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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 217 records · Page 12

A new constraint on galaxy–halo connections of [O ii ] emitters via HOD modelling with angular clustering and luminosity functions from the Subaru HSC survey

ABSTRACT Establishing a robust connection model between emission-line galaxies (ELGs) and their host dark haloes is of paramount importance in anticipation of upcoming redshift surveys. We propose a novel halo occupation distribution (HOD) framework that incorporates galaxy luminosity, a key observable reflecting ELG star-formation activity, into the galaxy occupation model. This innovation enables prediction of galaxy luminosity functions (LFs) and facilitates joint analyses using both angular correlation functions (ACFs) and LFs. Using physical information from luminosity, our model provides more robust constraints on the ELG–halo connection compared to methods relying solely on ACF and number density constraints. Our model was applied to $\rm [O\, {\small II}]$-emitting galaxies observed at two redshift slices at $z=1.193$ and 1.471 from the Subaru Hyper Suprime-Cam PDR2. Our model effectively reproduces observed ACFs and LFs observed in both redshift slices. Compared to the established Geach et al. HOD model, our approach offers a more nuanced depiction of ELG occupation across halo mass ranges, suggesting a more realistic representation of ELG environments. Our findings suggest that ELGs at $z\sim 1.4$ may evolve into Milky-Way-like galaxies, as their inferred halo masses evolve accordingly based on the extended Press–Schechter formalism, highlighting their role as potential building blocks in galaxy formation scenarios. By incorporating the LF as a constraint linking galaxy luminosity to halo properties, our HOD model provides a more precise understanding of ELG-host halo relationships. Furthermore, this approach facilitates the generation of high-quality ELG mock catalogues for future surveys. As the LF is a fundamental observable, our framework is potentially applicable to diverse galaxy populations, offering a versatile tool for analysing data from next-generation galaxy surveys.

Ishikawa, Shogo (ORCID:0000000221184211)↗

Structural and Mechanical Analysis of Individual Mineralized Collagen Fibrils Using In Situ Transmission Electron Microscopy

Bone serves as an example of nature’s architectured material with its characteristic blend of strength and toughness, all at a lightweight design. Given the hierarchical nature of these materials, it is essential to understand the governing mechanisms and organization of their constituents across length scales for bioinspired structural design. Despite recent advances in transmission electron microscopy (TEM) that have allowed us to witness the hierarchical arrangement of bone at micro-down to the nanoscale, we are still missing the details about the structural organization and mechanical properties of the main building blocks of bone─mineralized collagen fibrils (MCFs). Here, we present a method to extract individual MCFs from nature’s model material, mineralized turkey leg tendon, using a dropcasting procedure. By isolating the MCFs onto TEM supporting grids, we visualized the arrangement of organic and mineral phases within individual MCFs at the nanoscale. Using a four-dimensional scanning transmission electron microscopy (4D-STEM) approach, the orientation of individual mineral crystals within the MCFs was examined. Furthermore, we conducted in situ tensile experiments, revealing exceptional tensile strains of at least 8%, demonstrating the intricate relationship between structural organization and the mechanical behavior of MCFs. These insights into the ultrastructure of mineralized tissue building blocks, as well as the proposed sample-extraction method compatible with in situ mechanical testing, provide a strong basis for research into nature-inspired material design.

4D-STEM↗

Optical implementation of neocognitron and its applications to radar signature discrimination

A feature-extraction-based optoelectronic neural network is introduced. The system implementation approach applies the principle of the neocognitron paradigm first introduced by Fukushima et al. (1983). A multichannel correlator is used as a building block of a generic single layer of the neocognitron for shift-invariant feature correlation. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator. Successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved using this optoelectronic neocognitron. Detailed system analysis is described. Experimental demonstration of radar signature processing is also provided.

Chao, Tien-Hsin↗

Improved Benchmarking of Cohesive Elements in Abaqus Standard for Predicting Disbond and Delamination in Composite Structures

Traditional approaches for aircraft certification require the assumption of an initial flaw condition, either represented as barely visible impact damage (BVID) or through inclusion of a Teflon insert to serve as surrogate damage. Based on the initial composite damage state, the structure must be shown to demonstrate structural durability and damage tolerance (DaDT) according to the following criteria: a. Damage displays no detrimental growth under cyclic loading. The structure is able to sustain design limit load (DLL). Currently, the only available manner for validating structural performance is through test. Since damage can occur over a wide variety of areas within a structure, this approach has proven to be increasingly expensive and time consuming for composite airframes and acreage structure within the design-test-certification building block. A further complicating factor is the requirement to accurately capture the most critical damage morphologies as a starting condition. To understand the severity of the damage, it is either required to experimentally determine the most critical areas at tremendous expense or rely on legacy data of similar structural testing, which limits design space expansion. A preferred solution is to use advanced analysis to provide improved understanding of load margins for critical locations based on a wide variety of potential starting damage conditions.

Eric M. Roberts↗

Deposition of Nanostructured Thin Film from Size-Classified Nanoparticles

Materials comprising nanometer-sized grains (approximately 1_50 nm) exhibit properties dramatically different from those of their homogeneous and uniform counterparts. These properties vary with size, shape, and composition of nanoscale grains. Thus, nanoparticles may be used as building blocks to engineer tailor-made artificial materials with desired properties, such as non-linear optical absorption, tunable light emission, charge-storage behavior, selective catalytic activity, and countless other characteristics. This bottom-up engineering approach requires exquisite control over nanoparticle size, shape, and composition. We describe the design and characterization of an aerosol system conceived for the deposition of size classified nanoparticles whose performance is consistent with these strict demands. A nanoparticle aerosol is generated by laser ablation and sorted according to size using a differential mobility analyzer. Nanoparticles within a chosen window of sizes (e.g., (8.0 plus or minus 0.6) nm) are deposited electrostatically on a surface forming a film of the desired material. The system allows the assembly and engineering of thin films using size-classified nanoparticles as building blocks.

Camata, Renato P.↗

Atmospheric flow over two-dimensional bluff surface obstructions

The phenomenon of atmospheric flow over a two-dimensional surface obstruction, such as a building (modeled as a rectangular block, a fence or a forward-facing step), is analyzed by three methods: (1) an inviscid free streamline approach, (2) a turbulent boundary layer approach using an eddy viscosity turbulence model and a horizontal pressure gradient determined by the inviscid model, and (3) an approach using the full Navier-Stokes equations with three turbulence models; i.e., an eddy viscosity model, a turbulence kinetic-energy model and a two-equation model with an additional transport equation for the turbulence length scale. A comparison of the performance of the different turbulence models is given, indicating that only the two-equation model adequately accounts for the convective character of turbulence. Turbulence flow property predictions obtained from the turbulence kinetic-energy model with prescribed length scale are only insignificantly better than those obtained from the eddy viscosity model. A parametric study includes the effects of the variation of the characteristics parameters of the assumed logarithmic approach velocity profile. For the case of the forward-facing step, it is shown that in the downstream flow region an increase of the surface roughness gives rise to higher turbulence levels in the shear layer originating from the step corner.

Bitte, J.↗

The reflection for dense plant canopies from the one-angle radiative transfer equation

An essential component of remote sensing of vegetation canopies from satellites is fundamental understanding. Since passive remote is driven by photons, the modeling of photon interactions with vegetation is a basic building block in that understanding. Several such photon transport models have been developed during the past two decades and continue to be developed. Different approaches have been followed including monte carlo, radiosity methods, geometric shadowing, and radiative transfer. In general, each approach has application for canopies with specific attributes. This presentation concerns the application of radiative transfer to dense vegetation canopies in which the soil does not participate. The approach taken here is novel in that a consistent theory for photon transport for non-rotationally invariant leaf scattering is developed in a canopy with a general leaf angle distribution (LAD). The theory is limited to the one-angle approximation (azimuthally averaged radiance) and is based on Chandrasekhar's analytical theory. While such a model is admittedly only approximate, it does fulfill a unique function in our search for understanding. In particular, the model is simple in its construct yet contains the essential features of canopy architecture that are mainly responsible for observed responses. Thus, this model will not only be a predictive tool but also an educational one. The mathematical setting is the radiative transfer equation in a dense (semiinfinite) canopy. The leaf scattering phase function is assumed to be Lambertian with different reflectance and transmittance. In addition, abaxial and adaxial differentiation is allowed which effectively destroys optical reciprocity. The analytical solution for the canopy BRDF is obtained by manipulation of the integral transport equation (a la Chandrasekhar) for a general LAD. With discretization of the. leaf angle, the resulting set of integral equations are solved iteratively including an acceleration procedure when the single scatter albedo is near one (in the NIR). Results will be compared to the LARS soybean canopy radiances as well as to broadleaf results from a recent Ames experiment.

Ganapol, B. D.↗

Battery Systems for X-38 Crew Return Vehicle (CRV) and Deorbit Propulsion Stage (DPS)

A 28V 32 Ah cell Li/MnO2 and a 28V NiMH battery systems for the Deorbit Propulsion Stage (DPS) and the X-38 Crew Return Vehicle (CRV) are developed in Friwo-Silforkraft, Germany with the following objectives and approach: Provide safe battery designs for lowest volume and cost, and within schedule; Take advantage of less complex requests for V201 vs OPS CRV to simplify design and reduce cost; Use only existing commercial cell designs as building blocks for larger battery; Derive battery designs from the ASTRO-SPAS design which is the largest lithium battery design with Shuttle flight experience; Place maximum amount of battery energy on DPS; DPS battery is non rechargeable; and CRV batteries are rechargeable. This paper contains the following sections: a brief introduction on CRV requirements, CRV advantages over Soyuz, and X-38 programs; Battery objectives and approach; Battery requirements and groundrules (performance, on-orbit operation, etc); Design trades, solutions, redundancy plan, and margins; Envelope, size, and mass; Interfaces (structural, electrical & thermal); and Deviation from OPS CRV.

Darcy, Eric↗

Multiphysics simulation of recent experiments on alkali‐silica reaction expansion in reinforced concrete members

Alkali‐silica reaction (ASR) is an important degradation process that causes volumetric expansion and damage in concrete, and is affected significantly by the local temperature, moisture and stress conditions that often vary across the regions of a structure. Numerical simulation is essential to predict the progression and effects of ASR on the performance of structures. Because of the interactions between thermal and moisture transport and mechanical deformation, it is important for numerical models to represent all these physical phenomena and the coupling between them. Simulations of ASR in reinforced concrete (RC) structures are further complicated by the need to capture interactions between concrete and embedded reinforcing bars. Here, this paper describes the implementation of a scalable, coupled‐physics ASR model for simulating RC structures and assesses the ability of that model to predict ASR‐induced expansion in recent laboratory tests on RC block and beam specimens. These laboratory tests and the simulation approach were selected because of their applicability to RC structural‐scale simulations. This validation study helps builds confidence the ability of this approach to model ASR expansion in large, complex RC structures, which is a current high‐priority need.

36 MATERIALS SCIENCE↗

Bond-centric modular design of protein assemblies

Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.

Biomaterials – proteins↗

Structural characterization of ligand binding and pH-specific enzymatic activity of mouse Acidic Mammalian Chitinase

Chitin is an abundant biopolymer and pathogen-associated molecular pattern that stimulates a host innate immune response. Mammals express chitin-binding and chitin-degrading proteins to remove chitin from the body. One of these proteins, Acidic Mammalian Chitinase (AMCase), is an enzyme known for its ability to function under acidic conditions in the stomach but is also active in tissues with more neutral pHs, such as the lung. Here, we used a combination of biochemical, structural, and computational modeling approaches to examine how the mouse homolog (mAMCase) can act in both acidic and neutral environments. We measured kinetic properties of mAMCase activity across a broad pH range, quantifying its unusual dual activity optima at pH 2 and 7. We also solved high-resolution crystal structures of mAMCase in complex with oligomeric GlcNAcn, the building block of chitin, where we identified extensive conformational ligand heterogeneity. Leveraging these data, we conducted molecular dynamics simulations that suggest how a key catalytic residue could be protonated via distinct mechanisms in each of the two environmental pH ranges. These results integrate structural, biochemical, and computational approaches to deliver a more complete understanding of the catalytic mechanism governing mAMCase activity at different pH. Engineering proteins with tunable pH optima may provide new opportunities to develop improved enzyme variants, including AMCase, for therapeutic purposes in chitin degradation.

59 BASIC BIOLOGICAL SCIENCES↗

Meso-Scale Digital Materials: Modular, Reconfigurable, Lattice-Based Structures

We present a modular, reconfigurable system for building large structures. This system uses discrete lattice elements, called digital materials, to reversibly assemble ultralight structures that are 99.7% air and yet maintain sufficient specific stiffness for a variety of structural applications and loading scenarios. Design, manufacturing, and characterization of modular building blocks are described, including struts, nodes, joints, and build strategies. Simple case studies are shown using the same building blocks in three different scenarios: a bridge, a boat, and a shelter. Field implementation and demonstration is supplemented by experimental data and numerical simulation. A simplified approach for analyzing these structures is presented which shows good agreement with experimental results.

Reconfigurable↗

Shaping Peptide Assemblies Using Multifaceted Cyclic Tectons

Constructing distinct biomacromolecular assemblies typically necessitates target-specific selection and engineering of building blocks alongside optimization of assembly conditions. The challenge lies in achieving diverse morphological outcomes using simple, shared modules under identical conditions, a hallmark of natural systems that remains elusive in synthetic approaches. Here, in this work, we present a molecular scaffold-based strategy to instruct the coassembly of the same set of peptides into a variety of nanostructures across multiple dimensions. We create trifaceted cyclic scaffolds to manipulate two pairs of dimeric coiled-coil peptides prior to coassembly. These scaffolds, with addressable and orthogonal modules, allow controlled exposure of their cohesive faces, directing the formation of nanotriangles and fibrillar and lamellar assemblies. By tuning interpeptide arrangements that dictate scaffold geometry, we construct nonstraight fibrils with tunable curvature, which are rarely observed before. Notably, these scaffolds exhibit plasticity in adapting the sizes and orientations of cohesive faces to different assembly morphologies. The resultant nanostructures are consistent with the design and simulation results, demonstrating the reliability and predictability of this approach. Multifaceted cyclic scaffolds bridge the intellectual and physical gaps between building peptides and assemblies, holding promise for endowing various existing assembly systems with high tunability and versatility.

assembly morphology↗

Formulation of an effective safety design review for the Skylab Program.

The Skylab Program is presenting a unique set of requirements by extending the capabilities of both men and equipment to withstand extended periods of time in space. The progression of space programs which preceded Skylab have provided a set of building blocks of knowledge and experience coupled with an extensive ground test program which makes it possible to plan its flight program without earlier, unmanned test flights. This approach, however, makes it mandatory that to the maximum extent possible, we factor into the design review process all the 'lessons learned' which are applicable. It is this conscious review of the Skylab design, based on checklists prepared from design criteria, gleaned from a variety of sources and experiences, which is the subject of this paper. A brief description of the Skylab Program, its objectives, and the missions planned for it are presented briefly to better understand the degree of extrapolation of hardware development from previous programs.

Cohen, H.↗

Materials and Process Activities for NASA's Composite Crew Module

In January 2007, the NASA Administrator and Associate Administrator for the Exploration Systems Mission Directorate chartered the NASA Engineering and Safety Center (NESC) to design, build, and test a full-scale Composite Crew Module (CCM). The overall goal of the CCM project was to develop a team from the NASA family with hands-on experience in composite design, manufacturing, and testing in anticipation of future space exploration systems being made of composite materials. The CCM project was planned to run concurrently with the Orion project s baseline metallic design within the Constellation Program so that features could be compared and discussed without inducing risk to the overall Program. The materials and process activities were prioritized based on a rapid prototype approach. This approach focused developmental activities on design details with greater risk and uncertainty, such as out-of-autoclave joining, over some of the more traditional lamina and laminate building block levels. While process development and associated building block testing were performed, several anomalies were still observed at the full-scale level due to interactions between process robustness and manufacturing scale-up. This paper describes the process anomalies that were encountered during the CCM development and the subsequent root cause investigations that led to the final design solutions. These investigations highlight the importance of full-scale developmental work early in the schedule of a complex composite design/build project.

Polis, Daniel L.↗

Modular Standards for Space Power Systems

This presentation presents an approach to provide commonality for future space power systems through a set of modular power standards. The approach presented breaks down the electrical power conversion and distribution system into the lowest level functions, which are represented by power electronics modules, and serve as the foundational building blocks of the system. A series of Modular Power Standards has been developed to define the functions and interfaces of the lowest level of the electrical power system, or for each type of power electronics module. The power electronics modules, when integrated with a common chassis and backplane, can then be built up into modular electronics assemblies, which have been demonstrated and characterized in a relevant ground test environment.

Gardner, Brent G.↗

Advancing AI-Driven Analysis in X-ray Absorption Spectroscopy: Spectral Domain Mapping and Universal Models

In recent years, rapid progress has been made in developing artificial intelligence (AI) and machine learning (ML) methods for X-ray absorption spectroscopy (XAS) analysis. Compared to traditional XAS analysis methods, AI/ML approaches offer dramatic improvements in efficiency and help eliminate human bias. To advance this field, we advocate an AI-driven XAS analysis pipeline that features several interconnected key building blocks: benchmarks, workflows, databases, and AI/ML models. Specifically, we present two case studies for XAS ML. In the first study, we demonstrate the importance of reconciling the discrepancies between simulation and experiment using spectral domain mapping (SDM). Our ML model, which is trained solely on simulated spectra, predicts an incorrect oxidation state trend for Ti atoms in a combinatorial zinc titanate film. After transforming the experimental spectra into a simulation-like representation using SDM, the same model successfully recovers the correct oxidation state trend. In the second study, we explore the development of universal XAS ML models that are trained on the entire periodic table, which enables them to leverage common trends across elements. Looking ahead, we envision that an AI-driven pipeline can unlock the potential of real-time XAS analysis to accelerate scientific discovery.

36 MATERIALS SCIENCE↗

Improving Discrete-Sensitivity-Based Approach for Practical Design Optimization

In developing the automated methodologies for simulation-based optimal shape designs, their accuracy, efficiency and practicality are the defining factors to their success. To that end, four recent improvements to the building blocks of such a methodology, intended for more practical design optimization, have been reported. First, in addition to a polynomial-based parameterization, a partial differential equation (PDE) based parameterization was shown to be a practical tool for a number of reasons. Second, an alternative has been incorporated to one of the tedious phases of developing such a methodology, namely, the automatic differentiation of the computer code for the flow analysis in order to generate the sensitivities. Third, by extending the methodology for the thin-layer Navier-Stokes (TLNS) based flow simulations, the more accurate flow physics was made available. However, the computer storage requirement for a shape optimization of a practical configuration with the -fidelity simulations (TLNS and dense-grid based simulations), required substantial computational resources. Therefore, the final improvement reported herein responded to this point by including the alternating-direct-implicit (ADI) based system solver as an alternative to the preconditioned biconjugate (PbCG) and other direct solvers.

Baysal, Oktay↗