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

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NASA NTRS1998

The X-33 range Operations Control Center

This paper describes the capabilities and features of the X-33 Range Operations Center at NASA Dryden Flight Research Center. All the unprocessed data will be collected and transmitted over fiber optic lines to the Lockheed Operations Control Center for real-time flight monitoring of the X-33 vehicle. By using the existing capabilities of the Western Aeronautical Test Range, the Range Operations Center will provide the ability to monitor all down-range tracking sites for the Extended Test Range systems. In addition to radar tracking and aircraft telemetry data, the Telemetry and Radar Acquisition and Processing System is being enhanced to acquire vehicle command data, differential Global Positioning System corrections and telemetry receiver signal level status. The Telemetry and Radar Acquisition Processing System provides the flexibility to satisfy all X-33 data processing requirements quickly and efficiently. Additionally, the Telemetry and Radar Acquisition Processing System will run a real-time link margin analysis program. The results of this model will be compared in real-time with actual flight data. The hardware and software concepts presented in this paper describe a method of merging all types of data into a common database for real-time display in the Range Operations Center in support of the X-33 program. All types of data will be processed for real-time analysis and display of the range system status to ensure public safety.

Shy, Karla S.↗

NASA NTRS2004

X Persei: The X-Ray Halo and Spectrum of a High-Latitude X-Ray Binary

The observations were completed on February 25,2003. Although the source was in the FOV for 31.4 ksec, only 18.2 ksec of data were usable due to a strong flare in the first part of the observations. We have extracted the X-ray halo from the good portion of the data, and were then faced with the problem of calibrating the far-off-axis point spread function, which is needed only for X-ray halo analysis; the same problem affected Chandra halo observations. We used data from 3C273, MCG 6-30-15, LMC X-1, and Her X-1 to measure the PSF, and found that it is reasonably well fit with a power law of the form PSF(theta) = A theta^-G, where A = 0.0034 arcmin^-2, and G = 3.05 for energies between 1-4 keV. This suggests there are fewer large dust grains along the When fitting the spectrum of X Persei, we found NH = 3e21 cm^-2, as expected. However, the X-ray halo (using a Mathis, Rumpl, Nordsieck 1977 dust model) required at most a column density of 1.4+/-0.1 e21 cm^-2; other models required sightline to X Per than would have been expected. In addition, a smoothly distributed dust model fit the observations better than a single cloud model, also against our expectations. We are in the process of writing a paper to be submitted to ApJ with these results, and will also present them at the 2004 HEAD meeting in New Orleans.

Mushotzky, Richard↗

NASA NTRS2011

An Overview of the GEOS-5 Aerosol Reanalysis

GEOS-5 is the latest version of the NASA Global Modeling and Assimilation Office (GMAO) earth system model. GEOS-5 contains components for atmospheric circulation and composition (including data assimilation), ocean circulation and biogeochemistry, and land surface processes. In addition to traditional meteorological parameters, GEOS-5 includes modules representing the atmospheric composition, most notably aerosols and tropospheric/stratospheric chemical constituents, taking explicit account of the impact of these constituents on the radiative processes of the atmosphere. MERRA is a NASA meteorological reanalysis for the satellite era (1979-present) using GEOS-5. This project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales. As a first step towards an integrated Earth System Analysis (IESA), the GMAO is extending MERRA with reanalyses for other components of the earth system: land, ocean, bio-geochemistry and atmospheric constituents. In this talk we will present results from the MERRA-driven aerosol reanalysis covering the Aqua period (2003-present). The assimilation of Aerosol Optical Depth (AOD) in GEOS-5 involves very careful cloud screening and homogenization of the observing system by means of a Neural Net scheme that translates MODIS radiances into AERONET calibrated AOD. These measurements are further quality controlled using an adaptive buddy check scheme, and assimilated using the Local Displacement Ensemble (LDE) methodology. For this reanalysis, GEOS-5 runs at a nominal 50km horizontal resolution with 72 vertical layers (top at approx. 8Skm). GEOS-5 is driven by daily biomass burning emissions derived from MODIS fire radiative power retrievals. We will present a summary of our efforts to validate such dataset. The GEOS-5 assimilated aerosol fields are first validated by comparison to independent in-situ measurements (AERONET and PM2.5 surface concentrations). In order to asses aerosol absorption on a global scale, we perform a detailed radiative transfer calculation to simulate the UV aerosol index, comparing our results to OMI measurements. By simulating aerosol attenuated backscatter, we use CALIPSO measurements to evaluate the vertical structure of our aerosol estimates, in particular in regions where we have larger discrepancies with OMI. Finally, the consistency of our AOD estimates with estimates from MISR, MODIS/Deep Blue, OMI and PARASOL will be briefly discussed.

da Silva, Arlindo↗

NASA NTRS2011

Orbit Determination and Navigation Software Testing for the Mars Reconnaissance Orbiter

During the extended science phase of the Mars Reconnaissance Orbiter's lifecycle, the operational duties pertaining to navigation primarily involve orbit determination. The orbit determination process utilizes radiometric tracking data and is used for the prediction and reconstruction of MRO's trajectories. Predictions are done twice per week for ephemeris updates on-board the spacecraft and for planning purposes. Orbit Trim Maneuvers (OTM-s) are also designed using the predicted trajectory. Reconstructions, which incorporate a batch estimator, provide precise information about the spacecraft state to be synchronized with scientific measurements. These tasks were conducted regularly to validate the results obtained by the MRO Navigation Team. Additionally, the team is in the process of converting to newer versions of the navigation software and operating system. The capability to model multiple densities in the Martian atmosphere is also being implemented. However, testing outputs among these different configurations was necessary to ensure compliance to a satisfactory degree.

Deep Space Network↗

NASA NTRS2018

SLS Model Based Design: A Navigation Perspective

The SLS Program has implemented a Model-based Design (MBD) and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team is responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1B design, the additional GPS Receiver hardware model is managed as a DMM at the vehicle design level. This paper describes the models, and discusses the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the navigation components.

Oliver, T. Emerson↗

NASA NTRS2019

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗

NASA NTRSDate not supplied

TPSAS-NF1676L-32709-DND

Outline - Process-Structure-Performance Framework - Process-Specific Defects in selective laser melting (SLM) additive manufacturing (AM) process - Idealized Keyhole/Entrapped gas pores - Idealized Lack of Fusion (LoF) pores - Influence of Pore Geometry on Strain Localization - 3D Model of LoF pores - Partial validation of the 3D LoF 2 model

Saikumar R Yeratapally↗

NASA NTRSDate not supplied

An Overview of the Patch Integral Method (PIM), a New Heat Transfer Analysis Tool for Hypersonic Wind Tunnel Facilities at NASA Langley

NASA Langley’s hypersonic wind tunnels are heavily leveraged for planetary missions. The data collection method in these tunnels is thermography, and surface temperature measurements of the model surface are collected and reduced to produce surface heating data, as seen in Fig 1. However, during model injection, no temperature data are collected, and thus conventional, integral heat transfer methods cannot be used to solve for surface heating. A method was developed in the 1990’s to reduce this data despite the data gap, known as the step approximation method. The method assumes that the film coefficient behaves as a step function, the model is semi-infinite, and thermal properties are constant. With these simplifying assumptions, a Laplace transform can be performed to result in an equation that takes the initial temperature of the model and a temperature at some point in time to back out the film coefficient at that time. This is the method that is used in the current thermographic data reduction software, IHEAT. While computationally light-weight, the step approximation has several issues associated with it. The time-history of temperature is not accounted for, which is vital as heat transfer is an integral process. Additionally, the required semi-infinite assumption is unnecessary and might be violated during runtime. Thermal variation of material properties can have a sizeable impact on heating results and are not modeled by the method. This method also takes multiple seconds to “collapse” to a steady state, which is undesirable from both a facility and data reduction standpoint. The method is also very sensitive to the “effective time” approximation, an approximation of when heating instantaneously starts (which is a nonphysical simplification), and a small variation in this value can result in an error in heating results.

J. S. Cheatwood↗

NASA NTRS2018

GMI-IPS: Processing & Visualization Software Used in ATom DC-8 Aircraft Studies

NASA's Atmospheric Tomography Mission (ATom) deployed in each of the four seasons during 2016-2018, the DC-8 aircraft in order to establish global-scale datasets intended to improve the representation of chemically reactive gases in global atmospheric chemistry models (ACMs). The Global Modeling Initiative (GMI) executed simulations for each ATom flight using the GMI Chemistry Transport Model (GMI-CTM) to provide species concentrations of chemical gases along the DC-8 flight transects. To solve the problem of translating the GMI-CTM simulation data to the unique spatial resolutions of each ATom flight, the GMI ICARTT Processing Software (GMI-IPS) was developed.The GMI-IPS is written in Python and provides data processing, flight extraction, and visualization support for aircraft research projects using ICARTT format, which is a standard format for airborne instrument data. Additionally, the GMI-IPS interpolates global gridded model data from Hierarchical Data Format (HDF) to ICARTT compatible flight transects. Software classes for instruments and collections provided by the ATom DC-8 aircraft such as MER10, MMS, etc. are derived from a common base class. Other functionality provided by the GMI-IPS are: deriving missing flight entries along a transect, reading ICARTT entries from file, and providing Python data structures for storing flight and model information, and more.The GMI-IPS is GIT source controlled, has approximately 30,000 lines of code, and supports parallelization across data collections. It delivered GMI-CTM data for more than forty distinct DC-8 aircraft flights that took place under ATom. The output ICARTT files adhere to format standard V1.1, and pass the scan utility provided by NASA LaRC Airborne Science Data for Atmospheric Composition. This presentation will include a software and methods overview, and results from ATom, including assessments using the GMI-CTM showing how well observations from ATom flight transects represent a broader region.

Damon, M. R.↗

DOE OSTI2025

COCOMO2: A Coarse-Grained Model for Interacting Folded and Disordered Proteins

Biomolecular interactions are essential in many biological processes, including complex formation and phase separation processes. Coarse-grained computational models are especially valuable for studying such processes via simulation. Here, we present COCOMO2, an updated residue-based coarse-grained model that extends its applicability from intrinsically disordered peptides to folded proteins. This is accomplished with the introduction of a surface exposure scaling factor, which adjusts interaction strengths based on solvent accessibility, to enable the more realistic modeling of interactions involving folded domains without additional computational costs. COCOMO2 was parametrized directly with solubility and phase separation data to improve its performance on predicting concentration-dependent phase separation for a broader range of biomolecular systems compared to the original version. COCOMO2 enables new applications including the study of condensates that involve IDPs together with folded domains and the study of complex assembly processes. COCOMO2 also provides an expanded foundation for the development of multiscale approaches for modeling biomolecular interactions that span from residue-level to atomistic resolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Correction to “COCOMO2: A Coarse-Grained Model for Interacting Folded and Disordered Proteins”

Molecular interactions↗

NASA NTRS2024

Helium Conservation by Diffusion Limited Purging of Liquid Hydrogen Tanks

Recently, the new 1.2-million-gallon liquid hydrogen (LH 2 ) storage tank at the Kennedy Space Center Launch Complex 39 was purged, replacing nitrogen with helium, using a piston purge process. This purging approach had been used on Space Shuttle External Tanks (ET) in the past, but not on one of the large LH 2 tanks. The result was a huge success, potentially saving more than 1 million cubic feet of helium and significant labor. To better understand this result, a diffusion-based purge model was developed. The model predictions accurately match the helium concentration data, providing understanding of the helium savings and suggesting how to better optimize the purging of this large tank for future operations. The model was then applied to the piston purging of the Space Shuttle ETs, showing that these purges were not optimal, but that the amount of wasted helium was not excessive and that additional helium might have been saved by small changes to the process. The Space Shuttle Program (SSP) has ended, but these results are applicable to the purging of future large cylindrical LH 2 tanks. Finally, data have been obtained on inerting the Space Launch System (SLS) Core Stage (CS) LH 2 tank, replacing hydrogen with helium after an aborted launch. This is a more complicated case, but the model predicts that substantial helium might be saved by modifying the current purging process.

Helium Conservation↗

NASA NTRS1989

New atmospheric sensor analysis study

The functional capabilities of the ESAD Research Computing Facility are discussed. The system is used in processing atmospheric measurements which are used in the evaluation of sensor performance, conducting design-concept simulation studies, and also in modeling the physical and dynamical nature of atmospheric processes. The results may then be evaluated to furnish inputs into the final design specifications for new space sensors intended for future Spacelab, Space Station, and free-flying missions. In addition, data gathered from these missions may subsequently be analyzed to provide better understanding of requirements for numerical modeling of atmospheric phenomena.

Parker, K. G.↗

DOE OSTI2026

Advancing Industry 4.0: Multimodal Sensor Fusion for AI-Based Fault Detection in 3D Printing

Additive manufacturing, particularly fused deposition modeling, is transforming modern production by enabling rapid prototyping and complex part fabrication. However, its layer-by-layer process remains vulnerable to faults such as nozzle clogging, filament runout, and layer misalignment, which compromise print quality and reliability. Traditional inspection methods are costly, time-intensive, and often limited to post-process analysis, making them unsuitable for real-time intervention. In this current study, the authors developed a novel, low-cost, and portable faultdetection system that leverages multimodal sensor fusion and artificial intelligence for real-time monitoring in FDM-based 3D printing. The system integrates acoustic, vibration, and thermal sensing into a non-intrusive architecture, capturing complementary data streams that reflect both mechanical and process-related anomalies. Acoustic and thermal sensors operate in a fully contactless manner, while the vibration sensor requires minimal attachment such that it will not interfere with printer hardware, thereby preserving portability and ease of deployment. The multimodal signals are processed into spectrograms and time-frequency features, which are classified using convolutional neural networks for intelligent fault detection. The proposed system advances Industry 4.0 objectives by offering an affordable, scalable, and practical monitoring solution that improves faultdetection accuracy, reduces waste, and supports sustainable, adaptive manufacturing.

42 ENGINEERING↗

DOE OSTI2024

Multiscale Modeling of Vinyl-Addition Polynorbornenes: The Effect of Stereochemistry

Vinyl-addition polynorbornenes are candidates for designing high-performance polymers due to unique characteristics, which include a high glass transition temperature associated with a rigid backbone. Recent studies have established that the processability and properties of these polymers can be fine-tuned by using targeted substitutions. However, synthesis with different catalysts results in materials with distinct properties, potentially due to the presence of various stereoisomers that are difficult to quantify experimentally. Herein, we develop all-atom models of polynorbornene oligomers based on classical force fields and density functional theory. To establish the relationship between chemical architecture, chain conformations, and melt structure, we perform detailed molecular dynamics simulations with the fine-tuned atomistic force field and propose simpler coarse-grained descriptions to address the high molecular weight limit. All-atom simulations of oligomers suggest high glass transition temperatures in the range of 550–600 K. In the melt state (800 K), meso chains form highly rigid extended coils (C∞≈11) with amorphous structural characteristics similar to the X-ray diffraction data observed in the literature. In contrast, simulations with racemo chains predict highly helical tubular chain conformations that could promote assembly into crystalline structures.

Polymer Science↗

DOE OSTI2026

Measurements of $\textrm{t}\overline{\textrm{t}}\textrm{W}$ differential cross sections and the leptonic charge asymmetry at $\sqrt{s}=13$ TeV

Measurements of properties of top quark-antiquark pair production in association with a W boson in proton-proton collisions at a center-of-mass energy of 13 TeV are presented, using a data sample corresponding to an integrated luminosity of 138 fb −1 , recorded by the CMS experiment at the CERN LHC. Events are selected based on the presence of either two leptons with the same electric charge or three leptons, and multiple jets and b-tagged jets. We present measurements of differential production cross sections as a function of kinematic variables sensitive to different aspects of the process modeling, using a multivariate discriminator in the two-lepton selection region and a simple selection-based method in the three-lepton region. The normalized cross section measurements are generally consistent with the standard model expectations, while we observe larger values compared to the expectations in the absolute cross section measurements, consistent with previous inclusive cross section measurements. In addition, we measure the leptonic charge asymmetry of this process, obtaining an observed value of ${A}_c^{\ell }=-{0.19}_{-0.18}^{+0.16}$, consistent with the expectation of −0.085 ± 0.006 predicted by next-to-leading order simulations.

Hadron-Hadron Scattering↗

DOE OSTI2025

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

NASA NTRS2002

Using Monte-Carlo Simulations to Study the Disk Structure in Cygnus X-1

As the first dynamically determined black hole X-ray binary system, Cygnus X-1 has been studied extensively. However, its broad-band spectra in hard state with BeppoSAX is still not well understood. Besides the soft excess described by the multi-color disk model (MCD), the power- law component and a broad excess feature above 10 keV (disk reflection component), there is also an additional soft component around 1 keV, whose origin is not known currently.We propose that the additional soft component is due to the thermal Comptonization process between the s oft disk photon and the warm plasma cloud just above the disk.i.e., a warm layer. We use Monte-Carlo technique t o simulate this Compton scattering process and build several table models based on our simulation results.

Yao, Y.↗