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At least 631 records · Page 35

Cluster Analysis of Thermal Icequakes Using the Seismometer to Investigate Ice and Ocean Structure (SIIOS): Implications for Ocean World Seismology

Ocean Worlds are of high interest to the planetary community due to the potential habitability of their subsurface oceans. Over the next few decades several missions will be sent to ocean worlds including the Europa Clipper, Dragonfly, and possibly a Europa lander. The Dragonfly and Europa lander missions will carry seismic payloads tasked with detecting and locating seismic sources. The Seismometer to Investigate Ice and Ocean Structure (SIIOS) is a NASA PSTAR funded project that investigates ocean world seismology using terrestrial analogs. The goals of the SIIOS experiment include quantitatively comparing flight-candidate seismometers to traditional instruments, comparing single-station approaches to a small-aperture array, and characterizing the local seismic environment of our field sites. Here we present an analysis of detected local events at our field sites at Gulkana Glacier in Alaska and in Northwest Greenland approximately 80 km North of Qaanaaq, Greenland. Both field sites passively recorded data for about two weeks. We deployed our experiment on Gulkana Glacier in September 2017 and in Greenland in June 2018. At Gulkana there was a nearby USGS weather station which recorded wind data. Temperature data was collected using the MERRA satellite. In Greenland we deployed our own weather station to collect temperature and wind data. Gulkana represents a noisier and more active environment. Temperatures fluctuated around 0°C, allowing for surface runoff to occur during the day. The glacier had several moulins, and during deployment we heard several rockfalls from nearby mountains. In addition to the local environment, Gulkana is located close to an active plate boundary (relative to Greenland). This meant that there were more regional events recorded over two weeks, than in Greenland. Greenland’s local environment was also quieter, and less active. Temperatures remained below freezing. The Greenland ice was much thicker than Gulkana (~850 m versus ~100 m) and our stations were above a subglacial lake. Both conditions can reduce event detections from basal motion. Lastly, we encased our Greenland array in an aluminum vault and buried it beneath the surface unlike our array in Gulkana where the instruments were at the surface and covered with plastic bins. The vault further insulated the array from thermal and atmospheric events.

Marusiak, A. G.↗

NanoSIMS opens a New Window for Deciphering Organic Matter in Terrestrial and Extraterrestrial Samples

Recognition of the earliest morphological or chemical evidence of terrestrial life has proved to be challenging, as organic matter in ancient rocks is commonly fragmentary and difficult to distinguish from abiotically-produced materials (Schopf, 1993; Van Zuilen et al., 2002; Altermann & Kazmierczak, 2003; Cady et al., 2003; Brasier et al., 2002, 2004, 2005; Hofmann, 2004; Skrzypczak et al., 2004, 2005). Yet, the ability to identify remnants of earliest life is critical to our understanding of the timing of life's origin on earth, the nature of earliest terrestrial life, and recognition of potential remnants of microbial life that might occur in extraterrestrial materials. The search for earliest life on Earth now extends to early Archean organic remains; these tend to be very poorly preserved and considerably more difficult to interpret than the delicately permineralized microfossils known from many Proterozoic deposits. Thus, recent efforts have been directed toward finding biosignatures that can help distinguish fragmentary remnants of ancient microbes from either pseudofossils or abiotic organic materials that may have formed hydrothermally or in extraterrestrial processes (House et al., 2000; Boyce et al., 2001; Kudryavtsev et al., 2001; Schopf, 2002; Schopf et al., 2002, 2005a,b; Cady et al., 2003; Garc a-Ruiz et al., 2003; Hofmann, 2004; Brasier et al., 2005; Rushdi and Simoneit, 2005; Skrzypczak et al., 2005). An exciting area of biosignature research involves the developing technology of NanoSIMS. NanoSIMS is secondary ion mass spectrometry (SIMS) for ultrafine feature, elemental and isotopic analysis. Its resolution approaches 0.05 micrometers for element mapping, which is 10-50 times finer than that attainable with conventional SIMS or electron microprobes. Consequently, NanoSIMS has the potential to reveal previously unknown, chemical and structural characteristics of organic matter preserved in geologic materials. Robert et al. (2005) were the first to combine NanoSIMS element maps with optical microscopic imagery in an effort to develop a new method for assessing biogenicity. They showed that the ability to simultaneously map the distribution of organic elements [such as carbon (C), nitrogen (N), and sulfur (S)] and compare those element distributions with optically recognizable, cellularly preserved fossils could provide significant new insights into the origin of organic materials in ancient sediments. This chapter details a recent NanoSIMS study which was designed to acquire new data relevant to establishing critical biosignatures (Oehler et al., 2006a-c). In this study, NanoSIMS was used to characterize element distributions of spheroidal and filamentous microfossils and associated organic laminae in chert from the approx. 0.85 billion year old (Ga) Bitter Springs Formation of Australia. Previous work established preservation of a diverse microbiota in the Bitter Springs Formation (Schopf, 1968; Schopf and Blacic, 1971), and there is no dispute within the scientific community regarding the biogenicity of any of the Bitter Springs structures evaluated in this new study. Thus, the NanoSIMS results described below provide new insight into - and can be used as a guide for assessing - the origin of less well understood organic materials that may occur in early Archean samples and in meteorites or other extraterrestrial samples.

Oehler, Dorothy ZS.↗

Deep Learning Scene Classification Experiments in Automatic Detection of Slums on Planetscope Imagery

Population growth is increasingly happening in slum settlements of the large urban centers in the Global South. The term "slum" encompasses a wide range of communities, located mostly in underserved areas, and often exhibiting distinct structural and functional informalities with a relatively high concentration of marginalized populations. To address the issues confronting slums for effective planning and development, including the realistic estimation of the resident population, identifying them accurately is fundamental. Given the disagreements over a universal definition, diverse characteristic features, and socio-political limitations, global detection of slums is a veritable challenge. In this paper, we present experiments in slum detection using a scene classification algorithm and 3-meter spatial resolution satellite imagery. We train and evaluate the model for slum detection in Mumbai, India for the year 2023 and test the temporal generalization of the trained model on Mumbai in 2020 and 2018. In addition, we explore the pathways toward geographic generalization to Kolkata and Delhi (India). We discuss several limitations in the workflow and model, situate our findings in the existing literature, and suggest improvements and alternatives. With this, we establish baseline methods and experiments as a first step towards developing an image-based global slum detection framework and algorithm. This work adds to the community discussion on methods, data challenges, and open questions related to the detection of slums globally. With this research, we hope to improve our understanding of human settlements, especially in critical areas, improve population estimates, and help measure progress towards the sustainable development goals.

Arndt, Jacob↗

RCSB protein data Bank: Next‐generation advanced search for exploration of experimental structures and computed structure models

Abstract The Protein Data Bank (PDB), established in 1971, is the primary global, open‐access archive for experimentally determined 3D macromolecular structures (proteins, RNA, DNA). The research‐focused RCSB.org web‐portal provides access to these data alongside more than one million machine‐learning‐predicted structure models, greatly expanding the available structural landscape. Rapid growth of both experimental and computational structures has increased the need for powerful yet accessible search tools that serve a broad and diverse scientific community. Herein, we describe a redesigned RCSB Protein Data Bank RCSB.org Advanced Search capability that supports intuitive discovery of 3D structures through a unified interface. This interface integrates annotation‐, sequence‐, and 3D structure‐based searches, embeds an interactive 3D viewer, and incorporates curated biological knowledge, such as catalytic site definitions from Mechanism and Catalytic Site Atlas and ligand‐guided structural motifs, for constructing geometry‐driven queries. A new Chemical Search tool allows definition of chemical queries via an integrated drawing tool or standard identifiers, seamlessly combining them with annotation filters. By allowing query definition directly within spatial and chemical contexts, these search interfaces reduce the need for detailed knowledge of residue numbering, chain identifiers, or external cheminformatics software. This capability enables efficient exploration of structures, chemical diversity, and structure–function relationships across all life domains. The redesigned interfaces can be accessed directly at rcsb.org/search/advanced for Advanced Search and rcsb.org/search/chemical for Chemical Search.

Rose, Yana [Research Collaboratory for Structural ↗

Synthetic Soil Aggregates: Bioprinted Habitats for High-Throughput Microbial Metaphenomics

The dynamics of microbial processes are difficult to study in natural soil, owing to the small spatial scales on which microorganisms operate and to the opacity and chemical complexity of the soil habitat. To circumvent these challenges, we have created a 3D-bioprinted habitat that mimics aspects of natural soil aggregates while providing a chemically defined and translucent alternative culturing method for soil microorganisms. Our Synthetic Soil Aggregates (SSAs) retain the porosity, permeability, and patchy resource distribution of natural soil aggregates—parameters that are expected to influence emergent microbial community interactions. We demonstrate the printability and viability of several different microorganisms within SSAs and show how the SSAs can be integrated into a multi-omics workflow for single SSA resolution genomics, metabolomics, proteomics, lipidomics, and biogeochemical assays. We study the impact of the structured habitat on the distribution of a model co-culture microbial community and find that it is significantly different from the spatial organization of the same community in liquid culture, indicating a potential for SSAs to reproduce naturally occurring emergent community phenotypes. The SSAs have the potential as a tool to help researchers quantify microbial scale processes in situ and achieve high-resolution data from the interplay between environmental properties and microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗

Structural Analysis of Load-Bearing Components in Mars Science Helicopter

The successful demonstration of powered flight on Mars by Ingenuity has led to the development of next generation Martian rotorcraft. As technology advances from a technology demonstrator to possible expanded planetary science investigations, the potential to fly a high payload carrying rotorcraft relies on the capability to analyze and validate the structural integrity of the vehicle in addition to the rotor aerodynamic performance. The Mars Science Helicopter (MSH), a next generation hexacopter concept, is an example of a proposed vehicle that would perform science investigations independent of a land-based vehicle. To ensure the feasibility and viability of MSH mission performance, it is critical to mature the structural design of vehicle concepts to bridge the gap between the best practices of the spacecraft and aircraft communities. MSH was analyzed under operational and 26G quasi-static launch loads with different rotor arm and frame designs. Structural analysis results showed that rotor arms could be stiffened for significantly improved structural performance with minimal mass penalty, while the rotorcraft frame exhibited a more complex relationship between mass and launch load stresses due to the mass-dependent launch loads.

Vehicle↗

Toward a NASA Deep Space Optical Communications System

As discussed at SpaceOps in 2016, we expect the data rates from deep space missions to increase approximately one order of magnitude per decade for the next 50 years. The first order of magnitude improvement will come from existing plans for radio frequency (RF) communications including enhancements to both spacecraft and Deep Space Network (DSN) facilities. The next two orders of magnitude are predicted to come from the introduction of deep space optical communications. Studies indicate that optical receive apertures of between 8m12m are desired. The large cost of dedicated receive telescopes makes this method unrealistic – at least in the near-term. The cost of large optical ground terminals is driven primarily by the cost of the optics and by the cost of a stable structure for the telescope. We propose a novel hybrid design in which existing DSN 34m beam waveguide (BWG) radio antennas can be modified to include an 8m equivalent optical primary. By utilizing a low-cost segmented spherical mirror optical design, pioneered by the optical astronomical community, and by exploiting the already existing extremely stable large radio aperture structures in the DSN, we can minimize both of these cost drivers for implementing large optical communications ground terminals. Two collocated hybrid RF/optical antennas could be arrayed to synthesize the performance of an 11.3m receive aperture to support more capable or more distant space missions or used separately to communicate with two optical spacecraft simultaneously. NASA is in the midst of building six new 34m BWG antennas in the DSN. The final two are planned to be built at the DSN Goldstone, California and Canberra complexes. We are now investigating building these last two antennas as RF/optical hybrids. By delaying their operational dates by two years, we would be able to add the 8m optical receive capability for these two antennas while fitting within existing budgetary constraints. This paper describes the hybrid antenna design, the technical challenges being addressed, and plan for using this concept, together with ongoing work on optical flight terminals, to infuse operation optical communications into deep space missions.

Cornwell, Donald M.↗

Robotic Assembly of Truss Structures for Space Systems and Future Research Plans

Many initiatives under study by both the space science and earth science communities require large space systems, i.e. with apertures greater than 15 m or dimensions greater than 20 m. This paper reviews the effort in NASA Langley Research Center's Automated Structural Assembly Laboratory which laid the foundations for robotic construction of these systems. In the Automated Structural Assembly Laboratory reliable autonomous assembly and disassembly of an 8 meter planar structure composed of 102 truss elements covered by 12 panels was demonstrated. The paper reviews the hardware and software design philosophy which led to reliable operation during weeks of near continuous testing. Special attention is given to highlight the features enhancing assembly reliability.

Doggett, William↗

Ligand- and Structure-Based Analysis of Deep Learning-Generated Potential α2a Adrenoceptor Agonists

The α2a adrenoceptor is a particularly medically relevant subtype of the G protein-couple receptor family. Unfortunately, high-throughput techniques aimed at producing novel drug leads targeted to this receptor have been largely unsuccessful due to the complex pharmacology of adrenergic receptors. As such, cutting-edge in silico ligand- and structure-based assessment and de novo deep learning methods are well-positioned to provide new insights into protein-ligand interactions and potential active compounds. In this work, we (i) collect a dataset of α2a adrenoceptor agonists and provide it as a resource for the drug design community; (ii) use the dataset as a basis to generate candidate active structures via deep learning; and (iii) apply computational ligand- and structure-based analysis techniques to gain new insight into α2a adrenoceptor agonists and assess the quality of the computer-generated compounds. Additionally, we further describe how such assessment techniques can be applied to putative chemical probes with a case study involved proposed medetomidine-based probes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tundra Soil Viruses Mediate Responses of Microbial Communities to Climate Warming

The rise of global temperature causes the degradation of the substantial reserves of carbon (C) stored in tundra soils, in which microbial processes play critical roles. Viruses are known to influence the soil C cycle by encoding auxiliary metabolic genes and infecting key microorganisms, but their regulation of microbial communities under climate warming remains unexplored. In this study, we evaluated the responses of viral communities for about 5 years of experimental warming at two depths (15 to 25 cm and 45 to 55 cm) in the Alaskan permafrost region. Our results showed that the viral community and functional gene composition and abundances (including viral functional genes related to replication, structure, infection, and lysis) were significantly influenced by environmental conditions such as total nitrogen (N), total C, and soil thawing duration. Although long-term warming did not impact the viral community composition at the two depths, some glycoside hydrolases encoded by viruses were more abundant at both depths of the warmed plots. With the continuous reduction of total C, viruses may alleviate methane release by altering infection strategies on methanogens. Importantly, viruses can adopt lysogenic and lytic lifestyles to manipulate microbial communities at different soil depths, respectively, which could be one of the major factors causing the differences in microbial responses to warming. This study provides a new ecological perspective on how viruses regulate the responses of microbes to warming at community and functional scales.

54 ENVIRONMENTAL SCIENCES↗

Network structure of vertebrate scavenger assemblages at the global scale: drivers and ecosystem functioning implications

The organization of ecological assemblages has important implications for ecosystem functioning, but little is known about how scavenger communities organize at the global scale. Here, we test four hypotheses on the factors affecting the network structure of terrestrial vertebrate scavenger assemblages and its implications on ecosystem functioning. We expect scavenger assemblages to be more nested (i.e. structured): 1) in species-rich and productive regions, as nestedness has been linked to high competition for carrion resources, and 2) regions with low human impact, because the most efficient carrion consumers that promote nestedness are large vertebrate scavengers, which are especially sensitive to human persecution. 3) We also expect climatic conditions to affect assemblage structure, because some scavenger assemblages have been shown to be more nested in colder months. Finally, 4) we expect more organized assemblages to be more efficient in the consumption of the resource. We first analyzed the relationship between the nestedness of the scavenger assemblages and climatic variables (i.e. temperature, precipitation, temperature variability and precipitation variability), ecosystem productivity and biomass (i.e. NDVI) and degree of human impact (i.e. human footprint) using 53 study sites in 22 countries across five continents. Then, we related structure (i.e. nestedness) with its function (i.e. carrion consumption rate). We found a more nested structure for scavenger assemblages in regions with higher NDVI values and lower human footprint. Moreover, more organized assemblages were more efficient in the consumption of carrion. However, our results did not support the prediction that the structure of the scavenger assemblages is directly related to climate. Our findings suggest that the nested structure of vertebrate scavenger assemblages affects its functionality and is driven by anthropogenic disturbance and ecosystem productivity worldwide. Disarray of scavenger assemblage structure by anthropogenic disturbance may lead to decreases in functionality of the terrestrial ecosystems via loss of key species and trophic facilitation processes.

54 ENVIRONMENTAL SCIENCES↗

Water relations and photosynthesis in the cryptoendolithic microbial habitat of hot and cold deserts

Two cryptoendolithic microbial communities, lichens in the Ross Desert of Antarctica and cyanobacteria in the Negev Desert, inhabit porous sandstone rocks of similar physical structure. Both rock types adsorb water vapor by physical mechanisms unrelated to biological processes. Yet the two microbial communities respond differently to water stress: cryptoendolithic lichens begin to photosynthesize at a matric water potential of -46.4 megaPascals (MPa) [70% relative humidity (RH) at 8 degrees C], resembling thallose desert lichens. Cryptoendolithic cyanobacteria, like other prokaryotes, photosynthesize only at very high matric water potentials [> -6.9 MPa, 90% RH at 20 degrees C].

NASA Discipline Number 52-30↗

Assessing residential activity in a home plumbing system simulator: monitoring the occurrence and relationship of major opportunistic pathogens and phagocytic amoebas

Opportunistic premise plumbing pathogens (OPPPs) have been detected in buildings’ plumbing systems causing waterborne disease outbreaks in the United States. In this study, we monitored the occurrence of OPPPs along with free-living amoeba (FLA) and investigated the effects of residential activities in a simulated home plumbing system (HPS). Water samples were collected from various locations in the HPS and analyzed for three major OPPPs: Legionella pneumophila, nontuberculous mycobacterial species (e.g., Mycobacterium avium, M. intracellulare, and M. abscessus), and Pseudomonas aeruginosa along with two groups of amoebas (Acanthamoeba and Vermamoeba vermiformis). A metagenomic approach was also used to further characterize the microbial communities. Results show that the microbial community is highly diverse with evidence of spatial and temporal structuring influenced by environmental conditions. L. pneumophila was the most prevalent pathogen (86% of samples), followed by M. intracellulare (66%) and P. aeruginosa (21%). Interestingly, M. avium and M. abscessus were not detected in any samples. The data revealed a relatively low prevalence of Acanthamoeba spp. (4%), while V. vermiformis was widely detected (81%) across all the sampling locations within the HPS. Locations with a high concentration of L. pneumophila and M. intracellulare coincided with the highest detection of V. vermiformis, suggesting the potential growth of both populations within FLA and additional protection in drinking water. After a period of stagnation lasting at least 2-weeks, the concentrations of OPPPs and amoeba immediately increased and then decreased gradually back to the baseline. Furthermore, monitoring the microbial population after drainage of the hot water tank and partial drainage of the entire HPS demonstrated no significant mitigation of the selected OPPPs. This study demonstrates that these organisms can adjust to their environment during such events and may survive in biofilms and/or grow within FLA, protecting them from stressors in the supplied water.

59 BASIC BIOLOGICAL SCIENCES↗

Investigating the interconnectedness of active transportation and public transit usage as a primer for Mobility-as-a-Service adoption and deployment

With the advent of Mobility-as-a-Service packages to reduce car usage and (by extension) greenhouse gas emissions, it is crucial that researchers and practitioners consider mutual determinants and outcomes that link the adoption of multiple alternative modes. This study therefore investigates the joint usage of active travel (walking, cycling, bike-sharing) and public transit (bus, rail) modes with respect to personal and situational contexts. Online survey data (n = 826) were collected across six Midwestern U.S. states using Amazon MTurk. Respondents indicated their average weekly usage of eight travel modes across three trip purposes so that multimodality could be assessed. Several psychological constructs were extracted via (a) the stages of change framework, used to indicate willingness to adopt new behavior, and (b) confirmatory factor analysis conducted on Likert scales rooted in theories of community, identity, norms, personality, and well-being. A multiple-indicators multiple-causes structural equation model is then employed to investigate the process of adopting a modality style that incorporates active and transit modes. The model confirms that compatible physical and social contexts, as well as navigational skills and openness to learning, are key primers of multimodalism. However, a path juncture stemming from neighborhood support for mobility innovation illustrates a potential polarity in outcomes between individuals and communities. In addition, the stage of active mobility adoption is linked to identity and norm activation, offering further guidance on what influences readiness for change. The seamless integration of mobility services is critical to matching the convenience and comfort of the private vehicle; understanding potential pathways to sustainable mobility, though, requires analyses and interventions that are driven by well-being outcomes and grounded in rigorous psychological frameworks. Here, the research findings offer practical guidance for identifying intervention opportunities to be linked with MaaS enrollment while demonstrating the need to illuminate how mobility might relate to social cohesion, identity expression, and various sources of satisfaction.

42 ENGINEERING↗

Structural Analysis of Load-Bearing Components in Mars Science Helicopter

The successful demonstration of powered flight on Mars by Ingenuity has led to the development of next generation Martian rotorcraft. As technology advances from a technology demonstrator to possible expanded planetary science investigations, the potential to fly a high payload carrying rotorcraft relies on the capability to analyze and validate the structural integrity of the vehicle in addition to the rotor aerodynamic performance. The Mars Science Helicopter (MSH), a next generation hexacopter concept, is one example of a proposed vehicle that would perform science independently of a land-based vehicle. To ensure the feasibility and viability of MSH mission performance, it is critical to mature the structural design for these vehicle concepts to bridge the gap between the best practices of the spacecraft and aircraft communities. MSH was analyzed under operational and 26G quasi-static launch loads with different rotor arm and fuselage designs. Structural analysis results showed that rotor arms could be stiffened for significantly improved structural performance with minimal mass penalty, while the rotorcraft frame exhibited a more complex relationship between mass and launch load stresses due to the mass-dependent launch loads.

Load-Bearing↗

ZMPY3D: accelerating protein structure volume analysis through vectorized 3D Zernike moments and Python-based GPU integration

Abstract Motivation Volumetric 3D object analyses are being applied in research fields such as structural bioinformatics, biophysics, and structural biology, with potential integration of artificial intelligence/machine learning (AI/ML) techniques. One such method, 3D Zernike moments, has proven valuable in analyzing protein structures (e.g., protein fold classification, protein–protein interaction analysis, and molecular dynamics simulations). Their compactness and efficiency make them amenable to large-scale analyses. Established methods for deriving 3D Zernike moments, however, can be inefficient, particularly when higher order terms are required, hindering broader applications. As the volume of experimental and computationally-predicted protein structure information continues to increase, structural biology has become a “big data” science requiring more efficient analysis tools. Results This application note presents a Python-based software package, ZMPY3D, to accelerate computation of 3D Zernike moments by vectorizing the mathematical formulae and using graphical processing units (GPUs). The package offers popular GPU-supported libraries such as CuPy and TensorFlow together with NumPy implementations, aiming to improve computational efficiency, adaptability, and flexibility in future algorithm development. The ZMPY3D package can be installed via PyPI, and the source code is available from GitHub. Volumetric-based protein 3D structural similarity scores and transform matrix of superposition functionalities have both been implemented, creating a powerful computational tool that will allow the research community to amalgamate 3D Zernike moments with existing AI/ML tools, to advance research and education in protein structure bioinformatics. Availability and implementation ZMPY3D, implemented in Python, is available on GitHub (https://github.com/tawssie/ZMPY3D) and PyPI, released under the GPL License.

Lai, Jhih-Siang (ORCID:0000000156775890)↗

Structure Computation of Quiet Spike[Trademark] Flight-Test Data During Envelope Expansion

System identification or mathematical modeling is used in the aerospace community for development of simulation models for robust control law design. These models are often described as linear time-invariant processes. Nevertheless, it is well known that the underlying process is often nonlinear. The reason for using a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades, the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B Quiet Spike(TradeMark) aeroservoelastic flight-test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description that may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance for the development of robust parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion, which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B Quiet Spike aeroservoelastic flight-test data for several flight conditions that 1) linear models are inefficient for modeling aeroservoelastic data, 2) nonlinear identification provides a parsimonious model description while providing a high percent fit for cross-validated data, and 3) the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗

Structures and Materials Competency Vision and Purpose at NASA Langley

Vision: The revolutionary materials and structures technologies developed at NASA Langley Research Center meet the needs of the Aerospace Community and benefit the quality of life on Earth Purpose: Develop and deliver useable research and technology results to meet Agency program objectives and to enable the Agency to develop future aerospace materials and structures

Shuart, Mark J.↗