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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The FC-1D: The profitable alternative Flying Circus Commercial Aviation Group

The FC-1D was designed as an advanced solution for a low cost commercial transport meeting or exceeding all of the 1993/1994 AIAA/Lockheed request for proposal requirements. The driving philosophy behind the design of the FC-1D was the reduction of airline direct operating costs. Every effort was made during the design process to have the customer in mind. The Flying Circus Commercial Aviation Group targeted reductions in drag, fuel consumption, manufacturing costs, and maintenance costs. Flying Circus emphasized cost reduction throughout the entire design program. Drag reduction was achieved by implementation of the aft nacelle wing configuration to reduce cruise drag and increase cruise speeds. To reduce induced drag, rather than increasing the wing span of the FC-1D, spiroids were included in the efficient wing design. Profile and friction drag are reduced by using riblets in place of paint around the fuselage and empennage of the FC-1D. Choosing a single aisle configuration enabled the Flying Circus to optimize the fuselage diameter. Thus, reducing fuselage drag while gaining high structural efficiency. To further reduce fuel consumption a weight reduction program was conducted through the use of composite materials. An additional quality of the FC-1D is its design for low cost manufacturing and assembly. As a result of this design attribute, the FC-1D will have fewer parts which reduces weight as well as maintenance and assembly costs. The FC-1D is affordable and effective, the apex of commercial transport design.

Meza, Victor J.↗
DOE OSTI2025

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-offs between electrical conductivity, the Seebeck coefficient, and thermal conductivity, which are further complicated by the presence of defects. This review explores how artificial intelligence (AI) and machine learning (ML) are transforming thermoelectric materials design. Advanced ML approaches including deep neural networks, graph-based models, and transformer architectures, integrated with high-throughput simulations and growing databases, effectively capture structure-property relationships in a complex multiscale defect space and overcome the “curse of dimensionality”. This review discusses AI-enhanced defect engineering strategies such as composition optimization, entropy and dislocation engineering, and grain boundary design, along with emerging inverse design techniques for generating materials with targeted properties. Finally, it outlines future opportunities in novel physics mechanisms and sustainability, highlighting the critical role of AI in accelerating the discovery of thermoelectric materials.

36 MATERIALS SCIENCE↗
NASA NTRS1987

A combined stochastic feedforward and feedback control design methodology with application to autoland design

A combined stochastic feedforward and feedback control design methodology was developed. The objective of the feedforward control law is to track the commanded trajectory, whereas the feedback control law tries to maintain the plant state near the desired trajectory in the presence of disturbances and uncertainties about the plant. The feedforward control law design is formulated as a stochastic optimization problem and is embedded into the stochastic output feedback problem where the plant contains unstable and uncontrollable modes. An algorithm to compute the optimal feedforward is developed. In this approach, the use of error integral feedback, dynamic compensation, control rate command structures are an integral part of the methodology. An incremental implementation is recommended. Results on the eigenvalues of the implemented versus designed control laws are presented. The stochastic feedforward/feedback control methodology is used to design a digital automatic landing system for the ATOPS Research Vehicle, a Boeing 737-100 aircraft. The system control modes include localizer and glideslope capture and track, and flare to touchdown. Results of a detailed nonlinear simulation of the digital control laws, actuator systems, and aircraft aerodynamics are presented.

Halyo, Nesim↗
DOE OSTI2021

A moving morphable component‐based topology optimization approach considering transient structural dynamic responses

Abstract A novel approach is developed under the moving morphable component (MMC) framework to solve topology optimization problems considering transient structural dynamic responses, where the structure for optimization is constructed with a collection of structural components, and the structural layout can be described explicitly via only a small number of design variables characterizing the positions and geometries of the components. The transient dynamic response of the structure and corresponding sensitivities are computed via step‐by‐step numerical integration and mode reduction technique is also employed to enhance the computational efficiency. Compared with existing works, the numerical instabilities induced by localized vibration modes can be substantially alleviated and the computational effort for direct sensitivity analysis is significantly reduced in the proposed approach. Two and three‐dimensional numerical examples considering the cases of nonproportional damping mechanism and time‐varying mass are also provided to manifest the validity of the proposed approach.

Li, Jialin↗
DOE OSTI2021

Pyomo.GDP: an ecosystem for logic based modeling and optimization development

We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.

42 ENGINEERING↗
DOE OSTI2025

Critical impact of experimentally-driven strut level anisotropic material models in advanced stress analysis of additively manufactured lattice structures

The rapid acceleration in materials discovery may overshadow the importance of thoroughly understanding the mechanical performance of newly developed materials in demanding environments. The recent interest in combining parametric studies with machine learning techniques to explore how changes in specific processing parameters or model inputs affect the overall behavior of a material system can only be truly beneficial if the governing constitutive relations describing material behavior are accurately established. In this study, we demonstrate the critical impact of accurately representing strut-level anisotropic material behavior in advanced stress analysis of additively manufactured lattice structures (AMLS). We introduce a systematic experimental and modeling approach for developing strut-level anisotropic elastoplastic material models that account for the influence of microstructural features such as porosity, texture, and surface roughness on the development of local anisotropic mechanical properties, which vary with strut orientation relative to the build direction (BD). As a result the presented material model captures and relates the statistics of spatially varying struts’ microstructural features to the local stress distribution. Our findings suggest that incorporating strut-level anisotropic material behavior into unit cell analysis significantly influences the load distribution and evolution of local stresses within the structure. Therefore, accounting for this anisotropy is critical for developing an understanding of unit cell behavior and performance, including subsequent topology/component design optimization based on this analysis.

Sahoo, Subhadip [University of Arizona]↗
DOE OSTI2022

Predicting oxidation damage in ultra high-temperature borides: A machine learning approach

Ultra-high temperature (UHT) borides are ceramics materials with melting points above 3000 °C for structural applications in extreme environments. However, at temperatures exceeding 1600 °C and under oxidizing conditions, the material suffers from detrimental degradation. Optimized design and performance of diboride materials under such extreme conditions requires filling the missing composition-microstructure-oxidation gap. This study proposes a computational data-driven framework to connect the processing and microstructure of Ultra-high temperature borides with the oxidation damage. Random Forest Regressor (RFR) model is adopted to forecast the oxide scale thickness developed after oxidation testing based on processing variables and microstructural features. The model trained on a dataset consisting of 107 samples of experimental data extracted from the literature aims to predict oxidation damage. With proper data manipulation and fine model tuning, the predictor could forecast the oxide scale thickness of UHT diborides with a Mean Absolute Error of 37.45 μm and an R-square of 0.83. This model could be used as a high-throughput scheme to design and test new UHT diborides materials computationally. Furthermore, a model with larger composition capabilities could also be developed in the future as more experimental data become available.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Laser-Induced Enhancement of Acoustic Mode Quality Factor Revealed by Correlated Single-Particle Optical and Electron Microscopy

Acoustic modes in plasmonic nanostructures provide fundamental insights into their optomechanical behavior at the nanoscale, enabling emerging applications in plasmon-enhanced optomechanics, ultrasensitive sensing, and nanoscale energy transduction. Here we explore the modulation of acoustic phonon dynamics in lithographically fabricated gold nanodisks via laser-induced photothermal annealing. Using a correlated approach that utilizes both single-particle transient extinction spectroscopy and advanced electron microscopy, we directly link nanoscale structural transformations to changes in mechanical properties as probed through the coherence of the excited acoustic modes. Specifically, ultrafast pump–probe microscopy reveals an enhancement in the acoustic mode quality factor of annealed gold nanodisks, indicative of reduced damping and improved vibrational coherence. Structural characterization via scanning electron microscopy and electron backscatter diffraction confirms that photoinduced annealing results in smoother surface morphology and overall enhanced crystallinity. The improved crystalline order reduces defect and crystal boundary scattering, which we suggest as the reason underlying the lower quality factor before annealing. Furthermore, these findings demonstrate that targeted structural engineering at the nanoscale offers a powerful strategy for optimizing the optomechanical performance of plasmonic nanostructures, with broad implications for the design of next-generation nanophotonic and optomechanical systems.

Annealing (metallurgy)↗
DOE OSTI2022

Multi-reward Reinforcement Learning Based Bond-Order Potential to Study Strain-Assisted Phase Transitions in Phosphorene

Here, we introduce a multi-reward reinforcement learning (RL) approach to train a flexible bond-order potential (BOP) for 2D phosphorene based on ab initio training data sets. Our approach is based on a continuous action space Monte Carlo tree search algorithm that is general and scalable and presents an efficient multiobjective optimization scheme for high-dimensional materials design problems. As a proof-of-concept, we deploy this scheme to parametrize multiple structural and dynamical properties of 2D phosphorene polymorphs. Our RL-trained BOP model adequately captures the structure, energetics, transformation barriers, equation of state, elastic constants, and phonon dispersions of various 2D P polymorphs. We use this model to probe the impact of temperature and strain rate on the phase transition from black (α-P) to blue phosphorene (β-P) through molecular dynamics simulations. A decrease in critical strain for this phase transition with increase in temperature is observed, and the underlying atomistic mechanisms are discussed.

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

Rapid data acquisition and machine learning-assisted composition design of functionally graded alloys via wire arc additive manufacturing

Abstract The lack of high-quality datasets in materials science hinders artificial intelligence (AI)-driven alloy design. To address this challenge, wire arc additive manufacturing (WAAM) was employed to fabricate graded alloys, generating extensive data for machine learning (ML)-assisted property prediction. ML models were developed using high-throughput experiments, computational models, and genetic algorithm to optimize feature selection, successfully predicting hardness and porosity. The ML model demonstrated its efficacy by designing a gradient alloy with enhanced properties. However, scaling up revealed uncertainties in tensile property and porosity due to differences in size and thermal conditions between the designed alloy build and the gradient print used to construct the ML model. This underscores the need for uncertainty quantification and process optimization in WAAM-driven alloy design. Our work advances AI-integrated additive manufacturing, offering a rapid approach to exploring process–structure–property relationships and accelerating materials development.

Wang, Xin↗
DOE OSTI2021

Recombination rate analysis in long minority carrier lifetime mid-wave infrared InGaAs/InAsSb superlattices

Gallium is incorporated into the strain-balanced In(Ga)As/InAsSb superlattice system to achieve the same mid-wave infrared cutoff tunability as conventional Ga-free InAs/InAsSb type-II superlattices, but with an additional degree of design freedom to enable optimization of absorption and transport properties. Time-resolved photoluminescence measurements of InGaAs/InAsSb superlattice characterization- and doped device structures are reported from 77 to 300 K and compared to InAs/InAsSb. The low-injection photoluminescence decay yields the minority carrier lifetime, which is analyzed with a recombination rate model, enabling the determination of the temperature-dependent Shockley–Read–Hall, radiative, and Auger recombination lifetimes and extraction of defect energy levels and capture cross section defect concentration products. The Shockley–Read–Hall-limited lifetime of undoped InGaAs/InAsSb is marginally reduced from 2.3 to 1.4 μs due to the inclusion of Ga; however, given that Ga improves the vertical hole mobility by a factor of >10×, a diffusion-limited InGaAs/InAsSb superlattice nBn could expect a lower bound of 2.5× improvement in diffusion length with significant impact on photodetector quantum efficiency and radiation hardness. At temperatures below 120 K, the doped device structures are Shockley–Read–Hall limited at 0.5 μs, which shows promise for detector applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Tailoring the Mass Transport to Achieve High-Performing Unitized Regenerative Fuel Cells Considering Practical Operating Conditions

Unitized regenerative fuel cells (URFCs) convert electrical energy to chemical bonds in hydrogen during charge and convert chemical energy to output electricity during discharge, offering a promising solution to long-term energy storage. Recent studies indicate that the round-trip-voltaic efficiency (RTE) and longevity of URFCs are limited by complex mass transport during charging and discharging. Here, we first investigate how different porous transport layer (PTL) structures can impact URFC performance. The preferred PTL has a low tortuosity and high porosity, leading to a high RTE above 50% at 1 A cm −2 using Nafion 212. Moreover, thicker membranes, such as Solvay 90, are required to ensure mechanical stability and minimize H 2 crossover when operating under high differential pressure. Although this assembly inevitably leads to a higher ohmic loss, the RTE can be improved by further tailoring the electrode structures to facilitate mass transport by using supported catalyst, which still achieves over 50% RTEs at 1 A cm −2 . Optimization of porous structure to mitigate mass transport resistance with appropriate materials down selection considering practical application requirements can be a key design principle for achieving high-performing URFCs.

25 ENERGY STORAGE↗
DOE OSTI2021

3D Printed, Low Tortuosity Garnet Framework For Beyond 500 Wh/kg Batteries

In this project, we developed LLZO garnet ink recipes and processes for 3D-printing highly ordered ionically conductive garnet porous structures on dense garnet separators. Using this technique, we are able to fabricate controlled architecture LLZO garnet solid-state electrolyte (SSE) trilayers for application in solid-state lithium batteries. The trilayer comprises a thin dense center layer sandwiched between a 3D-printed patterned porous layer and a random porous layer. The dense layer functions as the ionic separator between the anode and cathode. The random porous layer hosts the lithium-metal anode and provides the structural support. The 3D-printed SSE patterned porous layer hosts the cathode, providing continuous, low tortuosity pathways for fast 3D Li+ transport through the cell while increasing the electrode/electrolyte interface area to decrease the interfacial resistance. Compared to the random porous structure, this ordered patterned structure possesses more vacant space for higher cathode loading without sacrificing ionically conducting capability, thus potentially greatly increasing the cell energy density. For demonstration purposes, we developed two patterns for the 3D-printed porous layer: grids and columns, for hosting sulfur and NMC cathode, respectively. The corresponding two types of cells were fabricated and tested, and have demonstrated achievement of theoretical discharge capacity without cathode calendaring. In addition, we developed a fundamental solid-state ionic and electronic transport model to optimize the 3D-printed structures for maximum energy and power density. The model was validated by experiment and provides the critical design criteria for achieving the >500 Wh/kg energy goal as function of C-rate.

25 ENERGY STORAGE↗
NASA NTRS1976

The waveguide laser - A review

The present article reviews the fundamental physical principles essential to an understanding of waveguide gas and liquid lasers, and the current technological state of these devices. At the present time, waveguide laser transitions span the visible through submillimeter regions of the wavelength spectrum. The introduction discusses the many applications of waveguide lasers and the wide variety of laser configurations that are possible. Section 1 summarizes the properties of modes in hollow dielectric waveguides of circular, rectangular, and planar cross section. Section 2 considers various approaches to optical feedback including internal and external mirror Fabry-Perot type resonators, hollow waveguide distributed feedback structures, and ring-resonant configurations. Section 3 discusses those aspects of molecular kinetic and laser theory pertinent to the design and optimization of waveguide gas lasers.

Degnan, J. J.↗
NASA NTRS1977

Solar power satellite system definition study. Part 2, volume 4: Microwave power transmission systems

A slotted waveguide planar array was established as the baseline design for the spaceborne transmitter antenna. Key aspects of efficient energy conversion at both ends of the power transfer link were analyzed and optimized alternate approaches in the areas of antenna and tube design are discussed. An integrated design concept was developed which meets design requirements, observes structural and thermal constraints, exhibits good performance and was developed in adequate depth to permit cost estimating at the subsystem/component level.

Source record↗
NASA NTRS1983

Structural Optimization

Programming Structural Synthesis System (PROSSS) provides structural synthesis capability by combining SPAR and CONMIN computer programs with set of interface procedures. SPAR is large general-purpose finite-element structural-analysis program, and CONMIN is large general-purpose optimization program. User supplies two small problem-dependent programs to define design variables, constraints, and objective function.

Rogers, J. L., Jr↗
NASA NTRS1985

Estimating the weight of generally configured dual wing systems

Formulas available for the weight estimation of monoplane wings cannot be said to be appropriate for the estimation of generally configured dual wing systems. In the present paper a method is described which simultaneously generates a structural weight estimate and a fully stressed, quasi-optimal structure for a model of a dual wing system. The method is fast and inexpensive. It is ideally suited to preliminary design. To illustrate the method, a dual wing system and a conventional wing system are sized. Numerical computation is shown to be suitably fast for both cases and, for both cases, convergence to a final configuration is shown to be quite rapid. To illustrate the validity of the method, a conventional wing is sized and its weight obtained by the present method is compared to its weight determined by a reputable weight estimation formula. The results are shown to be very close.

Cronin, D. L.↗
NASA NTRS1989

Structural optimization of rotor blades with straight and swept tips subject to aeroelastic constraints

The main conclusions obtained in the present study are summarized. Their application to the structural optimization of a helicopter blade should be limited by the assumptions used in obtaining the numerical results presented here. The optimum design procedure described here is very efficient, and can produce improved designs with a very limited number of precise analyses. The method of constructing the approximate problem is such that previously conducted aeroelastic analyses can be reused in a new optimization problem. For example, if an optimization study is preceded by a parametric study in which the effect of various combinations of blade design parameters is examined, all the aeroelastic analyses performed for the parametric study can be reutilized in the optimization study. This is not possible when the approximate problem is built from Taylor series expansions. The results of the optimization are quite sensitive to the aeroelastic stability margins required of the blade. In the optimization of case 2, changing the aeroelastic stability constraints from simply requiring that the blade be stable in hover, to requiring that the stability margins be maintained during the course of the optimization, reduced the gains in n/rev vibration levels by more than 50 percent. The introduction of tip sweep can reduce the n/rev vertical hub shears beyond the level that can be obtained by just modifying the mass and stiffness distributions of the blade.

Friedmann, Peretz P.↗