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NASA NTRS1992

Relaxed Arakawa-Schubert - A parameterization of moist convection for general circulation models

A simple implementation of the Arakawa and Schubert (1974) cumulus parameterization is presented. The major simplification made is to 'relax' the state toward equilibrium each time the parameterization is invoked, rather than requiring that the final state be balanced, as in the original Arakawa-Schubert implementation. This relaxed Arakawa-Schubert (RAS) scheme is evaluated in off-line tests using the Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE) Phase III data. The results show that RAS is equivalent to the standard implementation of Arakawa-Schubert but is more economical and simpler to code. RAS also avoids the ill-posed problem that occurs in Arakawa-Schubert as a result of having to solve for a balanced state.

Moorthi, Shrinivas↗

NASA NTRS2009

Uncertain Representations of Sub-Grid Pollutant Transport in Chemistry-Transport Models and Impacts on Long-Range Transport and Global Composition

Sub-grid transport, by convection and turbulence, is known to play an important role in lofting pollutants from their source regions. Consequently, the long-range transport and climatology of simulated atmospheric composition are impacted. This study uses the Goddard Earth Observing System, Version 5 (GEOS-5) atmospheric model to study pollutant transport. The baseline model uses a Relaxed Arakawa-Schubert (RAS) scheme that represents convection through a sequence of linearly entraining cloud plumes characterized by unique detrainment levels. Thermodynamics, moisture and trace gases are transported in the same manner. Various approximate forms of trace-gas transport are implemented, in which the box-averaged cloud mass fluxes from RAS are used with different numerical approaches. Substantial impacts on forward-model simulations of CO (using a linearized chemistry) are evident. In particular, some aspects of simulations using a diffusive form of sub-grid transport bear more resemblance to space-biased CO observations than do the baseline simulations with RAS transport. Implications for transport in the real atmosphere will be discussed. Another issue of importance is that many adjoint/inversion computations use simplified representations of sub-grid transport that may be inconsistent with the forward models: implications will be discussed. Finally, simulations using a complex chemistry model in GEOS-5 (in place of the linearized CO model) are underway: noteworthy results from this simulation will be mentioned.

Pawson, Steven↗

NASA NTRS2013

Inclusion of Linearized Moist Physics in Nasa's Goddard Earth Observing System Data Assimilation Tools

Inclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa-Schubert (RAS) convection scheme has been developed and tested in NASA's Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encountered. Efficient filtering of these profiles is achieved by diagnosis of steep gradients in a reduced version of the operator of the tangent linear model. With filtering turned on, the inclusion of linearized moist physics increases the correlation between the nonlinear perturbation trajectory and the linear approximation of the perturbation trajectory. A month-long observation impact experiment is performed and the effect of including moist physics on the impacts is discussed. Impacts from moist-sensitive instruments and channels are increased. The effect of including moist physics is examined for adjoint sensitivity studies. A case study examining an intensifying Northern Hemisphere Atlantic storm is presented. The results show a significant sensitivity with respect to moisture.

Convection↗

NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to find optimal designs for an interdigitated flushwall injector suitable for scramjet applications at hypervelocity conditions. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. A Latin hypercube sampling design-of-experiments method was used to select design points for RAS. A methodology was developed that automated building geometries and generating grids for each design. The ensuing RAS analysis generated the performance database from which the two objective functions of interest were computed using a one-dimensional performance utility. The data were fitted using four surrogate models: an artificial neural network (ANN) model, a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model obtained an optimal solution set that predicted high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts are required in order to lower the errors and perform more accurate surrogate-based optimization. sed optimization.

Shenoy, Rajiv R.↗

NASA NTRSDate not supplied

The NASA Space Life Sciences Training Program (SLSTP)

The NASA Space Life Sciences Training Program (SLSTP) provides undergraduate students entering their junior or senior years with professional experience in space life science disciplines. This challenging ten-week summer program is hosted by NASA Ames Research Center. The primary goal of the program is to train the next generation of scientists and engineers, enabling NASA to meet future research and development challenges in the space life sciences. SLSTP Research Associates (RAs) work closely with NASA scientists and engineers on cutting-edge research and technology development. In addition to providing hands-on research experience and the ability to present their findings in a professional forum, SLSTP RAs attend technical lectures given by experts on a wide range of topics, tour NASA and other research facilities, participate in leadership and team building exercises, and develop a group project. Historically the SLSTP program has been held at Ames Research Center in Mountain View, California. However, due to the pandemic, both the 2020 and 2021 programs were restructured to be conducted virtually, enabling the program to continue despite the challenging times. For this presentation, we will highlight program processes, student recruitment, accomplishments, goals, and feedback from alumni and mentors since 2013. To date, 92 RAs from 64 different academic institutions in 29 states, 21 staffers, and 37 mentors have participated in the program. The SLSTP is funded by NASA’s Space Biology Program, which is part of the Biological and Physical Sciences Division of NASA. The SLSTP is managed by the Space Biology Project within the Science Directorate at Ames Research Center.

Training Space Biosciences Student↗

NASA NTRSDate not supplied

Assessing Helicopter Pilots’ Detect and Avoid and Collision Avoidance Performance With ACAS Xr

The latest variant of the Federal Aviation Administration’s Airborne Collision Avoidance System (ACAS X) is being designed for both crewed and uncrewed rotorcraft. Referred to as ACAS Xr, the system joins a suite of other ACAS X variants poised to replace the Traffic Alert and Collision Avoidance System (TCAS II). ACAS Xr is tuned to support current-day helicopter platforms as well as electric Vertical Takeoff and Landing (eVTOL) vehicles that are still under development. Given this flexibility, ACAS Xr may be used by helicopter crews currently in operation or by remotely-operated eVTOL aircraft in the emerging Advanced Air Mobility (AAM) market. To cover the range of potential uses, two distinct configurations are being proposed for ACAS Xr: Collision Avoidance System (CAS) and Detect and Avoid (DAA). Under the CAS configuration, ACAS Xr provides minimal caution-level alerting but issues directive warning-level alerting and guidance. The DAA configuration, by contrast, provides caution-level alerting and guidance, in addition to the warning-level alerting and guidance. The current study was performed as part of the National Aeronautics and Space Administration’s AAM project. Six helicopter pilots were recruited to fly a variety of scripted traffic scenarios in a full-motion, crewed eVTOL simulator. Participants flew 60 encounters over two days, reacting to pre-recorded intruder aircraft that were scripted to fly into the participant’s aircraft from different approach angles, relative altitudes, and during different phases of flight. The pilots flew half of the encounters with the CAS configuration and half with the DAA configuration. Within each block of 30 encounters, pilots experienced 10 conflicts while in cruise, 10 in hover, and 10 while on approach to a heliport. Results showed that pilot response times were consistently under 5 seconds for RAs and under 10 seconds for DAA alerts, when present, during all three phases of flight. Unsurprisingly, the DAA configuration was associated with lower rates of en-route and high-severity losses of DAA well clear compared to the CAS configuration in all phases of flight except for the terminal area. Rates of losses of DAA well clear were found to be substantially higher in the Hover scenario, compared to Cruise. Pilots failed to fully comply with RAs at a rate of 0.10-0.18 in all conditions except for the DAA configuration in the Hover scenario, which was associated with a higher non-compliance rate of 0.4 due to Descend RAs issued at low altitudes. The implications of these results with regards to the ongoing development of ACAS Xr is discussed.

air taxis↗

NASA NTRSDate not supplied

Assessing Helicopter Pilots’ Detect and Avoid and Collision Avoidance Performance with ACAS Xr

air taxis↗

DOE OSTI2025

An in vitro BRAF activation assay elucidates molecular mechanisms driving disassembly of the autoinhibited BRAF state

The RAF kinases (ARAF, BRAF, and CRAF) are essential components of the RAS-ERK signaling pathway, which controls vital cellular processes and is frequently dysregulated in human disease. Notably, mutations that alter BRAF function are prominent drivers of human cancer and certain RASopathy disorders, making BRAF an important target for therapeutic intervention. Despite extensive research, several aspects of BRAF regulation remain unclear. In this study, we developed an in vitro BRAF activation assay using purified autoinhibited BRAF:14-3-3 2 :MEK complexes. Our results show that fully processed, active-state KRAS alone can promote dimer-dependent BRAF activation. Moreover, we found that phosphatidylserine (PS)-containing liposomes synergized with KRAS to promote BRAF activation, achieving activity levels comparable to those observed with BRAF proteins that constitutively dimerize. In contrast, the SMP phosphatase complex had only a minimal effect on BRAF catalytic activity in this system but mediated the dephosphorylation of the negative regulatory pS365 14-3-3 binding site in a manner that was accelerated by the presence of KRAS alone or KRAS and 30% PS liposomes. Finally, we show that inhibitors blocking the BRAF RBD:KRAS interaction were able to suppress the in vitro activation of BRAF, underscoring the critical role of RAS binding in initiating the disassembly of the BRAF autoinhibited state. Thus, this assay provides valuable insights into the steps required for BRAF activation and can serve as an effective screening tool for identifying compounds that may inhibit this process and have therapeutic potential.

BRAF↗

DOE OSTI2026

Intercomparison of flood inundation models across land use types and hydrological flood stages

Flood Inundation Mapping (FIM) model selection is a key operational decision because accurate, rapid mapping underpins early warning and resource allocation. FIM performance is context-dependent and can vary with hydrograph phase, land-use/land-cover (LULC), and the evaluation benchmark. Intercomparison studies typically assess a single near-peak snapshot against one reference dataset. Here, we provide a context-stratified intercomparison across (i) multiple hydrograph phases, (ii) LULC classes, and (iii) benchmark types, for five FIM approaches spanning a wide range of physical complexity and operational cost (TRITON, LISFLOOD-FP, HEC-RAS 2D, ARC-Curve2Flood, and OWP HAND-FIM). We use the Hurricane Matthew flood (2016) in the Neuse River Basin, North Carolina, USA, as a case study. Using high-resolution remote sensing-derived flood inundation maps, hand-labeled points, and building footprints, we assess model skill across two rising and two falling hydrograph limbs and across major LULC types. Results show that model rankings shift systematically across contexts: LISFLOOD-FP ranks highest in three of four flood phases, while TRITON leads during one rising limb phase; LISFLOOD-FP performs best in vegetated areas, whereas HEC-RAS improves relative performance in agricultural and urban areas; and benchmark choice influences conclusions, with LISFLOOD-FP performing best for flooded-building detection in the late falling limb, while TRITON ranks highest against hand-labeled points. We also report representative wall-clock runtimes for each workflow to provide use-case context for operational feasibility. Together, these results offer transferable guidance for model selection and for designing large-scale, benchmark-aware FIM intercomparison studies.

Nikrou, Parvaneh [University of Alabama]↗

DOE OSTI2024

Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques⋆

Modeling large datasets through Multivariate Functional Approximations (MFA) provide an elegant way to handle many visualization and scientific analysis workflows. The process necessitates scalable data partitioning methods to compute MFA representations efficiently without compromising the accuracy or continuity of the reconstructed solution. We propose a domain -decomposed method for computing the MFA with B -spline bases, which reduces the total work per task and uses a restricted Additive Schwarz (RAS) method to converge the control point data degrees -of -freedom along subdomain boundaries. We provide an in-depth analysis of the parallel approach with domain decomposition solvers, aiming to minimize local subdomain error residuals and recover high -order continuity at subdomain interfaces with appropriate choices of knot overlaps. The communication cost, determined by the overlap regions in the RAS implementation, is optimized to recover the numerical error profile of the single subdomain case. Our proposed method stands in contrast to previous methods, which typically only recover either C 0 or at best C 1 continuity for arbitrary B -spline degree expansions, or those that require post -processing to blend discontinuities in the reconstructed data. We demonstrate the effectiveness of our approach using analytical and real -world datasets in 1D, 2D, and 3D through both strong and weak scaling studies. The performance results indicate that the overall cost of computing the approximation is directly proportional to the underlying nearest -neighbor communication implementation, and is only weakly dependent on the overlap region size that determines the size of the messages. This finding underscores the efficiency and scalability of our proposed method, making it a promising solution for handling large datasets in scientific workflows.

additive Schwarz solvers↗

DOE OSTI2025

Computation of Auger Electron Spectra in Organic Molecules with Multiconfiguration Pair-Density Functional Theory

Efficient and accurate computation of molecular Auger electron spectra for larger systems is limited by the rapid increase in the number of doubly ionized final states as the system size grows. Here, in this work, we benchmark the application of multiconfiguration pair-density functional theory with a restricted active space (RAS) reference wave function for computing the carbon K-edge decay spectra of 20 organic molecules. Decay rates are computed within the one-center approximation. We evaluate the performance of different basis sets and on-top functionals and find that multiconfiguration pair-density functional theory achieves accuracy comparable to RAS followed by second-order perturbation theory, but at significantly lower computational cost.

Fouda, Adam E. A. [Argonne National Laboratory (AN↗

DOE OSTI2025

Integrating Ultra-Coarse-Grained Protein Models into Accessible Workflows for Multiscale Molecular Dynamics

To capture protein conformational transitions using molecular dynamics (MD), several simulation resolutions covering different spatial and temporal scales are typically needed. All-atom (AA) simulations provide fine resolution, but are computationally infeasible for large systems over longer durations. Coarse-grained (CG) and ultra-coarse-grained (UCG) models have a lower resolution and computational cost while still being able to conserve essential protein features. Prior work on a Multiscale Machinelearned Modeling Infrastructure (MuMMI) combined both AA and CG simulations to study RAS-RAF protein interactions, leveraging CG models for longer time scales and using AA to investigate unusual conformations in greater detail. However, MuMMI is still resource-intensive, and this study aims to maximize exploration of the protein conformational space while reducing computational cost. In this paper, we build on prior work that integrates UCG models based on heterogeneous elastic network modeling (hENM) into the MuMMI workflow. We demonstrate that UCG models enable accurate sampling of protein conformations, focusing on simulating RAS-RAF protein interactions. Using higher-resolution CG Martini simulation data, we can automatically refine intramolecular interactions in UCG models. We present a scalable Python package that uses fluctuations observed in higher-resolution CG Martini simulations to estimate bond coefficients of the UCG model. We built novel machine learning-based backmapping methods to recover more detailed CG Martini structures from UCG structures, using diffusion models to learn the mapping between scales. Finally, we present UCG-mini-MuMMI, an accessible and less compute-intensive version of MuMMI as a resource for the scientific community. Incorporating UCG models into MD studies is applicable to a broad range of systems and proteins, and our study offers insights into the advantages and limitations of these methods.

Chemical structure↗

DOE OSTI2025

Blocking C-terminal processing of KRAS4b via a direct covalent attack on the CaaX-box cysteine

RAS is the most frequently mutated oncogene in cancer. RAS proteins show high sequence similarities in their G-domains but are significantly different in their C-terminal hypervariable regions (HVR). These regions interact with the cell membrane via lipid anchors that result from posttranslational modifications (PTM) of cysteine residues. KRAS4b is unique as it has only one cysteine that undergoes PTM, C185. Small molecule covalent modification of C185 would block any form of prenylation and subsequently inhibit attachment of KRAS4b to the cell membrane, blocking its biological activity. We translated this concept to the discovery and development of disulfide tethering screen hits into irreversible covalent modifiers of C185. These compounds inhibited proliferation of KRAS4b-driven mouse embryonic fibroblasts, but not cells driven by N-myristoylated KRAS4b that harbor a C185S mutation and are not dependent on C185 prenylation. Top–down proteomics was used to confirm target engagement in cells. These compounds bind in a pocket formed when the HVR folds back between helix 3 and 4 in the G-domain (HVR-α3-α4). This interaction can happen in the absence of small molecules as predicted by molecular dynamics simulations and is stabilized in the presence of C185 binders as confirmed by small-angle X-ray scattering and solution NMR. NOESY-HSQC, an NMR approach that measures internuclear distances of 6 Å or less, and structure analysis identified the critical residues and interactions that define the HVR-α3-α4 pocket. Further development of compounds that bind to this pocket could be the basis of a new approach to targeting KRAS cancers.

C185↗

DOE OSTI2026

A critical review on additive manufacturing of refractory alloys from a data analytics perspective- beyond nickel-based superalloys

Refractory alloys (RAs) are promising materials due to their exceptional physicochemical properties, but most research remains at the laboratory scale. For broader adoption, advancements in manufacturing are essential. Because their high stability makes conventional methods like machining and casting difficult, additive manufacturing (AM) is emerging as an effective approach for fabricating refractory alloy components. However, AM's repeated non-equilibrium thermal cycles introduce undesired features (e.g. defects, anisotropic microstructures, and residual stresses), which are magnified due to RAs’ unique properties. This paper comprehensively reviews the state-of-the-art methods of AM for refractory alloys. It explores data analytics techniques to establish design rules based on multi-fidelity experimental and computational methods. Furthermore, it investigates integrated, collaborative efforts to harmonise standalone databases, information, knowledge, and predictive models at multi-physics, multi-stage, and multi-scale. Unlike the existing literature that focuses primarily on material systems or process fundamentals, this work provides an integrated perspective on AM of refractory alloys from a data analytics standpoint, highlighting the roles of integrated computational materials engineering (ICME), verification, validation, and uncertainty quantification (VV&UQ), and digital twin-driven qualification in overcoming data scarcity and accelerating rapid qualification.

Additive manufacturing↗

NASA NTRS1991

Tactile discrimination and representations of texture, shape, and softness

We present here some of the salient results on the tactual discriminabilities of human subjects obtained through psychophysical experiments, and the associated peripheral neural codes obtained through electrophysiological recordings from monkey single nerve fibers. Humans can detect the presence of a 2 micron high single dot on a smooth glass plate stroked on the skin, based on the responses of Meissner type rapidly adapting fibers (RAs). They can also detect a 0.06 micron high grating on the plate, owing to the response of Pacinian corpuscle fibers. Among all the possible representations of the shapes of objects, the surface curvature distribution seems to be the most relevant for tactile sensing. Slowly adapting fibers respond to both the change and rate of change of curvature of the skin surface at the most sensitive spot in their receptive fields, whereas RAs respond only to the rate of change of curvature. Human discriminability of compliance of objects depends on whether the object has a deformable or rigid surface. When the surface is deformable, the spatial pressure distribution within the contact region is dependent on object compliance, and hence information from cutaneous mechanoreceptors is sufficient for discrimination of subtle differences in compliance. When the surface is rigid, kinesthetic information is necessary for discrimination, and the discriminability is much poorer than that for objects with deformable surfaces.

Srinivasan, M. A.↗

NASA NTRS2004

Tropical Diabatic Heating and the Role of Convective Processes as Represented in Several Contemporary Climate Models

One of the most fundamental properties of the global heat balance is the net heat input into the tropical atmosphere that helps drive the planetary atmospheric circulation. Although broadly understood in terms of its gross structure and balance of source / sink terms, incorporation of the relevant processes in predictive models is still rather poor. The work reported here examines the tropical radiative and water cycle behavior as produced by four contemporary climate models. Among these are the NSIPP-2 (NASA Seasonal to Interannual Prediction Project) which uses the RAS convective parameterization; the FVCCM, a code using finite volume numerics and the CCM3.6 physics; FVCCM-MCRAS again having the finite volume numerics, but MCRAS convective parameterization and a different radiation treatment; and, finally, the NCEP GSM which uses the RAS. Using multi-decadal integrations with specified SSTs we examine the statistics of radiative / convective processes and associated energy transports, and then estimate model energy flux sensitivities to SST changes. In particular the behavior of the convective parameterizations is investigated. Additional model integrations are performed specifically to assess the importance representing convective inhibition in regulating convective cloud-top structure and moisture detrainment as well as controlling surface energy fluxes. To evaluate the results of these experiments, a number of satellite retrievals are used: TRMM retrievals of vertical reflectivity structure, rainfall rate, and inferred diabatic heating are analyzed to show both seasonal and interannual variations in vertical structure of latent heat release. Top-of-atmosphere radiative fluxes from ERBS and CERES are used to examine shortwave and longwave cloud forcing and to deduce required seasonal energy transports. Retrievals of cloud properties from ISCCP and water vapor variations from SSM/T-2 are also used to understand behavior of the humidity fields. These observations are supplemented with output form the DOE Reanalysis-2.

Robertson, Franklin R.↗

NASA NTRS1997

Three-dimensional culture of a mixed mullerian tumor of the ovary: expression of in vivo characteristics

The Rotating-Wall Vessel (RWV) is a novel in vitro cell culture system used to successfully culture a cell line derived from a heterologous mixed mullerian tumor cell of the ovary. Although the original tumor was comprised of both epithelial and mesodermal components, long-term culture in conventional flasks established a cell line from this tumor with homogeneous epitheliallike growth characteristics (1). Cells from Passage 36 were seeded into a Rotating-Wall Vessel containing Cytodex-3 microcarrier beads. Scanning electron micrographs of tumor cells cultured for 32 d in the RWV showed the presence of heterogeneous cell populations organized into three-dimensional tissuelike architecture. Immunocytochemical analysis confirmed the cellular heterogeneity, as demonstrated by expression of both epithelial and mesenchymal antigens. Reverse transcription polymerase chain reaction amplification demonstrated the presence of mRNA for cellular oncogenes HER-2/neu, H-ras, K-ras, and tumor suppressor p53. Thus, there are two advantages to propagation of tissue in the RWV culture system:(a) tissue diversification representing populations present in the original tumor, and (b) the three-dimensional freedom to organize tissues morphologically akin to those observed in vivo. These data indicate that the RWV culture system is suitable for generating large quantities of ovarian tumor cells in vitro that are amenable to immunocytochemical, oncogenic, morphologic characteristics demonstrated in vivo.

Mixed Tumor, Mullerian/ultrastructure↗

NASA NTRS2004

Modeled Microgravity Disrupts Collagen I/Integrin Signaling During Osteoblastic Differentiation of Human Mesenchymal Stem Cells

Spaceflight leads to reduced bone mineral density in weight bearing bones that is primarily attributed to a reduction in bone formation. We have previously demonstrated severely reduced osteoblastogenesis of human mesenchymal stem cells (hMSC) following seven days culture in modeled microgravity. One potential mechanism for reduced osteoblastic differentiation is disruption of type I collagen-integrin interactions and reduced integrin signaling. Integrins are heterodimeric transmembrane receptors that bind extracellular matrix proteins and produce signals essential for proper cellular function, survival, and differentiation. Therefore, we investigated the effects of modeled microgravity on integrin expression and function in hMSC. We demonstrate that seven days of culture in modeled microgravity leads to reduced expression of the extracellular matrix protein, type I collagen (Col I). Conversely, modeled microgravity consistently increases Col I-specific alpha2 and beta1 integrin protein expression. Despite this increase in integrin sub-unit expression, autophosphorylation of adhesion-dependent kinases, focal adhesion kinase (FAK) and proline-rich tyrosine kinase 2 (PYK2), is significantly reduced. Activation of Akt is unaffected by the reduction in FAK activation. However, reduced downstream signaling via the Ras-MAPK pathway is evidenced by a reduction in Ras and ERK activation. Taken together, our findings indicate that modeled microgravity decreases integrin/MAPK signaling, which likely contributes to the observed reduction in osteoblastogenesis.

Meyers, Valerie E.↗