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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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Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models

Efficient methods for searching the chemical space of molecular compounds are needed to automate and accelerate the design of new functional molecules such as pharmaceuticals. Given the high cost in both resources and time for experimental efforts, computational approaches play a key role in guiding the selection of promising molecules for further investigation. Here, we construct a workflow to accelerate design by combining approximate quantum chemical methods [i.e. density-functional tight-binding (DFTB)], a graph convolutional neural network (GCNN) surrogate model for chemical property prediction, and a masked language model (MLM) for molecule generation. Property data from the DFTB calculations are used to train the surrogate model; the surrogate model is used to score candidates generated by the MLM. The surrogate reduces computation time by orders of magnitude compared to the DFTB calculations, enabling an increased search of chemical space. Furthermore, the MLM generates a diverse set of chemical modifications based on pre-training from a large compound library. We utilize the workflow to search for near-infrared photoactive molecules by minimizing the predicted HOMO-LUMO gap as the target property. Our results show that the workflow can generate optimized molecules outside of the original training set, which suggests that iterations of the workflow could be useful for searching vast chemical spaces in a wide range of design problems.

Blanchard, Andrew↗

Assessing ion–electron thermal equilibration in the scrape‐off layer of tokamaks using UEDGE

The ion–electron thermal equilibration along the scrape‐off layer (SOL) has been assessed using an analytical, one‐dimensional (1D) model; a single‐flux tube model assessed with the multi‐fluid code UEDGE, and an orthogonal, two‐dimensional (2D) slab model in UEDGE for pure deuterium plasmas. These studies highlight the importance of thermal equipartition, radial transport, and loss processes in ion–electron thermal equilibration in the SOL and demonstrates the strong dependence of equipartition on local plasma parameters. For the 2D UEDGE cases, equipartition is predicted to cool the ions by up to a factor of 2 at the upstream location and to heat the electrons by up to a factor of 3, predominantly in front of the target. Diffusive radial transport into the private flux region and far SOL is predicted to reduce the upstream ion temperatures by up to 30% compared to the 1D UEDGE predictions, and volumetric power and momentum sinks (charge‐exchange, ionization, recombination, and hydrogen radiation) reduces the target ion and electron temperatures by up to one order of magnitude compared to a 1D model considering conduction and equipartition only. The losses and radial transport are, however, insufficient to achieve T i ≈ T e in the absence of thermal equipartition due to losses affecting the ions and electrons asymmetrically. UEDGE simulations on a 2D slab predicts radially varying T i / T e ratios due to radial transport, which is not considered in any 0D or 1D models of the SOL.

Holm, A.↗

Multibody dynamics: Modeling component flexibility with fixed, free, loaded, constraint, and residual modes

The assumed-modes method in multibody dynamics allows the elastic deformation of each component in the system to be approximated by a sum of products of spatial and temporal functions commonly known as modes and modal coordinates respectively. The choice of component modes used to model articulating and non-articulating flexible multibody systems is examined. Attention is directed toward three classical Component Mode Synthesis (CMS) methods whereby component normal modes are generated by treating the component interface (I/F) as either fixed, free, or loaded with mass and stiffness contributions from the remaining components. The fixed and free I/F normal modes are augmented by static shape functions termed constraint and residual modes respectively. A mode selection procedure is outlined whereby component modes are selected from the Craig-Bampton (fixed I/F plus constraint), MacNeal-Rubin (free I/F plus residual), or Benfield-Hruda (loaded I/F) mode sets in accordance with a modal ordering scheme derived from balance realization theory. The success of the approach is judged by comparing the actuator-to-sensor frequency response of the reduced order system with that of the full order system over the frequency range of interest. A finite element model of the Galileo spacecraft serves as an example in demonstrating the effectiveness of the proposed mode selection method.

Spanos, John T.↗

Low-Cost Heliostat for High-Flux Small-Area Receivers (Final Technical Report)

This project analyzed a two-stage heliostat concept consisting of a tracking stage and a concentrating stage. The tracking stage uses mirrors mounted on a common drive that move to track the sun. The concentrating stage consists of stationary mirrors that each have a unique angle to direct rays towards a small-area, high-flux, point-focused receiver. By splitting the collection and concentrating process into two stages, multiple small, inexpensive mirrors can share a structure and be controlled by a single drive in the tracking stage. The project effort developed modeling techniques that were specifically relevant to this two-stage heliostat concept. Both field-level and unit-level models were developed. The field-level model does not explicitly consider unit-level losses which are predicted by the unit-level model and then integrated into the field-level model through a correlation referred to as an efficiency modifier. This approach is referred to as the two-model approach; the development and demonstration of this two-model approach for a multi-stage heliostat technology is a key outcome of this work. The field-level model is used to design a field that hits a specific design day power given a set of heliostat design parameters. An oversized field is simulated and then heliostat units are removed based on their annual energy production in order to generate the highest performing field. The field reduction procedure fits a smooth curve fit to annual energy production as a function of position in the field which has the effect of reducing the noise that is otherwise caused by the Monte Carlo ray tracing technique. This approach is referred to as the annual energy fit method and substantially reduces computational run time for a given field level modeling accuracy. The annual energy fit approach enables the selection of a properly sized, high-performing field using orders of magnitude fewer rays than would otherwise be possible and the development of this approach is a second key outcome of this work. These models are used within a genetic optimization algorithm in order to optimize the geometric parameters associated with a heliostat in order to achieve the lowest cost per unit of collected design day power. The cost modeling that underlies the optimization is a simple, scaling type analysis backed up by a much more detailed Design for Manufacture and Assembly (DFMA) analysis. Although the figure of merit used for optimization was not cost per mirror area, this metric is reasonable to use as a means of comparison. The optimally designed 500 kW design has a tracking mirror specific cost of $181.85/m 2 , which is significantly larger than the target value and also larger than the current state of the art. The cost of the torque-tube type linkages contributed substantially to the overall cost. Based on this observation, potentially attractive alternative design configuration utilizing a capstan type actuation system should be investigated. Finally, NREL compared the performance of the two-stage heliostat to the performance of a focused and different sized flat conventional heliostats and showed that, as expected, additional losses versus the convention heliostat caused by a worse cosine efficiency, two stages of reflection, and interstage interactions. The two-stage heliostat requires around 75% more reflective area than a flat 1x1 meter conventional heliostat (similar to a focused heliostat) and 40% more than a flat 2x2 meter conventional heliostat.

14 SOLAR ENERGY↗

Refinement of a limit cycle oscillator model of the effects of light on the human circadian pacemaker

In 1990, Kronauer proposed a mathematical model of the effects of light on the human circadian pacemaker. Although this model predicted many general features of the response of the human circadian pacemaker to light exposure, additional data now available enable us to refine the original model. We first refined the original model by incorporating the results of a dose response curve to light into the model's predicted relationship between light intensity and the strength of the drive onto the pacemaker. Data from three bright light phase resetting experiments were then used to refine the amplitude recovery characteristics of the model. Finally, the model was tested and further refined using data from an extensive phase resetting experiment in which a 3-cycle bright light stimulus was presented against a background of dim light. In order to describe the results of the four resetting experiments, the following major refinements to the original model were necessary: (i) the relationship between light intensity (I) and drive onto the pacemaker was reduced from I1/3 to I0.23 for light levels between 150 and 10,000 lux; (ii) the van der Pol oscillator from the original model was replaced with a higher-order limit cycle oscillator so that amplitude recovery is slower near the singularity and faster near the limit cycle; (iii) a direct effect of light on circadian period (tau x) was incorporated into the model such that as I increases, tau x decreases, which is in accordance with "Aschoff's rule". This refined model generates the following testable predictions: it should be difficult to enhance normal circadian amplitude via bright light; near the critical point of a type 0 phase response curve (PRC) the slope should be steeper than it is in a type 1 PRC; and circadian period measured during forced desynchrony should be directly affected by ambient light intensity.

NASA Discipline Regulatory Physiology↗

Intertidal Creeks and Overmarsh Circulation in a Small Salt Marsh Basin

The role of intertidal creek networks in overmarsh circulation is not well constrained. In this study, we systematically remove intertidal creeks from a high-resolution salt marsh digital elevation model and conduct new flow simulations with each iteration. Overall, removal of first- and second-order creeks reduced drainage density by 65%, and this had a negligible effect on overmarsh circulation and tracer distribution. However, upon removal of third- and fourth-order creeks, drainage density was reduced by 80% of the original value, and changes in peak velocity magnitude across various spatial and temporal scales reveal a system-wide switch from ebb to flood dominance. This response coincides with the interruption of topographically connected creeks that facilitate the direct exchange of water and tracer between the marsh interior and the larger subtidal system. Further, this reduction in hydraulic connectivity gives rise to less expansive tracer dispersal and a systematic decline in tracer residence time. Together, these results reveal that for the Groves Creek marsh, lower-order intertidal creeks have a minor role in overmarsh circulation, while higher-order creeks increase the potential for short circuiting of flow; they greatly influence overall flood and ebb dominance, and net tracer dispersal and associated retention time. Moreover, results reported here provide new insight on, for example, salt marsh restoration and the requisite digital elevation model bathymetry for robust simulations of overmarsh circulation.

58 GEOSCIENCES↗

An improved rotated staggered-grid finite-difference method with fourth-order temporal accuracy for elastic-wave modeling in anisotropic media

The rotated staggered-grid (RSG) finite-difference method is a powerful tool for elastic-wave modeling in 2D anisotropic media where the symmetry axes of anisotropy are not aligned with the coordinate axes. We develop an improved RSG scheme with fourth-order temporal accuracy to reduce the numerical dispersion associated with prolonged wave propagation or a large temporal step size. The high-order temporal accuracy is achieved by including high-order temporal derivatives, which can be converted to high-order spatial derivatives to reduce computational cost. Dispersion analysis and numerical tests show that our method exhibits very low temporal dispersion even with a large temporal step size for elastic-wave modeling in complex anisotropic media. Using the same temporal step size, our method is more accurate than the conventional RSG scheme. In conclusion, our improved RSG scheme is therefore suitable for prolonged modeling of elastic-wave propagation in 2D anisotropic media.

58 GEOSCIENCES↗

Accelerating structural dynamics simulations with localised phenomena through matrix compression and projection‐based model order reduction

In this work, a novel approach is introduced for accelerating the solution of structural dynamics problems in the presence of localised phenomena, such as cracks. For this category of problems, conventional projection-based Model Order Reduction (MOR) methods are either limited with respect to the range of system configurations that can be represented or require frequent solutions of the Full Order Model (FOM) to update the low-dimensional spaces, in which solutions are represented. In the proposed approach, low-dimensional spaces, constructed for the healthy structure, are enriched with appropriately selected columns of the flexibility matrix of the system. It can be shown that these spaces contain the solution to the original problem for the static case, while their dimension is much smaller. In order to allow their online construction for arbitrary localised features, the full flexibility matrix of the system should be available. To this end, a hierarchical representation is used for the matrices involved, allowing to compute the flexibility matrix efficiently and with reduced memory requirements. The resulting method offers significant speedups, without sacrificing the flexibility and accuracy of the full order model. The performance and limitations of the approach are studied through a series of examples in structural dynamics.

fracture mechanics↗

Uncertainty Quantification and Sensitivity Analysis of Nuclear Construction Cost Reduction Pathways

High construction costs have plagued recent nuclear projects and they hamper the widespread deployment of nuclear technology. The Nuclear Cost Reduction Tool is a plant economic framework that quantifies the impact that various plant design and construction attributes have on construction costs and cost overruns and shows the positive effects of learning over a series of deployments. However, a downside of the current model is that all model outputs and capabilities are deterministic. To provide a more comprehensive view, this study evaluated the impact of model parameter uncertainty through a sensitivity analysis applied to 18 model parameters. This approach quantified the impact of model uncertainty on the output variables of Net Overnight Capital Cost (Net OCC), Construction Duration (CD), and Levelized Cost of Electricity (LCOE). Monte Carlo analysis revealed uncertainty distributions for these variables, showing that absolute uncertainty decreases over a series of deployments. A local sensitivity analysis showed that even small parameter perturbations (5%) can have a significant impact on project execution, highlighting areas that could reduce costs by billions across an order book of plants. The results of this study have improved the understanding of the model and identified the most impactful model parameters and construction attributes.

Levelized Cost of Electricity↗

Direct Fault Tolerant RLV Altitude Control: A Singular Perturbation Approach

In this paper, we present a direct fault tolerant control (DFTC) technique, where by "direct" we mean that no explicit fault identification is used. The technique will be presented for the attitude controller (autopilot) for a reusable launch vehicle (RLV), although in principle it can be applied to many other applications. Any partial or complete failure of control actuators and effectors will be inferred from saturation of one or more commanded control signals generated by the controller. The saturation causes a reduction in the effective gain, or bandwidth of the feedback loop, which can be modeled as an increase in singular perturbation in the loop. In order to maintain stability, the bandwidth of the nominal (reduced-order) system will be reduced proportionally according to the singular perturbation theory. The presented DFTC technique automatically handles momentary saturations and integrator windup caused by excessive disturbances, guidance command or dispersions under normal vehicle conditions. For multi-input, multi-output (MIMO) systems with redundant control effectors, such as the RLV attitude control system, an algorithm is presented for determining the direction of bandwidth cutback using the method of minimum-time optimal control with constrained control in order to maintain the best performance that is possible with the reduced control authority. Other bandwidth cutback logic, such as one that preserves the commanded direction of the bandwidth or favors a preferred direction when the commanded direction cannot be achieved, is also discussed. In this extended abstract, a simplistic example is proved to demonstrate the idea. In the final paper, test results on the high fidelity 6-DOF X-33 model with severe dispersions will be presented.

Zhu, J. J.↗

Validation of Cryogenic Propellant Tank Self-Pressurization

NASA’s near-future long-term space missions necessitate advancements in cryogenic fluid management (CFM), which includes safe and reliable long-term propellant storage. Consequently, NASA STMD (Space Technology Mission Directorate) has established the CFM Portfolio Project to improve CFM technologies for upcoming missions. As a part of CFM Modeling Portfolio, NASA Marshall Space Flight Center’s (MSFC) Fluid Dynamics branch within the Propulsion Systems Department is tasked with assessing and improving computational tools used to support flight projects such as Human Lander System and Commercial Lunar Payload Services. One of the challenging modeling problems is that of self-pressurization of propellant tank due to heat leakage over long time periods. Reduced order and nodal tools find it extremely difficult to accurately predict self-pressurization under transient conditions or where complex flow patterns or thermal gradients exist, and application of 3-D CFD (computational fluid dynamics) simulations is necessary to characterize these problems. Until recently, CFD simulations for these long-term processes (order of hours or days) have been too impractical to conduct due to prohibitive wall time and computational resource requirements. The requisite CFD tool need to be efficient, computationally scalable, modular with ability to incorporate various physics models, and robust enough to not accumulate conservation errors over several hours of simulated time. NASA MSFC’s Loci-Stream CFD tool along with the VOF module is a great candidate to fit this mold. In this paper, we validate Loci-Stream for predicting self-pressurization of a flight scale propellant tank so it can serve as a reliable design and analysis tool for NASA’s CFM application needs. Liquid hydrogen tank pressurization tests carried out at the K-site testing facility provide a reliable data set for this purpose. These tests were simulated using Loci-Stream solver with VOF module as well as a hybrid approach which uses a lumped model for the ullage gas domain and CFD simulation of the liquid propellant. Both are shown to have very good predictive capabilities over multiple K-site experiments.

Hong Q. Yang↗

Validation of Cryogenic Propellant Tank Self-Pressurization

NASA's near-future long-term space missions necessitate advancements in cryogenic fluid management (CFM), which includes safe and reliable long-term propellant storage. Consequently, NASA STMD (Space Technology Mission Directorate) has established the CFM Portfolio Project to improve CFM technologies for upcoming missions. As a part of CFM Modeling Portfolio, NASA Marshall Space Flight Center's (MSFC) Fluid Dynamics branch within the Propulsion Systems Department is tasked with assessing and improving computational tools used to support flight projects such as Human Lander System and Commercial Lunar Payload Services. One of the challenging modeling problems is that of self-pressurization of propellant tank due to heat leakage over long time periods. Reduced order and nodal tools find it extremely difficult to accurately predict self-pressurization under transient conditions or where complex flow patterns or thermal gradients exist, and application of 3-D CFD (computational fluid dynamics) simulations is necessary to characterize these problems. Until recently, CFD simulations for these long-term processes (order of hours or days) have been too impractical to conduct due to prohibitive wall time and computational resource requirements. The requisite CFD tool need to be efficient, computationally scalable, modular with ability to incorporate various physics models, and robust enough to not accumulate conservation errors over several hours of simulated time. NASA MSFC's Loci-Stream CFD tool along with the VOF module is a great candidate to fit this mold. In this paper, we validate Loci-Stream for predicting self-pressurization of a flight scale propellant tank so it can serve as a reliable design and analysis tool for NASA's CFM application needs. Liquid hydrogen tank pressurization tests carried out at the K-site testing facility provide a reliable data set for this purpose. These tests were simulated using Loci-Stream solver with VOF module as well as a hybrid approach which uses a lumped model for the ullage gas domain and CFD simulation of the liquid propellant. Both are shown to have very good predictive capabilities over multiple K-site experiments.

cryogenic fluid management↗

Machine Learning for Memory Reduction in the Implicit Monte Carlo Simulations of Thermal Radiative Transfer [Slides]

Project Goal: Use parametric Machine Learning methods in order to reduce memory requirements at checkpointing & restarting in the IMC simulations of Thermal Radiative Transfer using: Expectation Maximization and Weighted Gaussian Mixture Model-based approach for `particle-data compression', introduced in Plasma Physics to model Maxwellian particle distributions by Luis Chacon and Guangye Chen; Expectation Maximization with Weighted Hyper-Erlang Model in order to compress isotropic IMC particle data in the frequency domain; and Expectation Maximization and von Mises-Fisher Mixture Model for compression of anisotropic IMC particle data in the angular domain (work-in-progress).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Coupling Visualization, Simulation, and Deep Learning for Ensemble Steering of Complex Energy Models

We describe a new framework that allows users to explore and steer ensembles of energy systems simulations by coupling multiple energy models and interactive visualization through a dataflow API. Through the visual interface, users can interactively explore complex parameter spaces populated by hundreds, or thousands, of simulation runs and interactively spawn new simulations to 'fill in' regions of interest in the parameter space. The computational and visualization capabilities reside within a general-purpose dataflow architecture for connecting producers of multidimensional timeseries data, such as energy simulations, with consumers of that data, whether they be visualizations, statistical analyses, or datastores. Fast computation and agile dataflow can enhance the engagement with energy simulations, allowing users to populate the parameter space in real time. However, many energy simulations are far too slow to provide an interactive response. To support interactive feedback, we are creating reduced-form simulations developed through machine learning techniques, which provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost. These reduced-form simulations have response times on the order of seconds, suitable for real-time human-in-the-loop design and analysis. The approximation methods apply to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. Such reduced-form representations do not replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and exploration for large ensembles of simulations. The improved understanding, facilitated by the reduced-form models, dataflow API, and visualization tools, allows researchers to better allocate computational resources to capture informative relationships within the system as well as provide a low-cost method for validating and quality-checking large-scale modeling efforts.

97 MATHEMATICS AND COMPUTING↗

Development of a Thin Film Primary Surface Heat Exchanger for Advanced Power Cycles

This project objective is to develop a high-temperature design upgrade for an existing primary surface heat exchanger so that the redesigned hardware is capable of operation in CO 2 at temperatures up to 1,510°F (821°C) and pressure differentials up to 130 psi (9 bar). The heat exchanger is proposed for use as a recuperator in an advanced low-pressure oxy-fuel Brayton cycle that is predicted to achieve over 50% thermodynamic efficiency, although the heat exchanger could also be used in other high-temperature, low-differential pressure cycles. This report describes the progress to date, which includes continuing work performed to select and test new candidate materials for the recuperator redesign, final mechanical and thermal performance analysis results of various redesign concepts, and the preliminary design of a test loop for the redesigned recuperator including a budgetary estimate for detailed test loop design, procurement, and test operation. A materials search was performed in order to investigate high-temperature properties of many candidate materials, including high-temperature strength and nickel content. These properties were used to rank the candidate materials, resulting in a reduced list of nine materials for corrosion testing. Multiple test rigs were considered and analyzed for short-term corrosion testing and Thermal Gravimetric Analysis (TGA) was selected as the most cost-effective option for evaluating corrosion resistance of the candidate materials. In addition, tantalum, niobium, and chromium coatings were identified as potential options for increased corrosion resistance. The test results show that many materials exhibit relatively low weight gain rates, and that niobium and tantalum coatings may improve corrosion resistance for many materials, while chromium coatings appear to oxidize and debond quickly. Metallurgical analysis of alloys was also performed, showing evidence of intergranular attack in 282 that may cause long-term reliability problems in CO 2 service at these temperatures. However, long-term testing in a flowing environment is recommended in order to understand accurately the severity of the attack. Detailed economic modeling of the existing air cycle recuperator and CO 2 cycle recuperator options was also completed, including costs for material, fabrication, fuel, maintenance, and operation. The analysis results show that the increased capital cost for high-temperature materials may be offset by higher cycle efficiencies, decreasing the overall lifetime cost of the system. The economic analysis also examines costs associated with increased pressure drop and material changes for two redesign options. These results show that, even with slightly reduced performance and/or higher material costs, the lifetime cost per energy production may still be reduced by over 12%. The existing recuperator design information was provided by Solar Turbines, Inc. via several models, drawings, and design handoff meetings. Multiple fluid/thermal and structural models were created in order to analyze critical recuperator performance and mechanical strength in critical areas throughout the redesign process. These models were analyzed for a baseline condition (consistent with current Mercury 50 operation) for validation purposes. Results are presented for heat transfer coefficients and pressure drops, matching well with the existing operational data. Simulation of higher-temperature CO 2 conditions was also performed, showing a slight expected increase in both heat transfer and pressure drop. Mechanical analysis results for critical areas on the cross-flow and counter-flow sheets have also been obtained for air and CO 2 cases. These results show similar stresses in both cases but significantly reduced safety factors for the CO 2 case due to reduced yield and creep rupture strengths of alloy 625 at the higher temperatures. A concept brainstorm session and initial down-selection were completed in order to identify promising redesign options for further analysis. Detailed analysis of all promising redesign options was performed via finite element and computational fluid dynamic simulations in order to characterize mechanical and thermal-fluid performance of each option. These options included material change, various sheet thickness configurations, pitch and phasing of cross-flow and counter-flow sheets, and separator sheets. The analysis results have identified two viable redesign options that maintain existing safety margins optimally through a material change to Haynes 282 and (A) sheet thickness increases of 40% on the counter-flow sheet and 75% on the hot side cross-flow corrugation sheet or (B) addition of a separator sheet in the counter-flow section while maintaining the original counter-flow sheet thickness and increasing the cross-flow corrugation sheet thickness by 90% to account for the increase in cell height. While both options satisfy mechanical stress constraints, the separator sheet design has a higher part count, slightly reduced heat transfer, and slightly higher pressure drop than the first option and is not preferred. Finally, several test loop concepts have been developed for different full-scale and reduced-scale recuperator testing options. For each option, various loop components, such as heat exchangers, valves, heaters, and compressors, were evaluated in an effort to maximize utilization of existing resources. All concepts utilize an existing 3-MW CO 2 compressor, heater, and loop coolers, but the concepts vary by incorporating different amounts of new equipment for achieving various flow rates (all concepts operate at design pressure and temperature). The third concept achieves a 1 kg/s test without purchasing any costly equipment (coolers, heaters, blowers, etc.). Since the stacked cell design of the recuperator results in the same flow conditions at each core cell (even for a reduced-scale test). Thus, test loop Concept #3 was selected for the preliminary design. This loop design is detailed within the report, culminating in a budgetary estimate of $1,013,000.00 for the detailed design, construction, commissioning, and operation of a high-temperature recuperator test loop.

03 NATURAL GAS↗

Major improvements on the longwave radiative interactions between surface and clouds in the Polar Regions in atmospheric global circulation model (GCM). Final Project Report

1. Summary of Work and Accomplishments in Year 1 (01/15/2015-01/14/2016). We developed new ice cloud parameterizations based on state-of-the-art MODIS Collection 6 (MC6) ice particle model. Features of the model include the consideration of surface roughness of ice crystals and spectral consistency in cloud property retrievals. Using more than 14,000 particle size distributions (PSDs) from in-situ measurements and the latest ice particle single-scattering property library, our parameterizations provide band-averaged bulk-scattering properties. According to statistics of fittings, the parameterization schemes represent the band-averaged bulk-scattering properties very well. Compared to the ice particle model developed by Fu (1998), flux simulations with the MC6 particle model result in larger upward flux at the top of the atmosphere (TOA) and smaller at the surface for typical cirrus clouds. In the assessment of the effect of longwave light scattering, our results also support the conclusions of previous studies. The error in flux calculations reaches about 10 W/m 2 when a cirrus cloud is thin and its particle size is small. 2. Summary of Work and Accomplishments in Year 2 (01/15/2016-01/14/2017) Clouds are a major modulator of the global radiation budgets. However, representations of clouds in general circulation models (GCMs) neglect many important processes, particularly those related to ice clouds. One major uncertainty source is the radiative transfer scheme in GCMs. To reduce the computational burden in most GCMs, absorption is the only radiative transfer process considered in longwave spectral bands. Recently, a state-of-the-art MC6 ice model has been available, which provides spectral consistency in ice cloud retrievals. With an advanced light scattering library for ice particles, we performed sensitivity studies of the potential impacts on the climate including light scattering for MC6 model and other 11 ice cloud models. Specifically, we modified RRTMG_LW (the GCM version of Longwave Rapid Radiative Transfer Model), a radiative transfer module widely used in GCMs and numerical prediction models, to identify flux simulation differences with and without considering light scattering processes. The simulations with light scattering come from a rigorous radiative solver, DISORT (Discrete Ordinates Radiative Transfer Program for a Multi-Layered Plane-Parallel Medium), are used as benchmarks. The results show that the weighted annual mean biases of RRTMG_LW for the upward flux at the top of the atmosphere, the downward flux at the surface, and the net flux into the atmosphere are about 0.8 ± 0.3, -0.1 ± 0.05, and -0.7 ± 0.3 W m-2, respectively. According to the different the ice crystal shapes, the weighted annual mean bias for heating rate is about -0.006 ± 0.02 to 0.04 K/day. 3. Summary of Work and Accomplishments in Year 3 (01/15/2017-01/14/2018) Since absorption dominates optical properties of clouds in the longwave (LW) spectrum, most of general circulation models (GCMs) only take absorption properties of clouds into account in the radiative transfer modules in order to reduce computational costs. To quantify the biases of excluding LW scattering when clouds exist, we simulated fluxes and heating rates by using satellite data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectrometer (MODIS) merged products (CCCM) in 2010. In annual global average, neglecting LW scattering causes overestimation by 2.6 W/m 2 for the top-of-atmosphere (TOA) upward fluxes and underestimation by 1.2 W/m 2 for surface downward fluxes. In particular, regional extreme biases are approximately 12 W/m 2 for TOA upward fluxes and are approximately -3.6 W/m 2 for surface downward fluxes, or are approximately 5% of the global averaged outgoing longwave radiation (OLR) and 1% of the global averaged surface downward fluxes, respectively. In terms of heating rates, on average, LW scattering heats the whole atmosphere column by 0.0045 K/day, heats the cloud layers by 0.0420 K/day, heats the surface by 0.028 K/day, and cools the tropopause by 0.018 K/day.

58 GEOSCIENCES↗

End-to-end Coronagraphic Modeling Including a Low-order Wavefront Sensor

To evaluate space-based coronagraphic techniques, end-to-end modeling is necessary to simulate realistic fields containing speckles caused by wavefront errors. Real systems will suffer from pointing errors and thermal and motioninduced mechanical stresses that introduce time-variable wavefront aberrations that can reduce the field contrast. A loworder wavefront sensor (LOWFS) is needed to measure these changes at a sufficiently high rate to maintain the contrast level during observations. We implement here a LOWFS and corresponding low-order wavefront control subsystem (LOWFCS) in end-to-end models of a space-based coronagraph. Our goal is to be able to accurately duplicate the effect of the LOWFS+LOWFCS without explicitly evaluating the end-to-end model at numerous time steps.

coronagraphs↗

Modeled Martian subsurface elemental composition measurements with the Probing In situ with Neutron and Gamma ray instrument: Gamma and Neutron Measurements on Mars

Here, the Probing In situ with Neutrons and Gamma rays (PING) instrument is an innovative application of active neutron-induced gamma-ray technology. The objective of PING is to measure the elemental composition of the Martian regolith. As part 2 of a two-part submission, this manuscript presents PING's sensitivities as a function of the Martian regolith depth and PING's uncertainties in the measurements as a function of observation time in passive and active mode. Part 1 of our submission models the associated regolith types. The modeled sensitivities show that in PING's active mode, where both a Pulsed Neutron Generator (PNG) and a Gamma-Ray Spectrometer (GRS) are used, PING can interrogate the material below the rover to about 20 cm due to the penetrating nature of the high-energy neutrons and the resulting secondary gamma rays observed with the GRS. PING is capable of identifying most major and minor rock-forming elements, including H, O, Na, Mn, Mg, Al, Si, P, S, Cl, Cr, K, Ca, Ti, Fe and Th. The modeled uncertainties show that PING's use of a PNG reduces the required observation times by an order of magnitude over a passive operating mode where the PNG is turned off. While the active mode allows for more complete elemental inventories with higher sensitivity, the gamma-ray signatures of some elements are strong enough to detect in passive mode. We show that PING can detect changes in key marker elements and make thermal neutron measurements in about 1 minute that are sensitive to H and Cl.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗