Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Computational Margin”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

EvoNet: A phylogenomic and systems biology approach to identify genes underlying plant survival in marginal, low‐N soils

The DOE‐BER “EvoNet” project investigates the genetic and molecular basis of plant resilience in extreme environments. We do this by identifying key genes that enable “extreme survivor” species to thrive in the nitrogen-poor soils of Chile’s hyper-arid Atacama Desert. Our collections focus on 32 Atacama extremophile species, including seven grass species with potential biofuel applications. To identify genes-of-importance to survival we compared genomic and transcriptomic profiles of extremophile species that thrive in the Atacama to those of closely related “sister” species from nitrogen-rich arid and mesic regions of California. Deep RNA sequencing and de novo transcriptome assembly across these triplet species sets supported a phylogenomic framework for identifying positively selected genes associated with adaptive divergence. Our integrative analysis combined ecological and environmental data, metagenomics, evolutionary and systems biology, and metabolomics. This enabled us to create an unprecedented framework for systematically understanding how non-model plants have adapted to survive in extreme conditions. Our resulting database of positively selected ortholog groups in the extremophile plants offers promising targets for engineering crop and biofuel species with enhanced resilience to drought and extreme weather. Additionally, our newest dataset explores and exploits a complementary metabolomic approach. This new aspect provides innovative strategies to manipulate plant cell metabolism, further supporting efforts to improve agricultural productivity in the face of extreme climates. Importantly, our combined evolutionary- and metabolomic-based strategies focused on convergent patterns of adaptation, providing a genetic and metabolomic toolkit for improving crop and biofuel resilience across diverse plant species. Finally, our novel exploration of ecological and evolutionary dynamics delivered to the community a phylogenomic computational pipeline called “PhyloGeneious.” Our continued adaptations of this pipeline are publicly available to expedite evolutionary genomic research for future scientific discoveries. In total, our DOE-BER has provided genomic, metabolomic, and computational strategies to understand how extremophile plants provide evolutionary and physiological targets for improving agricultural and biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Thermonuclear 28 P(p, γ ) 29 S reaction rate and astrophysical implication in ONe nova explosion

An accurate 28 P(p, γ) 29 S reaction rate is crucial to defining the nucleosynthesis products of explosive hydrogen burning in ONe novae. Using the recently released nuclear mass of 29 S, together with a shell model and a direct capture calculation, we reanalyzed the 28 P(p, γ) 29 S thermonuclear reaction rate and its astrophysical implication. We focus on improving the astrophysical rate for 28 P(p, γ) 29 S based on the newest nuclear mass data. Our goal is to explore the impact of the new rate and associated uncertainties on the nova nucleosynthesis. We evaluated this reaction rate via the sum of the isolated resonance contribution instead of the previously used Hauser-Feshbach statistical model. The corresponding rate uncertainty at different energies was derived using a Monte Carlo method. Nova nucleosynthesis is computed with the 1D hydrodynamic code SHIVA. The contribution from the capture on the first excited state at 105.64 keV in 28 P is taken into account for the first time. We find that the capture rate on the first excited state in 28 P is up to more than 12 times larger than the ground-state capture rate in the temperature region of 2.5 × 10 7 K to 4 × 10 8 K, resulting in the total 28 P(p, γ) 29 S reaction rate being enhanced by a factor of up to 1.4 at ~1 × 10 9 K. In addition, the rate uncertainty has been quantified for the first time. It is found that the new rate is smaller than the previous statistical model rates, but it still agrees with them within uncertainties for nova temperatures. The statistical model appears to be roughly valid for the rate estimation of this reaction in the nova nucleosynthesis scenario. Using the 1D hydrodynamic code SHIVA, we performed the nucleosynthesis calculations in a nova explosion to investigate the impact of the new rates of 28 P(p, γ) 29 S. Our calculations show that the nova abundance pattern is only marginally affected if we use our new rates with respect to the same simulations but statistical model rates. Finally, the isotopes whose abundance is most influenced by the present 28 P(p, γ) 29 S uncertainty are 28 Si, 33,34 S, 35,37 Cl, and 36 Ar, with relative abundance changes at the level of only 3% to 4%.

Astronomy & Astrophysics↗
DOE OSTI2026

Score-based deterministic density sampling

We propose a deterministic sampling framework using Score-Based Transport Modeling for sampling an unnormalized target density π given only its score ∇ log π. Our method approximates the Wasserstein gradient flow on KL($f_t$∥π) by learning the time-varying score ∇ log $f_t$ on the fly using score matching. While having the same marginal distribution as Langevin dynamics, our method produces smooth deterministic trajectories, resulting in monotone noise-free convergence. We prove that our method dissipates relative entropy at the same rate as the exact gradient flow, provided sufficient training. Numerical experiments validate our theoretical findings: our method converges at the optimal rate, has smooth trajectories, and is often more sample efficient than its stochastic counterpart. Experiments on high-dimensional image data show that our method produces high-quality generations in as few as 15 steps and exhibits natural exploratory behavior. The memory and runtime scale linearly in the sample size.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Reynolds-Averaged Turbulence Model Assessment for a Highly Back-Pressured Isolator Flowfield

The use of computational fluid dynamics in scramjet engine component development is widespread in the existing literature. Unfortunately, the quantification of model-form uncertainties is rarely addressed with anything other than sensitivity studies, requiring that the computational results be intimately tied to and calibrated against existing test data. This practice must be replaced with a formal uncertainty quantification process for computational fluid dynamics to play an expanded role in the system design, development, and flight certification process. Due to ground test facility limitations, this expanded role is believed to be a requirement by some in the test and evaluation community if scramjet engines are to be given serious consideration as a viable propulsion device. An effort has been initiated at the NASA Langley Research Center to validate several turbulence closure models used for Reynolds-averaged simulations of scramjet isolator flows. The turbulence models considered were the Menter BSL, Menter SST, Wilcox 1998, Wilcox 2006, and the Gatski-Speziale explicit algebraic Reynolds stress models. The simulations were carried out using the VULCAN computational fluid dynamics package developed at the NASA Langley Research Center. A procedure to quantify the numerical errors was developed to account for discretization errors in the validation process. This procedure utilized the grid convergence index defined by Roache as a bounding estimate for the numerical error. The validation data was collected from a mechanically back-pressured constant area (1 2 inch) isolator model with an isolator entrance Mach number of 2.5. As expected, the model-form uncertainty was substantial for the shock-dominated, massively separated flowfield within the isolator as evidenced by a 6 duct height variation in shock train length depending on the turbulence model employed. Generally speaking, the turbulence models that did not include an explicit stress limiter more closely matched the measured surface pressures. This observation is somewhat surprising, given that stress-limiting models have generally been developed to better predict shock-separated flows. All of the models considered also failed to properly predict the shape and extent of the separated flow region caused by the shock boundary layer interactions. However, the best performing models were able to predict the isolator shock train length (an important metric for isolator operability margin) to within 1 isolator duct height.

Baurle, Robert A.↗
DOE OSTI2026

Techno-Economic Analysis of Recycling Strategies for Catalyst and Acid During Catalytic Graphitization

With the aim of meeting the urgent demand for active anode materials (AAM) in energy storage systems, bio-based graphite (biographite) emerges as an affordable solution to de-risk the turbulent supply chain of critical minerals. Anode grade biographite requires high crystallinity and purity, which can be achieved by catalytic graphitization with iron, followed by acid washing. Therefore, a well-conceived process integration that recycles catalyst can be the starting point to commercialization. This study evaluates closed-loop catalyst recovery, and byproducts valorization scenarios through a technoeconomic framework to help understand the scale-up potential of biographite. For the acid washing, three reactors in series meet the required biographite purity at 99.95%. Iron and acid recovery can reduce material consumption and waste generation by ~95%, albeit at the expense of ~80% increase in capital costs. Recovery scenarios present similar capital and operational expenses, yielding minimum selling prices (MSP) near $6 kg-1 of biographite. Monte Carlo methodology reveals that feedstock price accounts for ~60% of MSP variance, followed by plant capacity ~20%. The likelihood of reaching a competitive profit margin of 30% in the U.S. AAM market sits at 85% average for recovery scenarios, and 103% when iron oxide is sold as byproduct. Additionally, an IRR >= 15% can be achieved for half of Monte Carlo simulations, representing promising early-stage results. Biographite production offers a strategic pathway to stabilize the anode market beyond China by integrating established technologies for a scalable, economically viable, and sustainable process. The role of catalyst recovery and byproducts utilization is critical for advancing the biomaterials industry.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Algorithms for software development version control and change detection

Simple computer algorithms for processing source program and text data files in order to extract change detection, version control, version history, and current status information are described. These algorithms presuppose that it is possible to attach to each record of the source files a 6-character code, placed within delimiters that will cause the compiler, or other using program, to ignore this code field. The code contains a 2-character code for a character-by-character position-sensitive checksum of the record, another for the record number in the file, and a third for the data on which the encoding took place. Once the source file has been thus encoded, it is possible to detect the following transactions on the file since the most recent version coding; (1) addition of new records (having no version code), (2) modification of existing records, (3) deletion of a number of records, (4) movement and/or duplication of existing records, and (5) modification and duplication of records. In addition, it is possible to extract a version history of the number of records created or modified by date. A special file listing program is described which prints the file records without showing the version codes, but places a "change bar" at the right margin whenever a change is detected. The program also provides a list of changed pages and a version history.

Tausworthe, R. C.↗
DOE OSTI2020

Relevant Advanced Reactor Benchmarks for Nuclear Data Assessment

Advanced reactor concepts currently being developed throughout the industry are significantly different from light water reactor (LWR) designs with respect to geometry, materials, and operating conditions, and consequently, with respect to their reactor physics behavior. Given the limited operating experience with non-LWRs, the accurate simulation of reactor physics and the quantification of associated uncertainties are critical for ensuring that advanced reactor concepts operate within the appropriate safety margins. Nuclear data are a major source of input uncertainties in reactor physics analysis. As part of an ongoing project at Oak Ridge National Laboratory, the effects of nuclear data uncertainties on key figures of merit associated with advanced reactor safety are being assessed for selected advanced reactor technologies. Key nuclear data relevant for reactor safety analysis for each selected advanced reactor technology were identified in Phase 1, and their impact on important key figures of merit was assessed in Phase 2. This report describes the outcome of Phase 3. Available benchmarks and fuel irradiation data for use in evaluating the impact of uncertainties and gaps in nuclear data that impact reactivity control for advanced reactor designs through the fuel cycle were identified and assessed. Benchmarks were identified by searching (1) the Organisation for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) International Criticality Safety Benchmark Evaluation Project (IRPhEP) handbook, (2) the OCED/NEA International Reactor Physics Experiment Evaluation Project (IRPhEP) handbook, (3) ongoing OECD/NEA benchmark activities, and (4) documentation in public literature. Relevant benchmarks were identified by selecting reactors with geometry, materials, and neutron energy spectra similar to those of selected advanced reactor technologies. This assessment identified six benchmarks, of which three are experimental and three are purely computational. One experimental and one computation benchmark contain depleted fuel; all others are limited to fresh fuel. This report provides short descriptions of the selected benchmarks along with the availability of measured data for comparison.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2009

Coupled Analysis of an Inlet and Fan for a Quiet Supersonic Aircraft

A computational analysis of a Gulfstream isentropic external compression supersonic inlet coupled to a Rolls-Royce fan was completed. The inlet was designed for a small, low sonic boom supersonic vehicle with a design cruise condition of M = 1.6 at 45,000 feet. The inlet design included an annular bypass duct that routed flow subsonically around an engine-mounted gearbox and diverted flow with high shock losses away from the fan tip. Two Reynolds-averaged Navier-Stokes codes were used for the analysis: an axisymmetric code called AVCS for the inlet and a 3-D code called SWIFT for the fan. The codes were coupled at a mixing plane boundary using a separate code for data exchange. The codes were used to determine the performance of the inlet/fan system at the design point and to predict the performance and operability of the system over the flight profile. At the design point the core inlet had a recovery of 96 percent, and the fan operated near its peak efficiency and pressure ratio. A large hub radial distortion generated in the inlet was not eliminated by the fan and could pose a challenge for subsequent booster stages. The system operated stably at all points along the flight profile. Reduced stall margin was seen at low altitude and Mach number where flow separated on the interior lips of the cowl and bypass ducts. The coupled analysis gave consistent solutions at all points on the flight profile that would be difficult or impossible to predict by analysis of isolated components.

Chima, Rodrick V.↗
NASA NTRS2019

Optimizing a Coupled Solution for the Orion MPCV Using DPLR and NEQAIR

The goal of this project is to study the convective and radiative heat flux predictions using computational fluid dynamics (CFD) on a smooth body representation of the NASA Orion Multi-Purpose Crew Vehicle (MPCV). The Orion MPCV is designed for long duration missions in space and will play a crucial role in transporting astronauts in the upcoming Artemis missions. With Orion's aim for cost-effective reusability comes a need to study its Thermal Protection System (TPS), which allows for safe entry into the atmospheres of the Earth, Moon, and Mars. In order to study the effects of the TPS on test flights and better understand the aerothermal environment, CFD is a necessary tool used to create simulations of entry vehicles and calculate the heat load and heat flux. However, solutions are often performed using an uncoupled approach between the flow and the radiation solver. This leads to an overestimation of the overall heating effects because they do not consider radiative cooling. Furthermore, the effects of radiation on the aft-body is an area of research with significant uncertainty. Through the use of codes developed at NASA Ames, DPLR and NEQAIR, a coupled solution can be attained for the Orion capsule which will more accurately solve for the effects of radiation in both the fore and aft-body regions. This yields more accurate design margins for the TPS, which produces a better estimate of the thickness required. By developing an accurate coupled solution of the TPS on the Orion MPCV, planners will have greater flexibility in carrying out future missions to the Moon and beyond.

Design↗
DOE OSTI2022

Hydrodynamics of countercurrent flow in an additive-manufactured column with triply periodic minimal surfaces for carbon dioxide capture

Computational investigation of the countercurrent flows in an additively manufactured (AM) column packed with triply periodic minimal surface (TPMS) is challenging. Multiphase flow simulations using the volume of fluid (VOF) method can explain the column’s hydrodynamic characteristics, including interfacial area, liquid holdup, pressure drop, flow regime, etc. The interfacial area is a key factor dictating the mass transfer via the absorption process, and thereby the overall efficiency of the column. The impacts of a solvent's physical properties, liquid and gas loads, and contact angle on the hydrodynamics are extensively explored. The solvents include traditional solvent (monoethanolamine [MEA]) used in industry as well as a water-lean solvent (EEMPA) as prospective solvents for carbon capture. As expected, interfacial area and liquid holdup increase with increasing liquid loads (q L ). The EEMPA exhibits higher values for the interfacial area and liquid holdup compared to those for the MEA. The dry and wet pressure drops per unit length in the column at different gas loads (F G ) are calculated and further compared with the empirical correlations for traditional packings. At low gas loads, i.e., in the preloading regime, the predicted values of the wet and dry pressure drops match well with the corresponding values calculated from available correlations. The gas load has a marginal impact on the interfacial area at its lower value, but the higher value of F G (>2.18 $\sqrt{Pa}$) causes flooding in the column. The effect of varying contact angles on the interfacial area and liquid holdup in the preloading regime is also studied. Both interfacial area and liquid holdup decrease with the increase in the value of the contact angle. Altogether, the effect of the contact angle on interfacial area is more pronounced than other parameters influencing the interfacial area.

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

Optimal Bayesian supervised domain adaptation for RNA sequencing data

Abstract Motivation When learning to subtype complex disease based on next-generation sequencing data, the amount of available data is often limited. Recent works have tried to leverage data from other domains to design better predictors in the target domain of interest with varying degrees of success. But they are either limited to the cases requiring the outcome label correspondence across domains or cannot leverage the label information at all. Moreover, the existing methods cannot usually benefit from other information available a priori such as gene interaction networks. Results In this article, we develop a generative optimal Bayesian supervised domain adaptation (OBSDA) model that can integrate RNA sequencing (RNA-Seq) data from different domains along with their labels for improving prediction accuracy in the target domain. Our model can be applied in cases where different domains share the same labels or have different ones. OBSDA is based on a hierarchical Bayesian negative binomial model with parameter factorization, for which the optimal predictor can be derived by marginalization of likelihood over the posterior of the parameters. We first provide an efficient Gibbs sampler for parameter inference in OBSDA. Then, we leverage the gene-gene network prior information and construct an informed and flexible variational family to infer the posterior distributions of model parameters. Comprehensive experiments on real-world RNA-Seq data demonstrate the superior performance of OBSDA, in terms of accuracy in identifying cancer subtypes by utilizing data from different domains. Moreover, we show that by taking advantage of the prior network information we can further improve the performance. Availability and implementation The source code for implementations of OBSDA and SI-OBSDA are available at the following link. https://github.com/SHBLK/BSDA. Supplementary information Supplementary data are available at Bioinformatics online.

Biochemistry & Molecular Biology↗
NASA NTRS2010

Coupled Analysis of an Inlet and Fan for a Quiet Supersonic Jet

A computational analysis of a Gulfstream isentropic external compression supersonic inlet coupled to a Rolls-Royce fan has been completed. The inlet was designed for a small, low sonic boom supersonic vehicle with a design cruise condition of M = 1.6 at 45,000 ft. The inlet design included an annular bypass duct that routed flow subsonically around an engine-mounted gearbox and diverted flow with high shock losses away from the fan tip. Two Reynolds-averaged Navier-Stokes codes were used for the analysis: an axisymmetric code called AVCS for the inlet and a three dimensional (3-D) code called SWIFT for the fan. The codes were coupled at a mixing plane boundary using a separate code for data exchange. The codes were used to determine the performance of the inlet/fan system at the design point and to predict the performance and operability of the system over the flight profile. At the design point the core inlet had a recovery of 96 percent, and the fan operated near its peak efficiency and pressure ratio. A large hub radial distortion generated in the inlet was not eliminated by the fan and could pose a challenge for subsequent booster stages. The system operated stably at all points along the flight profile. Reduced stall margin was seen at low altitude and Mach number where flow separated on the interior lips of the cowl and bypass ducts. The coupled analysis gave consistent solutions at all points on the flight profile that would be difficult or impossible to predict by analysis of isolated components.

Chima, Rodrick V.↗
NASA NTRS1999

Early events in the folding of an amphipathic peptide: A multinanosecond molecular dynamics study

Folding of the capped LQQLLQQLLQL peptide is investigated at the water-hexane interface by molecular dynamics simulations for 161.5 ns. Initially placed in the aqueous phase as a beta-strand, the peptide rapidly adsorbs to the interface, where it adopts an amphipathic conformation. The marginal presence of nonamphipathic structures throughout the complete trajectory indicates that the corresponding conformations are strongly disfavored at the interface. It is further suggestive that folding in an interfacial environment proceeds through a pathway of successive amphipathic intermediates. The energetic and entropic penalties involved in the conformational changes along this pathway markedly increase the folding time scales of LQQLLQQLLQL, explaining why the alpha-helix, the hypothesized lowest free energy structure for a sequence with a hydrophobic periodicity of 3.6, has not been reached yet. The formation of a type I beta-turn at the end of the simulation confirms the importance of such motifs as initiation sites allowing the peptide to coalesce towards a secondary structure. Proteins 1999;36:383-399. Copyright 1999 Wiley-Liss, Inc.

NASA Center ARC↗
NASA NTRS2017

Structural Design Exploration of an Electric Powered Multi-Propulsor Wing Configuration

Advancements in aircraft electric propulsion may enable an expanded operational envelope for electrically powered vehicles compared to their internal combustion engine counterparts. High aspect ratio wings provide additional lift and drag reduction for a proposed multi-propulsor design, however, the challenge is to reduce the weight of wing structures while maintaining adequate structural and aeroelastic margins. Design exploration using a conventional design-and-build philosophy coupled with a finite element method (FEM)-based design of experiments (DOE) strategy are presented to examine high aspect ratio wing structures that have spanwise distributed electric motors. Multiple leading-edge-mounted engine masses presented a challenge to design a wing within acceptable limits for dynamic and aeroelastic stability. Because the first four primary bending eigenmodes of the proposed wing structure are very sensitive to outboard motor placement, safety-of-flight requirements drove the need for multiple spars, rib attachments, and outboard structural reinforcements in the design. Global aeroelasticity became an increasingly important design constraint during the on-going design process, with outboard motor pod flutter ultimately becoming a primary design constraint. Designers successively generated models to examine stress, dynamics, and aeroelasticity concurrently. This research specifically addressed satisfying multi-disciplinary design criteria to generate fluid-structure interaction solution sets, and produced high aspect ratio primary structure designs for the NASA Scalable Convergent Electric Propulsion Technology and Operations Research (SCEPTOR) project in the Aeronautic Research Mission Directorate at NASA. In this paper, a dynamics-driven, quasi-inverse design methodology is presented to address aerodynamic performance goals and structural challenges encountered for the SCEPTOR demonstrator vehicle. These results are compared with a traditional computer aided design based approach.

Moore, James B.↗
NASA NTRS2022

Mars 2020 Entry, Descent, and Landing System Software Implementation

On February 18th, 2021, the Mars 2020 project's Perseverance Rover successfully touched down on the Martian surface after nearly eight years of development. The Mars 2020 Entry, Descent, and Landing (EDL) System largely leveraged heritage from the Mars Science Laboratory (MSL) EDL System while employing targeted technological advancements. The landing process is autonomously directed by a software behavior implemented in the rover's primary flight computer called the EDL Timeline that assumes control of the vehicle six days before atmospheric entry. This paper first walks through the basics of the EDL Timeline mechanics and how the behavior is designed to account for internal system variations and environmental unknowns. It then summarizes the interactions between the EDL timeline and other high-level system behaviors like spacecraft mode transitions and system fault protection, focusing on the complications that arise when passing spacecraft control between executive functions. Although the MSL-inherited EDL System is reliable and capable, targeted updates and a thorough verification and validation program were required for Mars 2020. This paper discusses changes made to close vulnerabilities discovered during both MSL and Mars 2020 development cycles, landing system capability enhancements that were enabling for Mars 2020's mission, and how these updates were integrated with the heritage system. It then describes how both analysis and testing campaigns were utilized to verify and validate all aspects of EDL and system behaviors that run during the six days before landing, as well as the operational workarounds that were needed to address problems found during the development and commissioning process. Finally, this paper imparts lessons learned from Mars 2020 EDL development, implementation, and operations, emphasizing how systems designed to conduct time-critical mission events with low margin of error can be improved in the future.

Stehura, Aaron↗
NASA NTRS2023

Fully Coupled Aeroelastic Stability Analysis of Adaptive Shape Memory Alloy Structural Technologies for Airframe Noise Reduction

This final report documents work performed by ATA Engineering, Inc., (ATA) to develop computational models and analyze the coupled fluid-structure response of two types of noise treatments applied to the leading-edge-slat component of a high-lift system typical of modern transport aircraft. The first treatment is a slat-gap filler (SGF), which closes the gap between the suction surfaces of a deployed slat and an aircraft main wing, and the second treatment is a slat-cove filler (SCF), which replaces the recirculating flow on the slat cove with a surface that promotes flow attachment. The representative airframe chosen for this work was NASA’s High-Lift Common Research Model (CRM-HL) in a baseline high-lift configuration. Superelastic shape memory alloys (SMAs) have been identified as enabling materials for these structural treatments. Since the technology elements rely upon having a highly reconfigurable structure, designs were assessed for their static aeroelastic deflection as well as their dynamic aeroelastic stability using coupled computational fluid dynamics (CFD) and nonlinear computational structural dynamics (NL-CSD) tools. Specifically, fluid-structure interaction (FSI) problems were solved computationally using the CFD solver Loci/CHEM and the NL-CSD solver Abaqus. As a part of the overall project, a similar capability was implemented using the CFD solver FUN3D coupled to Abaqus, although that work is documented in a separate report and that FSI framework was not used to analyze any of NASA’s SGF and SCF configurations. The technical approach consisted of solving for the flow field around the entire vehicle using a global CFD model, followed by extraction of relevant local subdomain data for CFD and NL-CSD co-simulations. The SGF design was analyzed using both 2D and 3D co-simulations to predict quasi-static aeroelastic deformations and to assess dynamic aeroelastic stability, whereas the SCF was analyzed in 2D only. SGF static aeroelastic response predictions focused on characterizing the deformed shape, with maximum displacements predicted to be on the order of magnitude of the technology element panel thickness. SGF dynamic aeroelastic response predictions used Partial Floquet analysis of the temporal evolution of selected nodal displacements to quantify the sign and magnitude of aeroelastic damping. Results suggest that the CRM-HL operating conditions would result in a dynamically stable response. The simulated dynamic pressure was also increased up to a factor of about four, and resulting responses suggest that predicted dynamic stability would be achieved with some margin.

Fluid Structure Interaction↗
DOE OSTI2025

The SAS4A/SASSYS-1 Version 5.8 Safety Analysis Code System

SAS4A/SASSYS-1 is a software simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced nuclear reactors. Detailed, mechanistic models of steady-state and transient thermal, hydraulic, kinetic, and mechanical phenomena are employed to describe the response of the reactor core, the reactor primary and secondary coolant loops, the reactor control and protection systems, and the balance-of-plant to accidents caused by changes in coolant flow, loss of heat rejection, or reactivity insertion. The consequences of single and double-fault accidents can be modeled, including fuel and coolant heating, fuel and cladding mechanical behavior, core reactivity feedbacks, coolant loop performance including natural circulation, and decay heat removal. Analyses are typically terminated upon demonstration of reactor and plant shutdown to permanently coolable conditions, or upon violation of design basis margins. The objective of the analysis is to quantify accident consequences as measured by the transient behavior of system performance parameters, such as fuel and cladding temperatures, reactivity, and cladding strain. Originally developed for analysis of sodium cooled reactors with oxide fuel clad by stainless steel, the models were subsequently extended and specialized to metallic fuel clad with advanced alloys and to several other coolant options, including lead, LBE, and water.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2003

Structure, Function, Self-Assembly and Origin of Simple Membrane Proteins

Integral membrane proteins perform such essential cellular functions as transport of ions, nutrients and waste products across cell walls, transduction of environmental signals, regulation of cell fusion, recognition of other cells, energy capture and its conversion into high-energy compounds. In fact, 30-40% of genes in modem organisms codes for membrane proteins. Although contemporary membrane proteins or their functional assemblies can be quite complex, their transmembrane fragments are usually remarkably simple. The most common structural motif for these fragments is a bundle of alpha-helices, but occasionally it could be a beta-barrel. In a series of molecular dynamics computer simulations we investigated self-organizing properties of simple membrane proteins based on these structural motifs. Specifically, we studied folding and insertion into membranes of short, nonpolar or amphiphatic peptides. We also investigated glycophorin A, a peptide that forms sequence-specific dimers, and a transmembrane aggregate of four identical alpha-helices that forms an efficient and selective voltage-gated proton channel was investigated. Many peptides are attracted to water-membrane interfaces. Once at the interface, nonpolar peptides spontaneously fold to a-helices. Whenever the sequence permits, peptides that contain both polar and nonpolar amino also adopt helical structures, in which polar and nonpolar amino acid side chains are immersed in water and membrane, respectively. Specific identity of side chains is less important. Helical peptides at the interface could insert into the membrane and adopt a transmembrane conformation. However, insertion of a single helix is unfavorable because polar groups in the peptide become completely dehydrated upon insertion. The unfavorable free energy of insertion can be regained by spontaneous association of peptides in the membrane. The first step in this process is the formation of dimers, although the most common are aggregates of 4-7 helices. The helices could arrange themselves such that they formed pores capable of transporting ions and small molecules across membranes. Stability of transmembrane aggregates of simple proteins is often only marginal and, therefore, it can be regulated by environmental signals or small sequence modifications in the region of interhelical interactions. A key step in the earliest evolution of membrane proteins was the emergence of selectivity for specific substrates. Many channels could become selective if one or only a few properly chosen amino acids are properly placed along the channel, acting as filters or gates. This is a convenient evolutionary solution because it does not require imposing conditions on the whole sequence.

Pohorille, Andrew↗