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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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The de novo crystal structure of SfmD reveals a novel c -type heme cofactor for promoting a monooxygenation reaction in the biosynthetic pathway of saframycin A.
An approach to dynamic system identification is presented taking into account the goal of enhancing robust control performance of flexible structures. Identification techniques are derived which take advantage of the physics of structural dynamics and can provide realistic bounds for all potential parameter uncertainties. The developed approach includes input optimization which distributes excitation energy in such a way that the influence of residual uncertainties on robust control performance is reduced.
The direct P and S wave arrival times from natural lunar seismic events are the most complete and reliable data set for determining the structure of the lunar mantle. A total of 40 events provide sufficiently well-observed arrivals to permit the extraction of structural information. Using this arrival time data set, the average velocities in a two-layered mantle with an assumed crustal structure (from Toksoz et al., 1974) have been obtained. Reflected phases arriving after direct S are then used to calculate the depth of the boundary between the two mantle layers, and to demonstrate that it is probably a complex transition zone approximately 80 km thick between 400 and 480 km depth. To determine velocity gradients in the upper mantle it is required that the model explain the pronounced decrease in shear wave amplitudes and accompanying delay in shear wave arrival times beyond a distance of about 90 deg. The final model is well-constrained.
The set of trajectories leaving/impacting the surface of the Galilean satellites of Jupiter is analyzed from theoretical and computational veiwpoints in the ciruclular restricted three body problem in order to characterize the sensitive impact regions for spacecraft trajectory applications as well as the main dynmical structures influencing this set of trajecotries.
A programmatic narrative of the effects of NASA stress lab program on physical education in U.S. schools and colleges is presented. Individual non-structured programs were set up where students participate during his or her free time. The program is also in accordance with the medical history of the student. Preliminary results indicate more student interest and participation in the program and that students are generally more physically fit than in previous structured programs.
Different finite element models previously set up for thermal analysis of the space shuttle orbiter structure are discussed and their shortcomings identified. Element density criteria are established for the finite element thermal modelings of space shuttle orbiter-type large, hypersonic aircraft structures. These criteria are based on rigorous studies on solution accuracies using different finite element models having different element densities set up for one cell of the orbiter wing. Also, a method for optimization of the transient thermal analysis computer central processing unit (CPU) time is discussed. Based on the newly established element density criteria, the orbiter wing midspan segment was modeled for the examination of thermal analysis solution accuracies and the extent of computation CPU time requirements. The results showed that the distributions of the structural temperatures and the thermal stresses obtained from this wing segment model were satisfactory and the computation CPU time was at the acceptable level. The studies offered the hope that modeling the large, hypersonic aircraft structures using high-density elements for transient thermal analysis is possible if a CPU optimization technique was used.
The coverage of the celestial sphere or the surface of the earth with a narrow-field instrument onboard a satellite can be described by a set of swaths on the sphere. A transect is a curve on this sphere constructed to sample the coverage. At each point on the transect the number of times that the field-of-view of the instrument has passed over the point is recorded. This information is conveniently displayed as an integer-valued histogram over the length of the transect. The effectiveness of the transect method for a particular observing plan and the best placement of the transects depends upon the structure of the set of observations. Survey missions are usually characterized by a somewhat parallel alignment of the instrument swaths. Using autocorrelation and cross-correlation functions among the histograms the structure of a survey has been analyzed into two components, and each is illustrated by a simple mathematical model. The complex, all-sky survey to be performed by the Infrared Astronomical Satellite (IRAS) is synthesized in some detail utilizing the objectives and constraints of that mission. It is seen that this survey possesses the components predicted by the simple models and this information is useful in characterizing the properties of the IRAS survey and the placement of the transects as a function of celestial latitude and certain structural properties of the coverage.
The dominating set problem has many practical applications but is well-known to be NP-hard. Therefore, there is a need for efficient heuristic algorithms, especially in applications such as ad hoc wireless networks. Most distributed algorithms proposed in the literature assume that each node has knowledge of the network structure. We propose a distributed heuristic algorithm that uses two rounds of communication, and where each node has only local information, both in terms of network structure and dominating set assignment. First, each node calculates a local centrality measure to determine whether it is part of the dominating set D. The second round guarantees D is a dominating set by adding any non-dominated nodes. We compare several centrality measures and show that the Shapley centrality, derived from the Shapley value in game theory, is theoretically motivated and performs well in practice on several synthetic and real-world networks.
The effect of element size on the solution accuracies of finite-element heat transfer and thermal stress analyses of space shuttle orbiter was investigated. Several structural performance and resizing (SPAR) thermal models and NASA structural analysis (NASTRAN) structural models were set up for the orbiter wing midspan bay 3. The thermal model was found to be the one that determines the limit of finite-element fineness because of the limitation of computational core space required for the radiation view factor calculations. The thermal stresses were found to be extremely sensitive to a slight variation of structural temperature distributions. The minimum degree of element fineness required for the thermal model to yield reasonably accurate solutions was established. The radiation view factor computation time was found to be insignificant compared with the total computer time required for the SPAR transient heat transfer analysis.
Noting that the stiffness of the girder increases very rapidly as Beta increases, the result can be summed up as follows: When the cross stress preponderates in one direction and when the web plate is to be given the dimensions commensurate to its stresses, it is advisable (regardless of any ensuing structural difficulties) to set the uprights at about Beta = 120 degrees, thereby lowering the weight of the plate wall 15 percent (in contrast to Beta = 90 degrees), and raising the stiffness 55 percent. But, when the cross stresses alternate and are approximately of the same intensity in both directions, or, if the web plate thickness is determined by other structural reasons, then Beta = 90 degrees should be chosen.
NASA has collected vibroacoustic response data on a variety of complex, aerospace structures to support research into numerical modeling of such structures. This data is being made available to the modeling community to promote the development and validation of analysis methods for these types of structures. Existing data from two structures is described, as well as plans for a data set from a third structure. The first structure is a 1.22 m by 1.22 m stiffened aluminum panel, typical of a commercial aircraft sidewall section. The second is an enclosed, stiffened aluminum cylinder, approximately 3.66 m long and 1.22 m in diameter, constructed to resemble a small aircraft fuselage with no windows and a periodic structure. The third structure is a filament-wound composite cylinder with composite stiffeners. Numerous combinations of excitation and response variables were measured on the structures, including: shaker excitation; diffuse acoustic field; velocity response from a laser vibrometer; intensity scans; and point acceleration.
This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.
The Space Shuttle inertial system is built around a sensor assembly called the inertial measurement unit (IMU). The system includes a redundant set of three structurally integrated IMU's that operate in conjunction with parallel strung data system computers to provide precise attitude and velocity information to user system functions. The inertial system is actually a separate subsystem function integrated into the overall avionics system. Software resident in the system computers is the final link in the inertial system. The inertial software is comprised of two major sets, including a subsystem operating program (SOP) called the IMU SOP and redundancy management. Attention is given to system applications, systems performance, attitude sensitivities, the IMU platform, IMU thermal management, aspects of IMU calibration, and Shuttle program experience.
The advancement in experimental techniques, like the atom probe tomography and high resolution electron microscopy, is fueling interest in studying structural transformations of grain boundaries in metal and alloys to uncover correlations between mechanical properties and solute or impurity segregation to grain boundaries. Atomistic modeling is an important tool that can pinpoint the intricate dynamics of grain boundary phase transitions, but the lack of accurate interatomic potentials needed to simulate the complex dynamics of grain boundary structural transitions and identify different metastable phases has been the bottleneck. To this end, we use niobium as a model body centered cubic (BCC) metal and develop an interatomic potential to study grain boundary phase transitions. The potential for Nb is based on a generalization of the embedded atomic method potential and has sufficient flexibility to learn complex energy landscapes using a small set of training structures. We systematically test and validate the using data from ab initio density functional theory calculations and experiments. Using this potential, we calculate energies of multiple symmetric-tilt grain boundaries spanning a wide range of misorientation angles. Additionally, we explore different metastable structures of the Σ 27(552) [$1\overline{1}0$] grain boundary and use molecular dynamic simulations to study the coexistence of metastable phases and grain boundary transitions at finite temperature.
Manipulating matter with a scanning tunneling microscope (STM) enables the creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of the designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating carbon monoxide (CO) molecules on a copper substrate by using the STM tip. The automated workflow combines molecule detection and manipulation, employing deep-learning-based object detection to locate CO molecules and linear assignment algorithms to allocate these molecules to designated target sites. We initially perform molecule maneuvering based on randomized parameter sampling for sample bias, tunneling current set point, and manipulation speed. This data set is then structured into an action trajectory used to train an RL agent. The model is subsequently deployed on the STM for real-time fine-tuning of the manipulation parameters during structure construction. Our approach incorporates path-planning protocols coupled with active drift compensation to enable atomically precise fabrication of structures with significantly reduced human input while realizing larger-scale artificial lattices with the desired electronic properties. Furthermore, using our approach, we demonstrate the automated construction of an extended artificial graphene lattice and confirm the existence of a characteristic Dirac point in its electronic structure. Further challenges regarding the RL-based structural assembly scalability are discussed.
Resonant soft X-ray scattering (RSoXS) probes structure with chemical sensitivity that is useful for determining the morphology of multiblock copolymers. However, the hyperspectral scattering data produced by this technique can be challenging to interpret. Here, in this study, we use computational scattering simulations to extract the microstructure of a model triblock copolymer from the energy-dependent scattering from RSoXS. An ABC triblock terpolymer formed from poly(4-methylcaprolactone) (P4MCL), poly(2,2,2-trifluoroethylacrylate) (PTFEA), and poly (dodecylacrylate) (PDDA), P4MCL-block-PTFEA-block-PDDA, was synthesized as the model triblock system. Through quantitative evaluation of simulated scattering data from a physics-informed set of candidate structure models against experimental RSoXS data, we find the best agreement with hexagonally packed core–shell cylinders. This result is also consistent with electron-density reconstruction from hard X-ray scattering data evaluated against electron-density maps generated with the same model set. These results demonstrate the utility of simulation-guided scattering analysis to study complex microstructures that are challenging to image by microscopy.
The design of most structures involves ensuring integrity for several independent loading conditions. Often, it is rational to design these, exploiting the ductility of the materials to reduce structural costs. Then, ensuring integrity evokes the need for nonmonotonic limit analyses. A groundwork is laid for implementing these analyses. An alternate limit load characterization to that of Greenberg is provided, a mathematical statement of the problem leading to both monotonic (proportional) and nonmonotonic limit loads values is formulated, a direct limit load analysis procedure for analysis within a finite-element framework is described, and limit loads for sets of simple structures are evaluated. A direct limit analysis process is described, and monotonic limit loads are characterized. The process furnishes 'exact' values of limit loads with increasing efficiency as the number of structural elements and force redundancy decreases. Tests show that the accuracy of predicting nonmonotonic limit loads is very sensitive to the number of degrees of freedom in the analysis compared with the total number in the model.
Terahertz (THz) metamaterials with high‐figure‐of‐merit (high‐FoM) performance resonance are essential for advancing sensors, detectors, and imagers. Conventional designs focus on symmetric or low‐asymmetry geometric structures, leaving high‐asymmetry designs largely unexplored due to the inefficiency of trial‐and‐error‐based rational design. Recent deep learning techniques offer automation and acceleration but are constrained by the need for large datasets inherent to their data‐driven nature. Here, a novel prior knowledge‐guided generative model augmented by a physics‐constrained active learning mechanism to design high‐asymmetry metamaterials. An advanced diffusion model learns features from a small set of classical structures with high‐FoM THz resonance and generates new high‐asymmetry structures. To mitigate the limited number of classical structures, the generated high‐asymmetry structures are actively selected and integrated into the initial training dataset based on their physical characteristics. Experimental results demonstrate the superior resonance performance of the generated high‐asymmetry metamaterials over classical designs, exhibiting improvements exceeding 30% in key resonance metrics. Remarkably, this performance is attained using only 68 classical structures as the initial training dataset, significantly reducing the data requirements for deep learning‐based metamaterial design. The proposed scheme for generating high‐asymmetry structures provides a new effective and efficient solution for high‐FoM resonance, expanding applications in high‐sensitivity THz metadevices.