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NASA NTRS1998

Global Warming Estimation from MSU

Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz) from sequential, sun-synchronous, polar-orbiting NOAA satellites contain small systematic errors. Some of these errors are time-dependent and some are time-independent. Small errors in Ch 2 data of successive satellites arise from calibration differences. Also, successive NOAA satellites tend to have different Local Equatorial Crossing Times (LECT), which introduce differences in Ch 2 data due to the diurnal cycle. These two sources of systematic error are largely time independent. However, because of atmospheric drag, there can be a drift in the LECT of a given satellite, which introduces time-dependent systematic errors. One of these errors is due to the progressive chance in the diurnal cycle and the other is due to associated chances in instrument heating by the sun. In order to infer global temperature trend from the these MSU data, we have eliminated explicitly the time-independent systematic errors. Both of the time-dependent errors cannot be assessed from each satellite. For this reason, their cumulative effect on the global temperature trend is evaluated implicitly. Christy et al. (1998) (CSL). based on their method of analysis of the MSU Ch 2 data, infer a global temperature cooling trend (-0.046 K per decade) from 1979 to 1997, although their near nadir measurements yield near zero trend (0.003 K/decade). Utilising an independent method of analysis, we infer global temperature warmed by 0.12 +/- 0.06 C per decade from the observations of the MSU Ch 2 during the period 1980 to 1997.

Prabhakara, C.↗

NASA NTRS1992

Aerodynamic simulation on massively parallel systems

This paper briefly addresses the computational requirements for the analysis of complete configurations of aircraft and spacecraft currently under design to be used for advanced transportation in commercial applications as well as in space flight. The discussion clearly shows that massively parallel systems are the only alternative which is both cost effective and on the other hand can provide the necessary TeraFlops, needed to satisfy the narrow design margins of modern vehicles. It is assumed that the solution of the governing physical equations, i.e., the Navier-Stokes equations which may be complemented by chemistry and turbulence models, is done on multiblock grids. This technique is situated between the fully structured approach of classical boundary fitted grids and the fully unstructured tetrahedra grids. A fully structured grid best represents the flow physics, while the unstructured grid gives best geometrical flexibility. The multiblock grid employed is structured within a block, but completely unstructured on the block level. While a completely unstructured grid is not straightforward to parallelize, the above mentioned multiblock grid is inherently parallel, in particular for multiple instruction multiple datastream (MIMD) machines. In this paper guidelines are provided for setting up or modifying an existing sequential code so that a direct parallelization on a massively parallel system is possible. Results are presented for three parallel systems, namely the Intel hypercube, the Ncube hypercube, and the FPS 500 system. Some preliminary results for an 8K CM2 machine will also be mentioned. The code run is the two dimensional grid generation module of Grid, which is a general two dimensional and three dimensional grid generation code for complex geometries. A system of nonlinear Poisson equations is solved. This code is also a good testcase for complex fluid dynamics codes, since the same datastructures are used. All systems provided good speedups, but message passing MIMD systems seem to be best suited for large miltiblock applications.

Haeuser, Jochem↗

DOE OSTI2025

Structural Distortions and Uniaxial Negative Thermal Expansion in the Polar Dion–Jacobson Oxide RbNdTa 2 O 7

We provide deeper insight into the crystal structures, sequential structural phase transitions (I2cm → Cmce → I4/mcm → P4/mmm), thermal expansion, and electronic properties of the n = 2 Dion–Jacobson polar oxide RbNdTa 2 O 7 , through X-ray powder diffraction, neutron powder diffraction, Raman studies, and density functional theory calculations. We observed a uniaxial negative thermal expansion (NTE) across the first-order transition, I2cm → Cmce, where the unit cell contracts along the c-axis, which is driven by a contraction of the NdTa 2 O 6 layer. Here, this NTE occurs within the temperature range of the first-order phase transition and contrasts with the corkscrew mechanism typically observed in Ruddlesden–Popper phases. In RbNdTa 2 O 7 , the I2cm (hybrid improper ferroelectric) → Cmce (antipolar) transition involves crucial changes in the bond lengths of Nd and Ta polyhedra, coupled with polar to antipolar displacement of the Nd ions, leading to a net contraction in the NdTa 2 O 6 layer along the c-axis, while preserving the overall octahedral tilting magnitude. This transition highlights the intricate interplay between the Nd and Ta coordination and the associated TaO 6 distortions. Temperature-dependent Raman spectra analysis further confirms the first-order structural transition and associated NTE, providing evidence for increased bond stiffness across this transition. Additionally, using neutron powder diffraction, we have determined that the transition I4/mcm → P4/mmm occurs at approximately 1150 K. Finally, we have calculated from DFT + U, the partial density of states, the energy bandgaps, and effective masses of the charge carriers of the polar ground structure.

Chemical structure↗

NASA NTRS2016

Simulated Space Radiation: Murine Skeletal Responses During Recovery and with Mechanical Stimulation

Simulated space radiation at doses similar to those of solar particle events or a round-trip sojourn to Mars (1-2Gy) may cause skeletal tissue degradation and deplete stem/progenitor cell pools throughout the body. We hypothesized that simulated space radiation (SSR) causes late, time-dependent deficits in bone structure and bone cell function reflected by changes in gene expression in response to anabolic stimuli. We used a unique sequential dual ion exposure (proton and iron) for SSR to investigate time-dependence of responses in gene expression, cell function, and microarchitecture with respect to radiation and an anabolic stimulus of axial loading (AL). Male 16-wk C57BL6/J mice (n=120 total) were exposed to 0Gy (Sham, n=10), 56Fe (2Gy, positive control dose, n=10), or sequential ions for SSR (1Gy 1H/56Fe/1H, n=10) by total body irradiation (IR), and the tissues were harvested 2 or 6 mo. later. Further, to assess the response to anabolic stimuli, we subjected additional Sham-AL (n=15) and SSR-AL (n=15) groups to rest-inserted tibial axial loading (AL) starting at 1 and 5 months post-IR (-9N, 60 cycles/day, 3 days/wk, 4 wks). Exposure to 56Fe caused a significant reduction in cancellous bone volume fraction (BV/TV) compared to Sham (-34%) and SSR (-20%) in the proximal tibia metaphysis at 2-months post-IR; however BV/TV for SSR group was not different than Sham. Both 56Fe and SSR caused significant reduction in trabecular number (Tb.N) compared to Sham (-33% and -16%, respectively). Further, Tb.N for 56Fe (2Gy) was significantly lower than SSR (-21%). Ex vivo culture of marrow cells to assess growth and differentiation of osteoblast lineage cells 6 months post-IR showed that both 56Fe and SSR exposures significantly impaired colony formation compared to Sham (-66% and -54%, respectively), as well as nodule mineralization (-90% and -51%, respectively). Two-way analysis of variance showed that both mechanical loading and radiation reduced BV/TV, mechanical loading reduced trabecular thickness (Tb.Th), and radiation reduced Tb.N, at both time points. To assess acute response to mechanical stimuli, samples were harvested from a subset of Sham-AL (n=5) and SSR-AL (n=5) to measure changes in gene expression levels. Preliminary results indicate that axial loading increased expression of the antioxidant response gene Nfe2l2 and the osteoprogenitor-associated marker Runx2 in the bone marrow cells, and there was an interaction effect between axial loading and radiation at 2-months post-IR. Additional analyses of gene expression levels in the mineralized tissue are in progress. Results indicate that SSR caused persistent impairment of osteoblast colony formation and nodule mineralization 6-mo post-IR. Contrary to our hypothesis, simulated space radiation did not impair the ability of cancellous bone to respond to a mechanical anabolic stimulus, consistent with our previous findings [1]. Hence, compressive loading may be a potential countermeasure against spaceflight-induced bone loss.

Bone Loss↗

NASA NTRS2016

Simulated Space Radiation: Murine Skeletal Responses During Recovery and with Mechanical Stimulation

Simulated space radiation at doses similar to those of solar particle events or a round-trip sojourn to Mars (1-2Gy) may cause skeletal tissue degradation and deplete stem/progenitor cell pools throughout the body. We hypothesized that simulated space radiation (SSR) causes late, time-dependent deficits in bone structure and bone cell function reflected by changes in gene expression in response to anabolic stimuli. We used a unique sequential dual ion exposure (proton and iron) for SSR to investigate time-dependence of responses in gene expression, cell function, and microarchitecture with respect to radiation and an anabolic stimulus of axial loading (AL). Male 16-wk C57BL6/J mice (n=120 total) were exposed to 0Gy (Sham, n=10), 56Fe (2Gy, positive control dose, n=10), or sequential ions for SSR (1Gy 1H/56Fe/1H, n=10) by total body irradiation (IR), and the tissues were harvested 2 or 6 mo. later. Further, to assess the response to anabolic stimuli, we subjected additional Sham-AL (n=15) and SSR-AL (n=15) groups to rest-inserted tibial axial loading (AL) starting at 1 and 5 months post-IR (-9N, 60 cycles/day, 3 days/wk, 4 wks). Exposure to 56Fe caused a significant reduction in cancellous bone volume fraction (BV/TV) compared to Sham (-34%) and SSR (-20%) in the proximal tibia metaphysis at 2-months post-IR; however BV/TV for SSR group was not different than Sham. Both 56Fe and SSR caused significant reduction in trabecular number (Tb.N) compared to Sham (-33% and -16%, respectively). Further, Tb.N for 56Fe (2Gy) was significantly lower than SSR (-21%). Ex vivo culture of marrow cells to assess growth and differentiation of osteoblast lineage cells 6 months post-IR showed that both 56Fe and SSR exposures significantly impaired colony formation compared to Sham (-66% and -54%, respectively), as well as nodule mineralization (-90% and -51%, respectively). Two-way analysis of variance showed that both mechanical loading and radiation reduced BV/TV, mechanical loading reduced trabecular thickness (Tb.Th), and radiation reduced Tb.N, at both time points. To assess acute response to mechanical stimuli, samples were harvested from a subset of Sham-AL (n=5) and SSR-AL (n=5) to measure changes in gene expression levels. Preliminary results indicate that axial loading increased expression of the antioxidant response gene Nfe2l2 and the osteoprogenitor-associated marker Runx2 in the bone marrow cells, and there was an interaction effect between axial loading and radiation at 2-months post-IR. Additional analyses of gene expression levels in the mineralized tissue are in progress. Results indicate that SSR caused persistent impairment of osteoblast colony formation and nodule mineralization 6-mo post-IR. Contrary to our hypothesis, simulated space radiation did not impair the ability of cancellous bone to respond to a mechanical anabolic stimulus, consistent with our previous findings. Hence, compressive loading may be a potential countermeasure against spaceflight-induced bone loss.

MURINE SKELETAL↗

NASA NTRS2000

Optical Analysis of Transparent Polymeric Material Exposed to Simulated Space Environment

Many innovations in spacecraft power and propulsion have been recently tested at NASA, particularly in non-chemical propulsion. One improvement in solar array technology is solar concentration using thin polymer film Fresnel lenses. Weight and cost savings were proven with the Solar Concentrator Arrays with Refractive Linear Element Technology (SCARLET)-II array on NASA's Deep Space I spacecraft. The Fresnel lens concentrates solar energy onto high-efficiency solar cells, decreasing the area of solar cells needed for power. Continued efficiency of this power system relies on the thin film's durability in the space environment and maintaining transmission in the 300 - 1000 nm bandwidth. Various polymeric materials have been tested for use in solar concentrators, including Lexan(TM), polyethylene terephthalate (PET), several formulations of Tefzel(Tm) and Teflon(TM), and DC 93-500, the material selected for SCARLET-II. Also tested were several innovative materials including Langley Research Center's CPI and CP2 polymers and atomic oxygen- resistant polymers developed by Triton Systems, Inc. The Environmental Effects Group of the Marshall Space Flight Center's Materials, Processes, and Manufacturing Department exposed these materials to simulated space environment and evaluated them for any change in optical transmission. Samples were exposed to a minimum of 1000 equivalent Sun hours of near-UV radiation (250 - 400 nm wavelength). Materials that appeared robust after near-UV exposure were then exposed to charged particle radiation equivalent to a five-year dose in geosynchronous orbit. These exposures were performed in MSFC's Combined Environmental Effects Test Chamber, a unique facility with the capability to expose materials simultaneously or sequentially to protons, low-energy electrons, high-energy electrons, near UV radiation and vacuum UV radiation. Reflectance measurements can be made on the samples in vacuum. Prolonged exposure to the space environment will decrease the polymer film's transmission and thus reduce the conversion efficiency. A method was developed to normalize the transmission loss and thus rank the materials according to their tolerance to space environmental exposure. Spectral results and the material ranking according to transmission loss are presented.

Edwards, David L.↗

DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗

NASA NTRS2021

Effects of a 33-Ion Sequential Beam Galactic Cosmic Ray Analog on Male Mouse Behavior and Evaluation of CDDO-EA as a Radiation Countermeasure

In long-term spaceflight, astronauts will face unique cognitive loads and social challenges which will be complicated by communication delays with Earth. It is important to understand the central nervous system (CNS) effects of deep spaceflight and the associated unavoidable exposure to galactic cosmic radiation (GCR). Rodent studies show single- or simple-particle combination exposure alters CNS endpoints, including hippocampal-dependent behavior. An even better Earth-based simulation of GCR is now available, consisting of a 33-beam (33-GCR) exposure. However, the effect of whole-body 33-GCR exposure on rodent behavior is unknown, and no 33-GCR CNS countermeasures have been tested. Here astronaut-age-equivalent (6mo-old) C57BL/6J male mice were exposed to 33-GCR (75cGy, a Mars mission dose). Pre-/during/post-Sham or 33-GCR exposure, mice received a diet containing a ‘vehicle’ formulation alone or with the antioxidant/anti-inflammatory compound CDDO-EA as a potential countermeasure. Behavioral testing beginning 4mo post-irradiation suggested radiation and diet did not affect measures of exploration/anxiety-like behaviors (open field, elevated plus maze) or recognition of a novel object. However, in 3-Chamber Social Interaction (3-CSI), CDDO-EA/33-GCR mice failed to spend more time exploring a holder containing a novel mouse vs. a novel object (empty holder), suggesting sociability deficits. Also, Vehicle/33-GCR and CDDO-EA/Sham mice failed to discriminate between a novel stranger vs. familiarized stranger mouse, suggesting blunted preference for social novelty. CDDO-EA given pre-/ during/post-irradiation did not attenuate the 33-GCR-induced blunting of preference for social novelty. Future elucidation of the mechanisms underlying 33-GCR-induced blunting of preference for social novelty will improve risk analysis for astronauts which may in-turn improve countermeasures.

Space radiation↗

NASA NTRS2021

Effects of A 33-Ion Sequential Beam Galactic Cosmic Ray Analog on Male Mouse Behavior and Evaluation of CDDO-EA as A Radiation Countermeasure

Space radiation↗

DOE OSTI2026

Vapor-Phase Heteroatom Incorporation into Semiconductive Molecular-Scale Magic-Size Clusters

Magic-size metal chalcogenide clusters of molecular size exhibit well-defined structure and unique properties that might be further expanded with the incorporation or substitution of a second metal. Here, we report the postmodification of magic-size clusters synthesized in polymer thin films via exposure to volatile metal organic precursors commonly utilized for atomic layer deposition. Exposure of In 6 S 6 (CH 3 ) 6 clusters to dimethylcadmium results in exposure-dependent incorporation of Cd 2+ , which extends the optical absorbance of the clusters into the visible spectrum. The mechanism for Cd 2+ incorporation is consistent with Cd 2+ replacement of In 3+ that includes methyl ligand removal to maintain charge neutrality. Even for clusters embedded in a polymer matrix, ligand loss leads to sintering and transformation into larger nanoscale aggregates with zinc blende-type structure. The extent of Cd incorporation can be modulated by varying the process temperature and volatile metal organic exposure as well as the choice of volatile metal organic precursor. A computational thermodynamic analysis of heteroatom incorporation for several metals and chemistries reveals that both the stability of the substituted cluster and the favorability of reaction byproducts jointly determine the favorability of cation incorporation.

atomic layer deposition↗

DOE OSTI2024

Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers

We present a new class of AI models for the detection of quasi-circular, spinning, non-precessing binary black hole mergers whose waveforms include the higher order gravitational wave modes ($\ell$, |m|) = {(2,2), (2,1), (3,3), (3,2), (4,4)}, and mode mixing effects in the $\ell$ = 3, |m| = 2 harmonics. These AI models combine hybrid dilated convolution neural networks to accurately model both short- and long-range temporal sequential information of gravitational waves; and graph neural networks to capture spatial correlations among gravitational wave observatories to consistently describe and identify the presence of a signal in a three detector network encompassing the Advanced LIGO and Virgo detectors. We first trained these spatiotemporal-graph AI models using synthetic noise, using 1.2 million modeled waveforms to densely sample this signal manifold, within 1.7 h using 256 NVIDIA A100 GPUs in the Polaris supercomputer at the Argonne Leadership Computing Facility. This distributed training approach exhibited optimal classification performance, and strong scaling up to 512 NVIDIA A100 GPUs. With these AI ensembles we processed data from a three detector network, and found that an ensemble of 4 AI models achieves state-of-the-art performance for signal detection, and reports two misclassifications for every decade of searched data. We distributed AI inference over 128 GPUs in the Polaris supercomputer and 128 nodes in the Theta supercomputer, and completed the processing of a decade of gravitational wave data from a three detector network within 3.5 h. Finally, we fine-tuned these AI ensembles to process the entire month of February 2020, which is part of the O3b LIGO/Virgo observation run, and found 6 gravitational waves, concurrently identified in Advanced LIGO and Advanced Virgo data, and zero false positives. This analysis was completed in one hour using one NVIDIA A100 GPU.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2005

Reciprocating Feed System Development Status

The reciprocating feed system (RFS) is an alternative means of providing high pressure propellant flow at low cost and system mass, with high fail-operational reliability. The RFS functions by storing the liquid propellants in large, low-pressure tanks and then expelling each propellant through two or three small, high-pressure tanks. Each RFS tank is sequentially filled, pressurized, expelled, vented, and refilled so as to provide a constant, or variable, mass flow rate to the engine. This type of system is much lighter than a conventional pressure fed system in part due to the greatly reduced amount of inert tank weight. The delivered payload for an RFS is superior to that of conventional pressure fed systems for conditions of high total impulse and it is competitive with turbopump systems, up to approximately 2000 psi. An advanced version of the RFS uses autogenous pressurization and thrust augmentation to achieve higher performance. In this version, the pressurization gases are combusted in a small engine, thus making the pressurization system, in effect, part of the propulsion system. The RFS appears to be much less expensive than a turbopump system, due to reduced research and development cost and hardware cost, since it is basically composed of small high- pressure tanks, a pressurization system, and control valves. A major benefit is the high reliability fail-operational mode; in the event of a failure in one of the three tank-systems, it can operate on the two remaining tanks. Other benefits include variable pressure and flow rates, ease of engine restart in micro-gravity, and enhanced propellant acquisition and control under adverse acceleration conditions. We present a system mass analysis tool that accepts user inputs for various design and mission parameters and calculates such output values payload and vehicle weights for the conventional pressure fed system, the RFS, the Autogenous Pressurization Thrust Augmentation (APTA) RFS, and turbopump systems. Using this tool, a preliminary design of a representative crew exploration vehicle (CEV) has been considered. The design parameters selected for a representative system were modeled after the orbital maneuvering system (OMS) on the Shuttle Orbiter, with an increase of roughly a factor of ten in the delta- V capability and a greater thrust (30,000 lbs, vs. 12,000 lbs). Both storable and cryogenic propellants were considered. Results show that a RFS is a low mass alternative to conventional pressure fed systems, with a substantial increase in payload capability and that it is weight-competitive with turbopump systems at low engine pressure (a few hundred psi); at high engine pressures, the APTA RFS appears to offer the highest payload. We also present the status of the RFS test bed fabrication, assembly, and checkout. This test bed is designed to provide flow rates appropriate for engines in the roughly 10,000 to 30,000 lb thrust range.

Trewek, Mary↗

NASA NTRS2002

Shuttle Abort Flight Management (SAFM) - Application Overview

One of the most demanding tasks that must be performed by the Space Shuttle flight crew is the process of determining whether, when and where to abort the vehicle should engine or system failures occur during ascent or entry. Current Shuttle abort procedures involve paging through complicated paper checklists to decide on the type of abort and where to abort. Additional checklists then lead the crew through a series of actions to execute the desired abort. This process is even more difficult and time consuming in the absence of ground communications since the ground flight controllers have the analysis tools and information that is currently not available in the Shuttle cockpit. Crew workload specifically abort procedures will be greatly simplified with the implementation of the Space Shuttle Cockpit Avionics Upgrade (CAU) project. The intent of CAU is to maximize crew situational awareness and reduce flight workload thru enhanced controls and displays, and onboard abort assessment and determination capability. SAFM was developed to help satisfy the CAU objectives by providing the crew with dynamic information about the capability of the vehicle to perform a variety of abort options during ascent and entry. This paper- presents an overview of the SAFM application. As shown in Figure 1, SAFM processes the vehicle navigation state and other guidance information to provide the CAU displays with evaluations of abort options, as well as landing site recommendations. This is accomplished by three main SAFM components: the Sequencer Executive, the Powered Flight Function, and the Glided Flight Function, The Sequencer Executive dispatches the Powered and Glided Flight Functions to evaluate the vehicle's capability to execute the current mission (or current abort), as well as more than IS hypothetical abort options or scenarios. Scenarios are sequenced and evaluated throughout powered and glided flight. Abort scenarios evaluated include Abort to Orbit (ATO), Transatlantic Abort Landing (TAL), East Coast Abort Landing (ECAL) and Return to Launch Site (RTLS). Sequential and simultaneous engine failures are assessed and landing footprint information is provided during actual entry scenarios as well as hypothetical "loss of thrust now" scenarios during ascent.

Hu, Howard↗

NASA NTRS1997

Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications

Distributed-memory parallel computers dominate today's parallel computing arena. These machines, such as Intel Paragon, IBM SP2, and Cray Origin2OO, have successfully delivered high performance computing power for solving some of the so-called "grand-challenge" problems. Despite initial success, parallel machines have not been widely accepted in production engineering environments due to the complexity of parallel programming. On a parallel computing system, a task has to be partitioned and distributed appropriately among processors to reduce communication cost and to attain load balance. More importantly, even with careful partitioning and mapping, the performance of an algorithm may still be unsatisfactory, since conventional sequential algorithms may be serial in nature and may not be implemented efficiently on parallel machines. In many cases, new algorithms have to be introduced to increase parallel performance. In order to achieve optimal performance, in addition to partitioning and mapping, a careful performance study should be conducted for a given application to find a good algorithm-machine combination. This process, however, is usually painful and elusive. The goal of this project is to design and develop efficient parallel algorithms for highly accurate Computational Fluid Dynamics (CFD) simulations and other engineering applications. The work plan is 1) developing highly accurate parallel numerical algorithms, 2) conduct preliminary testing to verify the effectiveness and potential of these algorithms, 3) incorporate newly developed algorithms into actual simulation packages. The work plan has well achieved. Two highly accurate, efficient Poisson solvers have been developed and tested based on two different approaches: (1) Adopting a mathematical geometry which has a better capacity to describe the fluid, (2) Using compact scheme to gain high order accuracy in numerical discretization. The previously developed Parallel Diagonal Dominant (PDD) algorithm and Reduced Parallel Diagonal Dominant (RPDD) algorithm have been carefully studied on different parallel platforms for different applications, and a NASA simulation code developed by Man M. Rai and his colleagues has been parallelized and implemented based on data dependency analysis. These achievements are addressed in detail in the paper.

Sun, Xian-He↗

DOE OSTI2024

Performance Comparison of Machine Learning Models for Ultrasonic Nondestructive Evaluation of Alkali-Silica Reaction in Concrete

Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.

36 MATERIALS SCIENCE↗

NASA NTRS2010

SPOT Program

A Spacecraft Position Optimal Tracking (SPOT) program was developed to process Global Positioning System (GPS) data, sent via telemetry from a spacecraft, to generate accurate navigation estimates of the vehicle position and velocity (state vector) using a Kalman filter. This program uses the GPS onboard receiver measurements to sequentially calculate the vehicle state vectors and provide this information to ground flight controllers. It is the first real-time ground-based shuttle navigation application using onboard sensors. The program is compact, portable, self-contained, and can run on a variety of UNIX or Linux computers. The program has a modular objec-toriented design that supports application-specific plugins such as data corruption remediation pre-processing and remote graphics display. The Kalman filter is extensible to additional sensor types or force models. The Kalman filter design is also strong against data dropouts because it uses physical models from state and covariance propagation in the absence of data. The design of this program separates the functionalities of SPOT into six different executable processes. This allows for the individual processes to be connected in an a la carte manner, making the feature set and executable complexity of SPOT adaptable to the needs of the user. Also, these processes need not be executed on the same workstation. This allows for communications between SPOT processes executing on the same Local Area Network (LAN). Thus, SPOT can be executed in a distributed sense with the capability for a team of flight controllers to efficiently share the same trajectory information currently being computed by the program. SPOT is used in the Mission Control Center (MCC) for Space Shuttle Program (SSP) and International Space Station Program (ISSP) operations, and can also be used as a post -flight analysis tool. It is primarily used for situational awareness, and for contingency situations.

Smith, Jason T.↗

NASA NTRS2017

Reconfigurable Cellular Composite Structures for Lighter than Air Vehicles with Scalable Size and Endurance

Engineered non-stochastic cellular materials show promising characteristics on the laboratory scale,with nearly ideal specific stiffness and strength scaling at ultralight mass density. These propertiessuggest performance benefits in any application with combined stiffness and mass constraints, suchas air vehicles. We investigate here the application of re-configurable cellular composite materialsand structures to lighter than air vehicles. We describe the properties and applicability of these materials,provide an example analysis of governing loading conditions associated with airships, showan example optimization method for navigating the design space, and describe how recent advancesin cellular material manufacturing and reconfiguration enable system performance benefits includingnew concepts of operation. Lastly, we propose lighter than air vehicles that are assembled andmaintained in-flight, eliminating structural compromises associated with transitional flight modesand ground handling.Engineered non-stochastic cellular material properties suggest performance benefits in lighter than air vehicles due tostiffness and mass constraints that are intrinsic to the airship design problem. Recent advances in cellular materialmanufacturing and reconfiguration enable system performance benefits including new concepts of operation, such aslighter than air vehicles that are assembled and maintained in-flight, eliminating structural compromises associatedwith transitional flight modes and ground handling. Existing engineered cellular materials display properties allowinglarge large scale airships design as monocoque cellular solids. Inevitable improvements in cellular material propertiesand manufacturing will improve feasibility even further. Given the suggestion that the two most significant technologygaps exist across all current airship projects are manufacturing and assembly processes and ground handling [7],a strategy that encompasses construction and maintenance in flight could provide critical rephrasing of the systemdesign problem through these new concepts of operation. Refactoring of traditional manufacturing, operation, andservice process constraints could extend to other domains in aerospace systems and manufacturing in general.In future work, the complexity of the design task would benefit from a form of optimization in order to find themost suitable geometry for a chosen application. For example, the Sequential Least SQuares Programming (SLSQP)function from within the SciPy Minimize library is a multiobjective constrained optimization method that has beenapplied to fixed wing aircraft design. [17] In this situation it would allow for several objective functions such as drag,bending stiffness, buoyancy and cost of transport to be incorporated into a composite objective function.

Copplestone, Grace↗

DOE OSTI2025

Validating sequential Monte Carlo for gravitational-wave inference

Nested sampling (NS) is the preferred stochastic sampling algorithm for gravitational-wave inference for compact binary coalescences. It can handle the complex nature of the gravitational-wave likelihood surface and provides an estimate of the Bayesian model evidence. However, there is another class of algorithms that meets the same requirements, but has not been used for gravitational-wave analyses: sequential Monte Carlo (SMC), an extension of importance sampling that maps samples from an initial density to a target density via a series of intermediate densities. In this work, we validate a type of SMC algorithm, called persistent sampling (PS), for gravitational-wave inference. We consider a range of different scenarios including binary black holes and binary neutron stars and real and simulated data and show that PS produces results that are consistent with NS whilst being, on average, 2 times more efficient and 2.74 times faster. This demonstrates that PS is a viable alternative to NS that should be considered for future gravitational-wave analyses.

black hole mergers↗