process), a higher power cycle efficiency can be achieved. With previous DOE/NETL funding (Contract No. DE-FE-0000469), we demonstrated the techno-economic viability of the technology in bench-scale tests and slipstream demonstrations at the National Carbon Capture Center (NCCC), Wilsonville, Alabama and Wabash River IGCC plant in Terra Haute, Indiana. We demonstrated a stable working CO 2 capacity for over 11,650 cycles with simulated synthesis gas. We also evaluated its performance with actual synthesis gas in two test campaigns at the Wabash River IGCC Plant, Terre Haute, IN and the National Carbon Capture Center (NCCC), Wilsonville, AL. The slipstream tests clearly showed that the actual coal gas constituents and potential contaminants (e.g. trace metals, halides, tars) had no effect on the sorbent’s ability to remove CO 2 (the same sorbent beds were used in both field tests with no sign of deactivation for 2,000 cycles with over 26,750 SCF of gas treated). As expected, due to the high temperature CO 2 removal capability and low energy needed to regenerate the sorbent, the power cycle efficiency with our process was greater than 34% on a higher heating value (HHV) basis; in comparison, the same IGCC plant equipped with the Selexol TM solvent for carbon capture can only achieve 31.4% HHV efficiency. The capital cost for an IGCC system with TDA’s process is estimated as $2,417/kW e , which is 12% lower than that of the IGCC/ Selexol TM process. The levelized cost for electricity including the transport, storage and monitoring (TS&M) cost for CO 2 was calculated as $\$ $92.9/MWh (lowest reported to our knowledge), which is much better than the $105.2/MWh estimated for the IGCC/ Selexol TM process. In this project (DE-FE0013105), TDA Research, in collaboration with our partners Gas Technology Institute (GTI), Illinois Clean Coal Institute (ICCI), University of California, Irvine (UCI), University of Alberta (UOA), Siemens, NCCC and Sinopec advanced the technical maturity of the technology; scaling it up by a factor of 100. We optimized the reactor design using computational fluid dynamics (CFD); using adsorption modeling we improved the pressure swing adsorption (PSA) cycle sequence. We carried out two field test campaigns with a fully-equipped 0.1 MW e prototype unit (for a total of 844 hours) using actual synthesis gas to prove the viability of the new technology. A successful 30 day (707 hrs) evaluation was completed at NCCC under air blown gasification conditions. We demonstrated 97.3% carbon capture at 1,500 SLPM, 93% carbon capture at 1,800 SLPM, and 90% carbon capture at 2,100 SLPM in the NCCC tests. We also demonstrated the system for 137 hours at a Sinopec petrochemical plant under oxygen blown gasification, demonstrating 86% carbon capture at 2,660 SLPM. In collaboration with University of California, Irvine (UCI), we completed a techno-economic analysis (TEA) for TDA’s warm gas cleanup technology integrated to IGCC power plant. The net plant efficiencies (on a coal HHV basis) for the warm gas cleanup cases were estimated to be 34.0% for E-GasTM gasifier, 34.4% for GE gasifier, 33.4 for the Shell gasifier and 34.2 for the TRIG TM gasifier (Cases 2, 4, 6 and 8 in this study) with a catalytic combustor for CO 2 purification, which are significantly higher than those for the Cold Gas Case, or an increase of as much as 12% in the heat rate for Case 2, 6% for Case 4, 9% for Case 6, and 9% for Case 8. The 1st year cost of electricity with the transport, storage and monitoring (TS&M) costs for the CO 2 included was $\$ $129.2/MWh for the E-GasTM gasifier Warm Gas Cleanup Case, $\$ $131.9/MWh for the GE gasifier Warm Gas Cleanup Case, $\$ $146.8/MWh for the Shell Gasifier Warm Gas Cleanup Case, and $\$ $129.9/MWh for the TRIG TM gasifier Warm Gas Cleanup Case. For comparison, the costs for the baseline Cold Gas CO 2 removal with Selexol for the different gasifiers were: $\$ $146.6/MWh for the E-Gas TM gasifier, $\$ $142.2/MWh for the GE gasifier, $\$ $159.0/MWh for the Shell gasifier and $\$ $144.3/MWh for the TRIG TM gasifier. In summary, the costs for our system were 7 to 12% lower than the corresponding Cold Gas Cleanup cases. The results of this techno-economic analysis suggested that TDA’s high temperature PSA-based Warm Gas Clean-up Technology can make a substantial improvement in the IGCC plant thermal performance for achieving near zero CO 2 emissions for E-Gas TM , GE, Shell and TRIG TM gasifier based IGCC power plants. The capital expenses were estimated to be lower than that of Selexol’s™. Taken together, the higher net plant efficiency and lower capital and operating costs resulted in substantial reduction in the cost of carbon capture for the IGCC plant equipped with TDA’s high temperature PSA-based carbon capture system. Finally, in collaboration with Gas Technology Institute (GTI) we completed the environmental health and safety assessment for TDA’s warm gas carbon capture technology.

01 COAL, LIGNITE, AND PEAT↗

Characterization of Exoplanet Atmospheres with the Optical Coronagraph on WFIRST

Wide-Field Infrared Survey Telescope (WFIRST)-CGI is a NASA technology demonstration mission that is charged with demonstrating key technologies for future exo-Earth imaging missions in space. In the process, it will obtain images and low-resolution spectra of a handful to a dozen extrasolar planets and possibly protoplanetary disks. Its unprecedented contrast levels in the optical will provide astronomers’ with their first direct look at mature, Jupiter-sized planets at moderate separations. This paper addresses the question: what science can be done with such data? An analytic noise model, which is informed by the ongoing engineering developments, is used to compute maximum achievable signal-to-noise ratios and scientifically viable integration times for hypothetical star–planet systems, as well as to investigate the constraining power of various combinations of WFIRST-CGI photometric and spectral observations. This work introduces two simple models for planetary geometric albedos, which are inspired largely by the solar system’s gas giants. The first planet model is a hybrid Jupiter–Neptune model, which separately treats the short and long wavelengths where chromophores and methane dominate absorption, respectively. The second planet model fixes cloud and haze properties in CoolTLusty to match Jupiter’s albedo spectrum, it then perturbs only the metallicity. MCMC retrievals performed on simulated observations are used to assess the precision with which planet model parameters can be measured subject to different exposure times and observing cases. Planet radius is recovered within ±15% for all observing cases with both the hybrid model and the CoolTLusty metallicity grid. Fit results for both models’ parameterizations of geometric albedo spectra demonstrate that a rough indication of the metallicity or methane content should be possible for some WFIRST-CGI targets. We conclude that real observations will likely be able to differentiate between extreme cases using these models, but will lack the precision necessary to uncover subtle trends.

79 ASTRONOMY AND ASTROPHYSICS↗

A lunar soil evolution model

Comminution, agglutination, and replenishment processes in a lunar soil are modeled by a system of time-dependent linear differential equations. In the model, a soil is subdivided into coarse-particle, fine-particle, and agglutinate fractions. The relative mass abundance of each component in a mature soil is found to be proportional to rates for the reworking processes. Evolution of the grain-size distribution from a fresh ejecta blanket to a mature soil is described quantitatively in terms of the changing proportions of the three soil constituents. If size data are available for an immature soil and a mature soil of the same system, rates for the various processes can be calculated under certain simplifying assumptions.

Mendell, W. W.↗