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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Decadal variability of the Tropical Atlantic Ocean Surface Temperature in shipboard measurements and in a Global Ocean-Atmosphere model

Sea surface temperature (SST) variability was investigated in a 200-yr integration of a global model of the coupled oceanic and atmospheric general circulations developed at the Geophysical Fluid Dynamics Laboratory (GFDL). The second 100 yr of SST in the coupled model's tropical Atlantic region were analyzed with a variety of techniques. Analyses of SST time series, averaged over approximately the same subregions as the Global Ocean Surface Temperature Atlas (GOSTA) time series, showed that the GFDL SST anomalies also undergo pronounced quasi-oscillatory decadal and multidecadal variability but at somewhat shorter timescales than the GOSTA SST anomalies. Further analyses of the horizontal structures of the decadal timescale variability in the GFDL coupled model showed the existence of two types of variability in general agreement with results of the GOSTA SST time series analyses. One type, characterized by timescales between 8 and 11 yr, has high spatial coherence within each hemisphere but not between the two hemispheres of the tropical Atlantic. A second type, characterized by timescales between 12 and 20 yr, has high spatial coherence between the two hemispheres. The second type of variability is considerably weaker than the first. As in the GOSTA time series, the multidecadal variability in the GFDL SST time series has approximately opposite phases between the tropical North and South Atlantic Oceans. Empirical orthogonal function analyses of the tropical Atlantic SST anomalies revealed a north-south bipolar pattern as the dominant pattern of decadal variability. It is suggested that the bipolar pattern can be interpreted as decadal variability of the interhemispheric gradient of SST anomalies. The decadal and multidecadal timescale variability of the tropical Atlantic SST, both in the actual and in the GFDL model, stands out significantly above the background 'red noise' and is coherent within each of the time series, suggesting that specific sets of processes may be responsible for the choice of the decadal and multidecadal timescales. Finally, it must be emphasized that the GFDL coupled ocean-atmosphere model generates the decadal and multidecadal timescale variability without any externally applied force, solar or lunar, at those timescales.

Mehta, Vikram M.↗
NASA NTRS2016

Wilson Corners SWMU 001 2015 Annual Long Term Monitoring Report Kennedy Space Center, Florida

This document presents the findings of the 2015 Long Term Monitoring (LTM) that was completed at the Wilson Corners site, located at the National Aeronautics and Space Administration John F. Kennedy Space Center, Florida. The objectives of the 2015 LTM event were to evaluate the groundwater flow direction and gradient, to monitor the vertical and horizontal extent of the volatile organic compounds (VOCs; including the upgradient and sidegradient extents, which are monitored every five years), and to monitor select locations internal to the dissolved groundwater plume. The 2015 LTM event included several upgradient and sidegradient monitoring wells that are not sampled annually to verify the extent of VOCs in this portion of the site. The December 2015 LTM groundwater sampling event included, depth to groundwater measurements, 40 VOC samples collected using passive diffusion bags, and one VOC sample collected using low-flow techniques. Additionally, monitoring well MW0052DD was overdrilled and abandoned using rotasonic drilling techniques. The following conclusions can be made based on the 2015 LTM results: groundwater flow is generally to the west with northwest and southwest flow components from the water table to approximately 55 feet below land surface (ft BLS); peripheral monitoring wells generally delineate VOCs to groundwater cleanup target levels (GCTLs) except for monitoring wells MW0088, MW0090, MW0095, and NPSHMW0039, which had vinyl chloride (VC) concentrations near the GCTL and MW0062, which had trichloroethene (TCE), cis-1,2-dichloroethenen (cDCE), and VC concentrations above natural attenuation default concentrations (NADCs); VOCs in interior downgradient wells generally fluctuate within historic ranges except for monitoring wells in the north-northwest portion of the site, which have increasing VC concentrations indicating potential plume migration and expansion; Historically, the vertical extents of the VOCs were delineated by monitoring wells screened greater than 60 ft BLS (MW0083 through MW0086, and MW0078). The 2015 LTM results indicate that concentrations of daughter product cDCE is greater than the NADC in MW0078 and that cDCE and VC are greater than NADCs in MW0130. TCE was greater than the GCTL in monitoring well MW130 and not detected above method detection limits (9 micrograms per Liter) in monitoring well MW0078. No GCTL exceedances were identified in monitoring wells MW0083 or MW0086; the dissolved plume footprint appears generally stable, though not fully delineated by monitoring well data in the northeast portion of the site; and 2015 LTM results generally support the existing Conceptual Site Model. Geosyntec recommends modifying the LTM program, collecting a verification sample from monitoring well MW0062, and performing a direct push technology instigation in the northnortheastern portion of the site. A cluster of monitoring wells (MW0132 [2 to 12 ft BLS], MW0133 [15 to 25 ft BLS], and MW0134 [29 to 34 ft BLS]) is proposed to delineate impacts in the northnortheast portion of the site. Geosyntec recommends installation of a vertical extent well in the center of the site (Hot Spot 2 area) post-remediation implementation.

groundwater↗
DOE OSTI2020

Hydrometeor Shape Variability in Snowfall as Retrieved from Polarimetric Radar Measurements

A polarimetric radar–based method for retrieving atmospheric ice particle shapes is applied to snowfall measurements by a scanning Ka-band radar deployed at Oliktok Point, Alaska (70.495°N, 149.883°W). The mean aspect ratio, which is defined by the hydrometeor minor-to-major dimension ratio for a spheroidal particle model, is retrieved as a particle shape parameter. The radar variables used for aspect ratio profile retrievals include reflectivity, differential reflectivity, and the copolar correlation coefficient. The retrievals indicate that hydrometeors with mean aspect ratios below 0.2–0.3 are usually present in regions with air temperatures warmer than approximately from –17° to –15°C, corresponding to a regime that has been shown to be favorable for growth of pristine ice crystals of planar habits. Radar reflectivities corresponding to the lowest mean aspect ratios are generally between –10 and 10 dBZ. For colder temperatures, mean aspect ratios are typically in a range between 0.3 and 0.8. There is a tendency for hydrometeor aspect ratios to increase as particles transition from altitudes in the temperature range from –17° to –15°C toward the ground. Furthermore, this increase is believed to result from aggregation and riming processes that cause particles to become more spherical and is associated with areas demonstrating differential reflectivity decreases with increasing reflectivity. Aspect ratio retrievals at the lowest altitudes are consistent with in situ measurements obtained using a surface-based multiangle snowflake camera. Pronounced gradients in particle aspect ratio profiles are observed at altitudes at which there is a change in the dominant hydrometeor species, as inferred by spectral measurements from a vertically pointing Doppler radar.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

ABINIT: Overview and focus on selected capabilities

ABINIT is probably the first electronic-structure package to have been released under an open-source license about 20 years ago. It implements density functional theory, density-functional perturbation theory (DFPT), many-body perturbation theory (GW approximation and Bethe–Salpeter equation), and more specific or advanced formalisms, such as dynamical mean-field theory (DMFT) and the “temperature-dependent effective potential” approach for anharmonic effects. Relying on planewaves for the representation of wavefunctions, density, and other space-dependent quantities, with pseudopotentials or projector-augmented waves (PAWs), it is well suited for the study of periodic materials, although nanostructures and molecules can be treated with the supercell technique. The present article starts with a brief description of the project, a summary of the theories upon which ABINIT relies, and a list of the associated capabilities. It then focuses on selected capabilities that might not be present in the majority of electronic structure packages either among planewave codes or, in general, treatment of strongly correlated materials using DMFT; materials under finite electric fields; properties at nuclei (electric field gradient, Mössbauer shifts, and orbital magnetization); positron annihilation; Raman intensities and electro-optic effect; and DFPT calculations of response to strain perturbation (elastic constants and piezoelectricity), spatial dispersion (flexoelectricity), electronic mobility, temperature dependence of the gap, and spin-magnetic-field perturbation. The ABINIT DFPT implementation is very general, including systems with van der Waals interaction or with noncollinear magnetism. Community projects are also described: generation of pseudopotential and PAW datasets, high-throughput calculations (databases of phonon band structure, second-harmonic generation, and GW computations of bandgaps), and the library libpaw. ABINIT has strong links with many other software projects that are briefly mentioned.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Automated Finite Element Modeling of Wing Structures for Shape Optimization

The displacement formulation of the finite element method is the most general and most widely used technique for structural analysis of airplane configurations. Modem structural synthesis techniques based on the finite element method have reached a certain maturity in recent years, and large airplane structures can now be optimized with respect to sizing type design variables for many load cases subject to a rich variety of constraints including stress, buckling, frequency, stiffness and aeroelastic constraints (Refs. 1-3). These structural synthesis capabilities use gradient based nonlinear programming techniques to search for improved designs. For these techniques to be practical a major improvement was required in computational cost of finite element analyses (needed repeatedly in the optimization process). Thus, associated with the progress in structural optimization, a new perspective of structural analysis has emerged, namely, structural analysis specialized for design optimization application, or.what is known as "design oriented structural analysis" (Ref. 4). This discipline includes approximation concepts and methods for obtaining behavior sensitivity information (Ref. 1), all needed to make the optimization of large structural systems (modeled by thousands of degrees of freedom and thousands of design variables) practical and cost effective.

Harvey, Michael Stephen↗
DOE OSTI2022

The radial phase variation of reversed-shear and toroidicity-induced Alfvén eigenmodes in DIII-D

The eigenfunction of an instability contains information about energy flow in the wave. Here, the amplitude and phase of electron cyclotron emission radiometer data from hundreds of DIII-D reversed shear Alfvén eigenmodes (RSAE) and toroidicity-induced Alfvén eigenmodes (TAE) are analyzed along the outboard horizontal midplane. The radial phase profile can be flat, linearly rising or falling, convex or concave; in other words, a wide variety of shapes is observed. For a particular mode, often the radial phase profile remains approximately constant as the mode evolves in time but sometimes it changes rapidly. Many TAEs and some RSAEs have phase profiles that are rather flat where the mode amplitude is largest but rise steadily by ~2π at large major radius. Rapid phase changes are observed when the frequencies of an RSAE and TAE overlap and the modes couple. The phase profile depends weakly on the fast-ion gradient that would appear in the absence of wave-induced transport. Linear and quadratic fits to the phase profiles, together with many plasma parameters, are assembled into RSAE and TAE databases. In both cases, large variability is observed. For RSAEs, the strongest phase dependencies are on electron temperature T e , RSAE mode frequency, and the density of carbon impurities. For TAEs, the strongest dependencies are on beam power and major radius of the mode. In general, the average RSAE radial phase profile is essentially flat but the TAE profile has non-zero slope and curvature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE↗
NASA NTRS1982

Regional applicability and potential of salt-gradient solar ponds in the United States. Volume 2: Detailed report

A comprehensive assessment of the regional applicability and potential of salt-gradient solar ponds in the United States is provided. The assessment is focused on the general characteristics of twelve defined geographic regions. Natural resources essential to solar ponds are surveyed. Meteorological and hydrogeological conditions affecting pond performance are examined. Potentially favorable pond sites are identified. Regional thermal and electrical energy output from solar ponds is calculated. Selected pond design cases are studied. Five major potential market sectors are evaluated in terms of technical and energy-consumption characteristics, and solar-pond applicability and potential. Relevant pond system data and financial factors are analyzed. Solar-pond energy costs are compared with conventional energy costs. The assessment concludes that, excepting Alaska, ponds are applicable in all regions for at least two market sectors. Total solar pond energy supply potential in the five market sectors examined is estimated to be 8.94 quads/yr by the year 2000, approximately 7.2% of the projected total national energy demand.

Lin, E. I. H.↗
DOE OSTI2025

Leveraging operator learning to accelerate convergence of the preconditioned conjugate gradient method

We propose a new deflation strategy to accelerate the convergence of the preconditioned conjugate gradient (PCG) method for solving parametric large-scale linear systems of equations. Unlike traditional deflation techniques that rely on eigenvector approximations or recycled Krylov subspaces, we generate the deflation subspaces using operator learning, specifically the Deep Operator Network (DeepONet). To this aim, we introduce two complementary approaches for assembling the deflation operators. The first approach approximates near-null space vectors of the discrete PDE operator using the basis functions learned by the DeepONet. The second approach directly leverages solutions predicted by the DeepONet. To further enhance convergence, we also propose several strategies for prescribing the sparsity pattern of the deflation operator. Here, a comprehensive set of numerical experiments encompassing steady-state, time-dependent, scalar, and vector-valued problems posed on both structured and unstructured geometries is presented and demonstrates the effectiveness of the proposed DeepONet-based deflated PCG method, as well as its generalization across a wide range of model parameters and problem resolutions.

Deflation↗
DOE OSTI2021

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions

Here we propose a new type of neural networks, Kronecker neural networks (KNNs), that form a general framework for neural networks with adaptive activation functions. KNNs employ the Kronecker product, which provides an efficient way of constructing a very wide network while keeping the number of parameters low. Our theoretical analysis reveals that under suitable conditions, KNNs induce a faster decay of the loss than that by the feed-forward networks. This is also empirically verified through a set of computational examples. Furthermore, under certain technical assumptions, we establish global convergence of gradient descent for KNNs. As a specific case, we propose the Rowdy activation function that is designed to get rid of any saturation region by injecting sinusoidal fluctuations, which include trainable parameters. The proposed Rowdy activation function can be employed in any neural network architecture like feed-forward neural networks, Recurrent neural networks, Convolutional neural networks etc. The effectiveness of KNNs with Rowdy activation is demonstrated through various computational experiments including function approximation using feed-forward neural networks, solution inference of partial differential equations using the physics-informed neural networks, and standard deep learning benchmark problems using convolutional and fully-connected neural networks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1953

Investigation at supersonic speeds of the variation with Reynolds number and Mach number of the total, base, and skin-friction drag of seven boattail bodies of revolution designed for minimum wave drag

An investigation has been conducted in the Langley 9-inch supersonic tunnel to determine the effect of the variation with Reynolds number and Mach number of the total, base, and skin-friction drag at zero lift of seven boattail bodies of revolution designed for minimum wave drag according to NACA TN 2550. The tests covered a Reynolds number range from approximately 1.0 x 10(6) to 10.0 x 10(6) at Mach numbers of 1.62, 1.93, and 2.41, respectively. The results show that base drag and, in general, the total drag increase with increasing values of the ratio of base area to maximum area B/S(sub max), although the results reported in NACA TN 3054 showed that the wave drag decreased with increasing values of B/S(sub max). The laminar skin-friction drag is in agreement with the theoretical predictions used, and, within the Mach number range of these tests, the simple Blasius incompressible theory gives a satisfactory prediction. Except for values of B/S (sub max) near 1, the Reynolds number of transition increases with increasing Mach number and as this ratio approaches 1 this variation is seen to reverse. These variations in Reynolds number of transition with Mach number appear to be associated with the changes in pressure gradient over the rear of the bodies.

Bromm, August F , Jr↗
NASA NTRS2008

Duration of a Magma Ocean and Subsequent Mantle Overturn in Mars: Evidence from Nakhlites

It is now generally accepted that the heat produced by accretion, short-lived radioactive elements such as Al-26, and gravitational energy from core formation was sufficient to at least partially melt the silicate portions of terrestrial planets resulting in a global-scale magma ocean. More particularly, in Mars, the geochemical signatures displayed by shergottites, are likely inherited from the crystallization of this magma ocean. Using the short-lived chronometer Sm-146 - Nd-142 (t(sup 1/2) = 103 Myr), the duration of the Martian magma ocean (MMO) has been evaluated to being less than 40 Myr, while recent and more precise ND-142/ND-144 data were used to evaluate the longevity of the MMO to approximately 100 Myr after the solar system formation. In addition, it has been proposed that the end of the crystallization of the MMO may have triggered a mantle overturn, as a result of a density gradient in the cumulate layers crystallized at different levels. Dating the mantle overturn could hence provide additional constraint on the duration of the MMO. Among SNC meteorites, nakhlites are characterized by high epsilon W-182 of approximately +3 and an epsilon Nd-142 similar to depleted shergottites of +0.6-0.9. It has hence been proposed that the source of nakhlites was established very early in Mars history (approximately 8-10 Myr). However, the times recorded in HF-182-W-182 isotope system, i.e. when 182Hf became effectively extinct (approximately 50 Myr after solar system formation) are less than closure times recorded in the Sm-146-Nd-142 isotope system (with a full coverage of approximately 500 Myr after solar system formation). This could result in decoupling between the present-day measured epsilon W-182 and epsilon Nd-142 as the SM-146 may have recorded later differentiation events in epsilon ND-142 not observed in epsilon W-182 values. With these potential complexities in short-lived chronological data for SNC's in mind, new Hf-176/Hf-177, Nd-143/Nd-144 and Nd-142/Nd-144 were obtained for three nakhlites (Nakhla, MIL03346 and Yamato000593). These new data are combined with previous epsilon W-182 data, to investigate potential discrepancies between the Hf-182-W-182 and Sm-146-Nd-142 systematics, and the relationship between the source of nakhlites and a crystallizing magma ocean

Debaille, V.↗
DOE OSTI2024

Techno-economic feasibility of geothermal energy production using inactive oil and gas wells for district heating and cooling systems in Tuttle, Oklahoma

Oil and gas wells have been drilled in the United States and often encounter hot co-produced water possibly suitable for geothermal direct-use applications. Here this study evaluated geothermal resources, heating and cooling demand, and techno-economic potential of four oil and gas wells repurposed for geothermal energy production to serve two public schools and 250 nearby houses in Tuttle, Oklahoma, USA. Subsurface geology in the study area primarily consists of Permian to Mississippian sandstone and limestone formations approximately from 2 km to 3.5 km depth. With a geothermal gradient of 25.3 °C/km, the temperature of geothermal energy production was estimated as 68.2 °C at 2.1 km. The potential of calcite scaling within boreholes and pipes was minimal. Using the characterized reservoir properties, techno-economic analyses were conducted for evaluating levelized costs of geothermal energy production for direct-use heating and cooling and district heating systems with five different production scenarios. Heating and cooling demand in two schools and 250 houses and additional 0.3 MW and 0.6 MW base heating loads for potential geothermal direct-use applications in the study area were also incorporated in the modeling. Results indicated that the levelized cost of heating of geothermal district heating systems utilizing existing wells were significantly lower than those of conventional geothermal energy systems that include well drillings. The geothermal energy production with doublet and quartet configurations was generally sufficient to supply total annual heating demand in the district, while a peaking boiler was used to supply peak loads. Doublet configurations showed higher production temperature with a lower thermal drawdown than the quartet configurations. The doublet system at 2.1 km production depth with 9.3 kg/s flow rate represented the optimal levelized cost of $71/MWh and 91.2% utilization factor. These results imply that the Tuttle geothermal district heating system is techno-economically feasible and comparable to geothermal district heating systems in the United States and the regional natural gas rate for residentials by recycling inactive oil and gas wells with no drillings.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Fully variational incremental CASSCF

We report the complete-active-space self-consistent field (CASSCF) method is a canonical electronic structure theory that holds a central place in conceptualizing and practicing first principles simulations. For application to realistic molecules, however, the CASSCF must be approximated to circumvent its exponentially scaling computational costs. Applying the many-body expansion - also known as the method of increments - to CASSCF (iCASSCF) has been shown to produce a polynomially scaling method that retains much of the accuracy of the parent theory and is capable of treating full valence active spaces. Due to an approximation made in the orbital gradient, the orbital parameters of the original iCASSCF formulation could not be variationally optimized, which limited the accuracy of its nuclear gradient. Herein, a variational iCASSCF is introduced and implemented, where all parameters are fully optimized during energy minimization. This method is able to recover electronic correlations from the full valence space in large systems, produce accurate gradients, and optimize stable geometries as well as transition states. Demonstrations on challenging test cases, such as the oxoMn(salen)Cl complex with 84 electrons in 84 orbitals and the automerization of cyclobutadiene, show that the fully variational iCASSCF is a powerful tool for describing challenging molecular chemistries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable Projection

Deep neural networks (DNNs) have achieved state-of-the-art performance across a variety of traditional machine learning tasks, e.g., speech recognition, image classification, and segmentation. The ability of DNNs to efficiently approximate high-dimensional functions has also motivated their use in scientific applications, e.g., to solve partial differential equations and to generate surrogate models. In this paper, we consider the supervised training of DNNs, which arises in many of the above applications. We focus on the central problem of optimizing the weights of the given DNN such that it accurately approximates the relation between observed input and target data. Devising effective solvers for this optimization problem is notoriously challenging due to the large number of weights, nonconvexity, data sparsity, and nontrivial choice of hyperparameters. To solve the optimization problem more efficiently, we propose the use of variable projection (VarPro), a method originally designed for separable nonlinear least-squares problems. Our main contribution is the Gauss--Newton VarPro method (GNvpro) that extends the reach of the VarPro idea to nonquadratic objective functions, most notably cross-entropy loss functions arising in classification. These extensions make GNvpro applicable to all training problems that involve a DNN whose last layer is an affine mapping, which is common in many state-of-the-art architectures. In our four numerical experiments from surrogate modeling, segmentation, and classification, GNvpro solves the optimization problem more efficiently than commonly used stochastic gradient descent (SGD) schemes. Finally, GNvpro finds solutions that generalize well, and in all but one example better than well-tuned SGD methods, to unseen data points.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Rain-Induced Stratification of the Equatorial Indian Ocean and Its Potential Feedback to the Atmosphere

Surface freshening through precipitation can act to stably stratify the upper ocean, forming a rain layer (RL). RLs inhibit subsurface vertical mixing, isolating deeper ocean layers from the atmosphere. This process has been studied using observations and idealized simulations. The present ocean modeling study builds upon this body of work by incorporating spatially resolved and realistic atmospheric forcing. Fine-scale observations of the upper ocean collected during the Dynamics of the Madden-Julian Oscillation field campaign are used to verify the General Ocean Turbulence Model (GOTM). Spatiotemporal characteristics of equatorial Indian Ocean RLs are then investigated by forcing a 2D array of GOTM columns with realistic and well-resolved output from an existing regional atmospheric simulation. RL influence on the ocean-atmosphere system is evaluated through analysis of RL-induced modification to surface fluxes and sea surface temperature (SST). This analysis demonstrates that RLs cool the ocean surface on time scales longer than the associated precipitation event. A second simulation with identical atmospheric forcing to that in the first, but with rainfall set to zero, is performed to investigate the role of rain temperature and salinity stratification in maintaining cold SST anomalies within RLs. Approximately one third, or 0.1°C, of the SST reduction within RLs can be attributed to rain effects, while the remainder is attributed to changes in atmospheric temperature and humidity. The prolonged RL-induced SST anomalies enhance SST gradients that have been shown to favor the initiation of atmospheric convection. These findings encourage continued research of RL feedbacks to the atmosphere.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Impacts of Varying Concentrations of Cloud Condensation Nuclei On Deep Convective Cloud Updrafts – A Multimodel Assessment

This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations amongst seven, state-of-the-art, cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced, updraft changes. The models show several consistent trends. In general, the changes between the High- CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5-15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~-5-0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone.

deep convective cloud updrafts↗
NASA NTRS1990

Analysis and design of sidestick controller systems for general aviation aircraft

A method to design sidestick controllers for general aviation aircraft with reversible flight controls is proposed. The use of a sidestick in this type of flight vehicle generally increases the stick forces required for maneuvering; this is due to a reduction in the moment arm of application of the force. In the present study, the reduction of stick forces is achieved by incorporating geared tabs in the control-surface design. A complete analysis using the rigid-body aircraft longitudinal equations of motion and stick-force equation in coupled form is carried out. Lateral stick forces are predicted by solving the single-degree-of-freedom roll approximation and aileron stick-force equations. Data are presented for configurations with various tab areas and a wide range of gearing ratios. The results indicate that the method can be used successfully for geared-tab design and stick-force prediction. It is shown that gearing-ratio selection is critical but that tab area does not have a significant impact on the magnitude of stick forces and stick force to stick deflection gradients.

Martin, Daniel M.↗