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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

ERS-1 and Seasat scatterometer measurements of ocean winds: Model functions and the directional distribution of short waves

Calculation of accurate vector winds from scatterometers requires knowledge of the relationship between backscatter cross-section and the geophysical variable of interest. As the detailed dynamics of wind generation of centimetric waves and radar-sea surface scattering at moderate incidence angles are not well known, empirical scatterometer model functions relating backscatter to winds must be developed. Less well appreciated is the fact that, given an accurate model function and some knowledge of the dominant scattering mechanisms, significant information on the amplitudes and directional distributions of centimetric roughness elements on the sea surface can be inferred. accurate scatterometer model functions can thus be used to investigate wind generation of short waves under realistic conditions. The present investigation involves developing an empirical model function for the C-band (5.3 GHz) ERS-1 scatterometer and comparing Ku-band model functions with the C-band model to infer information on the two-dimensional spectrum of centimetric roughness elements in the ocean. The C-band model function development is based on collocations of global backscatter measurements with operational surface analyses produced by meteorological agencies. Strengths and limitations of the method are discussed, and the resulting model function is validated in part through comparison with the actual distributions of backscatter cross-section triplets. Details of the directional modulation as well as the wind speed sensitivity at C-band are investigated. Analysis of persistent outliers in the data is used to infer the magnitudes of non-wind effects (such as atmospheric stratification, swell, etc.). The ERS-1 C-band instrument and the Seasat Ku-band (14.6 GHz) scatterometer both imaged waves of approximately 3.4 cm wavelength assuming that Bragg scattering is the dominant mechanism. Comparisons of the C-band and Ku-band model functions are used both to test the validity of the postulated Bragg mechanism and to investigate the directional distribution of the imaged waves under a variety of conditions where Bragg scatter is dominant.

Freilich, Michael H.↗
NASA NTRS2010

The Development of MSFC Usability Lab

This conference poster reviews the development of the usability lab at Marshall Space Flight Center. The purpose of the lab was to integrate a fully functioning usability laboratory to provide a resource for future human factor assessments. and to implement preliminary usability testing on a MSFC website to validate the functionality of the lab.

Cheng, Yiwei↗
NASA NTRS1990

Validation of the F-18 high alpha research vehicle flight control and avionics systems modifications

The verification and validation process is a critical portion of the development of a flight system. Verification, the steps taken to assure the system meets the design specification, has become a reasonably understood and straightforward process. Validation is the method used to ensure that the system design meets the needs of the project. As systems become more integrated and more critical in their functions, the validation process becomes more complex and important. The tests, tools, and techniques which are being used for the validation of the high alpha research vehicle (HARV) turning vane control system (TVCS) are discussed and the problems and their solutions are documented. The emphasis of this paper is on the validation of integrated system.

Chacon, Vince↗
NASA NTRS1990

Validation of the F-18 high alpha research vehicle flight control and avionics systems modifications

The verification and validation process is a critical portion of the development of a flight system. Verification, the steps taken to assure the system meets the design specification, has become a reasonably understood and straightforward process. Validation is the method used to ensure that the system design meets the needs of the project. As systems become more integrated and more critical in their functions, the validation process becomes more complex and important. The tests, tools, and techniques which are being used for the validation of the high alpha research vehicle (HARV) turning valve control system (TVCS) are discussed, and their solutions are documented. The emphasis of this paper is on the validation of integrated systems.

Chacon, Vince↗
NASA NTRS2006

HALE UAS Command and Control Communications: Step 1 - Functional Requirements Document. Version 4.0

The High Altitude Long Endurance (HALE) unmanned aircraft system (UAS) communicates with an off-board pilot-in-command in all flight phases via the C2 data link, making it a critical component for the UA to fly in the NAS safely and routinely. This is a new requirement in current FAA communications planning and monitoring processes. This document provides a set of comprehensive C2 communications functional requirements and performance guidelines to help facilitate the future FAA certification process for civil UAS to operate in the NAS. The objective of the guidelines is to provide the ability to validate the functional requirements and in future be used to develop performance-level requirements.

Source record↗
NASA NTRS2015

Pilot Field Test Study

The Field Test study is currently in full swing, preceded by the successful completion of the Pilot Field Test study that paved the way for collecting data on the astronauts in the medical tent in Kazakhstan. Abigail Sherriff worked alongside Logan Dobbe on one Field Test aspect to determine foot clearance over obstacles (5cm, 10cm, and 15cm) using APDM Inc. Internal Measurement Units (IMU) worn by the astronauts. They created a program to accurately calculate foot clearance using the accelerometer, magnetometer, and gyroscope data with the IMUs attached to the top of the shoes. To validate the functionality of their program, they completed a successful study on test subjects performing various tasks in an optical motion studio, considered a gold standard in biomechanics research. Future work will include further validation and expanding the program to include other analyses.

Sherriff, Abigail↗
DOE OSTI2024

Unlocking the distinctive enzymatic functions of the early plant biomass deconstructive genes in a brown rot fungus by cell-free protein expression

ABSTRACT Saprotrophic fungi that cause brown rot of woody biomass evolved a distinctive mechanism that relies on reactive oxygen species (ROS) to kick-start lignocellulosic polymers’ deconstruction. These ROS agents are generated at incipient decay stages through a series of redox relays that shuttle electrons from fungus’s central metabolism to extracellular Fenton chemistry. A list of genes has been suggested encoding the enzyme catalysts of the redox processes involved in ROS’s function. However, navigating the functions of the encoded enzymes has been challenging due to the lack of a rapid method for protein synthesis. Here, we employed cell-free expression system to synthesize four redox or degradative enzymes, which were identified, by transcriptomic data, as conserved players of the ROS oxidation phase across brown rot fungal species. All four enzymes were successfully expressed and showed activities that enable confident assignment of function, namely, benzoquinone reductase (BQR), ferric reductase, α-L-arabinofuranosidase (ABF), and heme-thiolate peroxidase (HTP). Detailed analysis of their catalytic features within the context of brown rot environments allowed us to interpret their roles during ROS-driven wood decomposition. Specifically, we validated the functions of BQR as the driver redox enzyme of Fenton cycles and reconstructed its interactions with the co-occurring HTP or laccase and ABF. Taken together, this research demonstrated that the cell-free expression platform is adequate for synthesizing functional fungal enzymes and provided an alternative route for the rapid characterization of fungal proteins, escalating our understanding of the distinctive biocatalyst system for plant biomass conversion. IMPORTANCE Brown rot fungi are efficient wood decomposers in nature, and their unique degradative systems harbor untapped catalysts pursued by the biorefinery and bioremediation industries. While the use of “omics” platforms has recently uncovered the key “oxidative-hydrolytic” mechanisms that allow these fungi to attack lignocellulose, individual protein characterization is lagging behind due to the lack of a robust method for rapid synthesis of crucial fungal enzymes. This work delves into the studies of biochemical functions of brown rot enzymes using a rapid, cell-free expression platform, which allowed the successful depictions of enzymes’ catalytic features, their interactions with Fenton chemistry, and their roles played during the incipient stage of brown rot when fungus sets off the reactive oxygen species for oxidative degradation. We expect this research could illuminate cell-free protein expression system’s use to fulfill the increasing need for functional studies of fungal enzymes, advancing the discoveries of novel biomass-converting catalysts.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2020

Design for Manufacturing Tool for Automated Fiber Placement Structures - Verification and Validation

A tool has been developed to address the growing Design for Manufacturing needs for composite structures, specifically those manufactured with automated fiber placement. This manufacturing approach presents unique challenges associated with puckers and wrinkling, tow overlaps and gaps, fiber deviation, and laminate strength. Achieving a satisfactory laminate design usually requires finding compromises between those four areas. The developed tool, dubbed the Central Optimizer, assists with the process of balancing competing design metrics in automated fiber placement. This tool was developed under the NASA Advanced Composites Consortium with input from industry partners. Under this program, the Central Optimizer has been exercised on three different structures to verify its functionality and validate ability to improve the design process for automated fiber placement structures.

August T Noevere↗
DOE OSTI2025

Transcription factor binding divergence drives transcriptional and phenotypic variation in maize

Regulatory elements are essential components of plant genomes that have shaped the domestication and improvement of modern crops. However, their identity, function and diversity remain poorly characterized, limiting our ability to harness their full power for agricultural advances using induced or natural variation. Here, in this study, we mapped transcription factor (TF) binding for 200 TFs from 30 families in two distinct maize inbred lines historically used in maize breeding. TF binding comparison revealed widespread differences between inbreds, driven largely by structural variation, that correlated with gene expression changes and explained complex quantitative trait loci such as Vgt1, an important determinant of flowering time, and DICE, an herbivore resistance enhancer. CRISPR–Cas9 editing of TF binding regions validated the function and structure of regulatory regions at various loci controlling plant architecture and biotic resistance. Our maize TF binding catalogue identifies functional regulatory regions and enables collective and comparative analysis, highlighting its value for agricultural improvement.

Galli, Mary [Rutgers Univ., Piscataway, NJ (United↗
NASA NTRS1993

CSI Flight Computer System and experimental test results

This paper describes the CSI Computer System (CCS) and the experimental tests performed to validate its functionality. This system is comprised of two major components: the space flight qualified Excitation and Damping Subsystem (EDS) which performs controls calculations; and the Remote Interface Unit (RIU) which is used for data acquisition, transmission, and filtering. The flight-like RIU is the interface between the EDS and the sensors and actuators positioned on the particular structure under control. The EDS and RIU communicate over the MIL-STD-1553B, a space flight qualified bus. To test the CCS under realistic conditions, it was connected to the Phase-0 CSI Evolutionary Model (CEM) at NASA Langley Research Center. The following schematic shows how the CCS is connected to the CEM. Various tests were performed which validated the ability of the system to perform control/structures experiments.

Sparks, Dean W., Jr.↗
NASA NTRS2018

Trusted Communication: Utilizing Speech Communication to Enhance Human-Machine Teaming Success

An area of increasing interest for the next generation of aircraft is autonomy and the integration of increasingly autonomous systems into the national airspace. Such an integration requires humans to work closely with autonomous systems, forming teams. Our hypothesis is that a team composed of both humans and autonomous systems will operate better than either entity alone. We have existing procedures for certifying pilots to operate in the national airspace and are currently working on methods for validating the function of autonomous systems, however we have no method in place for assessing the interaction of these two disparate systems. Communication is one avenue. This paper will examine the use of language as a metric for ascertaining human-machine teaming effectiveness. A proof-of-concept of the application of two communication-based analysis techniques, Linguistic Inquiry and Word Count (LIWC) and Latent Semantic Analysis (LSA), for the prediction of success in human/chatbot teaming was conducted. By running these analyses over data from the 2014 and 2015 Loebner Prize competitions of human/chatbot teaming, numerical scores were obtained that can be associated with scores provided by human judges during the competition. Correlating their LIWC and LSA data with the scores provided by the judges, and using linear regression over this correlation, formulae were obtained that predict the score of human/chatbot interaction. These formulae were tested over the 2013 Loebner Prize transcripts, determining that, though there was strong correlation between predicted and actual scores, the predictive success of this method was not strong. However, with specialized topic spaces and lexica, as well as larger data sets, the predictive power of these metrics will improve. Given the importance of providing metrics for human-machine system team success and given the promise shown by the communication-basedLIWCand LSAmethods, continuing research in this area is necessary. After examining the potential for using communication and spoken language as a metric for the success of human/autonomous system teaming, this paper then examines aspects inherent to communication systems that may contribute to unreliability and reduced trust. Modern natural language processing tools rely on deep learning algorithms to create language rules that produce accurate results, but these rules are uninterpretable. The resulting blackbox system lacks transparency necessary for full validation and complete trust. Additionally, speech-based interfaces pose other difficulties to developing coordinated teamwork between humans and autonomous systems. Human communication is infrequently limited to speech only, instead usually relying on a combination of verbal, gestural, and general body language communication. Reducing an analysis of team effectiveness to a study of spoken language alone is problematic as it leaves these other equally important forms of communication out. This paper will examine these problems and the general deficiencies in speech-based metrics for human-machine teaming.

E L Meszaros↗
DOE OSTI2024

Decoding the Pair Distribution Function of Uranium in Molten Fluoride Salts from X-Ray Absorption Spectroscopy Data by Machine Learning

Thermal properties of actinides in molten salts are linked to the strongly disordered local environment of actinide ions. Here, we illustrate both the limitations of the commonly used fitting method for analysis of extended X-ray absorption fine structure (EXAFS) spectra in molten UF 4 and a possible solution using an "objective neural network - EXAFS" (ONNE) method. ONNE provides both extraction of the pair distribution function, as validated by its application to the EXAFS spectra calculated on molecular dynamics trajectory, and the EXAFS data reconstruction. The ONNE analysis of the molten UF4 has revealed reduction of the first nearest neighbor U-F coordination number, expansion of the U-F bond length and smaller contribution to the second shell compared to its crystalline counterpart. This method is therefore an attractive alternative to conventional EXAFS analysis and molecular dynamics simulations for studies of disordered environment of actinides in molten salts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Exploring the Computational Aspects of Propylene Oligomerization Catalysis Using M′ 2 M Type Trimetallic MOF Nodes

Metal-organic frameworks have emerged as promising materials in the field of catalysis. They offer an optimal ground for screening catalysts and tailoring their catalytic properties. Here, in this work, via density functional theory (DFT) calculations, we investigated the catalytic activity of the trimetallic MOF nodes, M' 2 M for propylene oligomerization, by varying the active metal M from Sc to Cu with M' being Fe, aiming to grasp the impact of altering the active atoms on the catalyst's activity. Additionally, we examined how substituting the spectator atom, M', with other transition metals, i.e., from Sc to Cu, affects these energy barriers, keeping Ni as the active metal. We proposed several cases with lower or comparable energy barriers to the experimentally reported Fe 2 Ni trimetallic MOF node. In addition, we found a correlative relationship between spin-density from natural population analysis and energy barriers in the realm of C-C bond formation, whereby an elevation in spin-density is found to be inversely proportional to the magnitude of the energy barriers. Moreover, we calculated the energy barriers for C-C coupling and beta-hydride elimination using multireference NEVPT2 calculations on top of the CASSCF wave function to validate the rate-determining step that is predicted by DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Expediting field-effect transistor chemical sensor design with neuromorphic spiking graph neural networks

Improving the sensitive and selective detection of analytes in a variety of applications requires accelerating the rational design of field-effect transistor (FET) chemical sensors. Achieving high-performance detection relies on identifying optimal probe materials that can effectively interact with target analytes, a process traditionally driven by chemical intuition and time-consuming trial-and-error methods. To address the difficulties in probe screening for FET sensor development, this work presents a methodology that combines neuromorphic machine learning (ML) architectures, specifically a hybrid spiking graph neural network (SGNN), with an enriched dataset of physicochemical properties through semi-automated data extraction using large language models. Achieving a classification accuracy of 0.89 in predicting sensor sensitivity categories, the SGNN model outperformed traditional ML techniques by leveraging its ability to capture both global physicochemical properties and sparse topological features through a hybrid modeling framework. Next-generation sensor design was informed by the actionable insights into the connections between material properties and sensing performance offered by the SGNN framework. Through virtual screening for the detection of per- and polyfluoroalkyl substances (PFAS) as a use case, the effectiveness of the SGNN model was further validated. Density functional theory simulations confirmed graphene as a promising active material for PFAS detection as suggested by the SGNN framework. By bridging gaps in predictive modeling and data availability, this integrated approach provides a strong foundation for accelerating advancements in FET sensor design and innovation.

Ferreira, Rodrigo Pires [Univ. of Chicago, IL (Uni↗
DOE OSTI2025

Constraining primordial non-Gaussianity with DESI 2024 LRG and QSO samples

We analyse the large-scale clustering of the Luminous Red Galaxy (LRG) and Quasar (QSO) sample from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). In particular, we constrain the primordial non-Gaussianity (PNG) parameter f NL loc via the large-scale scale-dependent bias in the power spectrum using 1,631,716 LRGs (0.6 < z < 1.1) and 1,189,129 QSOs (0.8 < z < 3.1). This new measurement takes advantage of the enormous statistical power at large scales of DESI DR1 data, surpassing the latest data release (DR16) of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). For the first time in this kind of analysis, we use a blinding procedure to mitigate the risk of confirmation bias in our results. We improve the model of the radial integral constraint proposing an innovative technique allowing the correction through the window matrix convolution. We also carefully test the mitigation of the dependence of the target selection on the photometry qualities by incorporating an angular integral constraint contribution to the window function, and validate our methodology with the blinded data. Finally, combining the two samples, we measure f NL loc = -3.6 -9.1 +9.0 at 68% confidence, where we assume the universality relation for the LRG sample and a recent merger model for the QSO sample about the response of bias to primordial non-Gaussianity. Adopting the universality relation for the PNG bias in the QSO analysis leads to f NL loc = 3.5 -7.4 +10.7 at 68% confidence. Due to restricted selection in the LRG sample, the inclusion of the LRGs allows for 10% improvement. This measurement is the most precise determination of primordial non-Gaussianity using large-scale structure to date, surpassing the latest result from eBOSS by a factor of 2.3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dark Energy Survey Year 3 results: $w$CDM cosmology from simulation-based inference with persistent homology on the sphere

We present cosmological constraints from Dark Energy Survey Year 3 (DES Y3) weak lensing data using persistent homology, a topological data analysis technique that tracks how features like clusters and voids evolve across density thresholds. For the first time, we apply spherical persistent homology to galaxy survey data through the algorithm TopoS2, which is optimized for curved-sky analyses and HEALPix compatibility. Employing a simulation-based inference framework with the Gower Street simulation suite, specifically designed to mimic DES Y3 data properties, we extract topological summary statistics from convergence maps across multiple smoothing scales and redshift bins. After neural network compression of these statistics, we estimate the likelihood function and validate our analysis against baryonic feedback effects, finding minimal biases (under $0.3σ$) in the $Ω_\mathrm{m}-S_8$ plane. Assuming the $w$CDM model, our combined Betti numbers and second moments analysis yields $S_8 = 0.821 \pm 0.018$ and $Ω_\mathrm{m} = 0.304\pm0.037$-constraints 70% tighter than those from cosmic shear two-point statistics in the same parameter plane. Our results demonstrate that topological methods provide a powerful and robust framework for extracting cosmological information, with our spherical methodology readily applicable to upcoming Stage IV wide-field galaxy surveys.

Prat, J. [Nordita; Royal Inst. Tech., Sodertalje; ↗
DOE OSTI2026

Quantum speed limit for the out-of-time-ordered correlator from an open-system perspective

Scrambling, the delocalization of initially localized quantum information, is commonly characterized by the out-of-time-ordered correlator (OTOC). Employing the OTOC–Renyi-2 entropy theorem, we derive a quantum speed limit for the OTOC, which sets a lower bound for the rate with which information can be scrambled. This bound becomes particularly tractable by describing the scrambling of information in a closed quantum system as an effective decoherence process of an open system interacting with an environment. We prove that decay of the OTOC can be bounded by the strength of the system-environment coupling and two-point environmental correlation functions. We validate our analytic bound numerically using the nonintegrable transverse field Ising model. Furthermore, our results provide a universal and model-agnostic quantitative framework for understanding the dynamical limits of information spreading across quantum many-body physics, condensed matter systems, and engineered quantum platforms.

Fermions↗
DOE OSTI2026

Poxvirus infection triggers remodeling of host m⁶A epitranscriptome and benefits from the m⁶A regulatory responses

Understanding how host gene regulation responds to viral infection is essential for developing effective antiviral strategies. Emerging evidence suggests that host transcripts undergo dynamic chemical modifications to counteract viral invasion. Conversely, viruses that rely on nuclear transcription exploit host RNA methyltransferases to enhance mRNA export and translation. Orthopoxviruses, however, complete their entire replication cycle within compartmentalized cytoplasmic “factories” utilizing enzymes encoded by their large double-stranded viral DNA genomes. The dynamic interplay between host and poxviral epitranscriptome remains poorly characterized. Using a temporally resolved model of Vaccinia virus (VV) infection, we investigated host-virus interactions through transcriptome and N6-methyladenosine (m⁶A) epitranscriptome whole genome sequencing. We found that host m⁶A modifications respond rapidly to VV infection, preceding the delayed transcriptional changes that emerge at later stages. Early m⁶A signatures included key innate immunity factors as well as host genes involved in transcriptional regulation, post-transcriptional modification, and protein ubiquitination. Functional assays validated two host factors with early m⁶A modification changes that are essential for VV infection: a m⁶A reader, YTHDF1, and a component of the SCF E3 ubiquitin ligase complex, FBXO31. The m⁶A gain on YTHDF1 enhanced its protein expression and promoted efficient VV replication. In addition, we identified previously unrecognized roles of FBXO31 and the SCF E3 ligase complex in supporting VV infection. Temporal profiling of the m⁶A epitranscriptome reveals how VV exploits host post-transcriptional regulatory pathways, specifically m⁶A RNA modification and protein ubiquitination. These findings highlight critical host factors co-opted during poxvirus infection and identify potential targets for therapeutic intervention.

59 BASIC BIOLOGICAL SCIENCES↗