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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Lightweight moving radiators for heat rejection in space

Low temperature droplet stream radiators, using nonmetallic fluids, can be used to radiate large amounts of waste heat from large space facilities. Moving belt radiators are suitable for use on a smaller scale, radiating as few as 10 kW from shuttle related operations. If appropriate seal technology can be developed, moving belt radiators may prove to be important for high temperature systems as well. Droplet stream radiators suitable for operation at peak temperatures near 300 K and 1000 K were studied using both freezing and nonfreezing droplets. Moving belt radiators were also investigated for operation in both temperature ranges. The potential mass and performance characteristics of both concepts were estimated on the basis of parametric variations of analytical point designs. These analyses included all consideration of the equipment required to operate the moving radiator system and take into account the mass of fluid lost by evaporation during mission lifetimes. Preliminary results indicate that low temperature droplet stream radiator appears to offer the greatest potential for improvement over conventional flat plate radiators.

Knapp, K.↗
NASA NTRS1987

Fracture mechanics concepts in reliability analysis of monolithic ceramics

Basic design concepts for high-performance, monolithic ceramic structural components are addressed. The design of brittle ceramics differs from that of ductile metals because of the inability of ceramic materials to redistribute high local stresses caused by inherent flaws. Random flaw size and orientation requires that a probabilistic analysis be performed in order to determine component reliability. The current trend in probabilistic analysis is to combine linear elastic fracture mechanics concepts with the two parameter Weibull distribution function to predict component reliability under multiaxial stress states. Nondestructive evaluation supports this analytical effort by supplying data during verification testing. It can also help to determine statistical parameters which describe the material strength variation, in particular the material threshold strength (the third Weibull parameter), which in the past was often taken as zero for simplicity.

Manderscheid, Jane M.↗
NASA NTRS1990

Vortex Flow Aerodynamics

The AGARD Fluid Dynamics Panel sponsored this symposium to provide an update review of the aerodynamic effects of separation-induced vortex flows on the design and off-design performance of fighter aircraft. A better understanding is needed to predict and control these vortex flows throughout the flight envelope at subsonic, transonic, and supersonic speeds, and especially during high lift operations for take-offs, landings, and sustained and instantaneous maneuvers. Topics of interest included vortex development and burst, modeling and validation of the full range of analytic methods, slender-body vortex flows at high angles of attack, vortex control and management, and unsteady vortex flow effects. In addition to the symposium papers, the results of the round table discussion are presented.

delta wings↗
NASA NTRS1997

Multidisciplinary Optimization of Tilt Rotor Blades Using Comprehensive Composite Modeling Technique

An optimization procedure is developed for addressing the design of composite tilt rotor blades. A comprehensive technique, based on a higher-order laminate theory, is developed for the analysis of the thick composite load-carrying sections, modeled as box beams, in the blade. The theory, which is based on a refined displacement field, is a three-dimensional model which approximates the elasticity solution so that the beam cross-sectional properties are not reduced to one-dimensional beam parameters. Both inplane and out-of-plane warping are included automatically in the formulation. The model can accurately capture the transverse shear stresses through the thickness of each wall while satisfying stress free boundary conditions on the inner and outer surfaces of the beam. The aerodynamic loads on the blade are calculated using the classical blade element momentum theory. Analytical expressions for the lift and drag are obtained based on the blade planform with corrections for the high lift capability of rotor blades. The aerodynamic analysis is coupled with the structural model to formulate the complete coupled equations of motion for aeroelastic analyses. Finally, a multidisciplinary optimization procedure is developed to improve the aerodynamic, structural and aeroelastic performance of the tilt rotor aircraft. The objective functions include the figure of merit in hover and the high speed cruise propulsive efficiency. Structural, aerodynamic and aeroelastic stability criteria are imposed as constraints on the problem. The Kreisselmeier-Steinhauser function is used to formulate the multiobjective function problem. The search direction is determined by the Broyden-Fletcher-Goldfarb-Shanno algorithm. The optimum results are compared with the baseline values and show significant improvements in the overall performance of the tilt rotor blade.

Chattopadhyay, Aditi↗
DOE OSTI2020

Characteristics of flow through randomly packed impermeable and permeable particles using pore resolved simulations

Pore resolved simulations are performed to study the mean flow characteristics in porous media formed by random distribution of impermeable and permeable particles. Here, permeability of the medium and reactive surface areas are analyzed for a range of solid fractions, packing patterns and flow rates. The results are compared with models presented in the literature and with simulations of flow through ordered packings. Permeability of a randomly packed porous medium is found to depend on the heterogeneous distribution of porosity which results from particle agglomeration and is typically ignored by simpler models. The reactive surface area is dependent on the flow field at pore scale in addition to geometry. Moreover, the wake formed downstream of the particles at moderately high flow rates also affects the reactive surface area. Similar analysis is also performed by assuming particles to be permeable to account for dual scale porosity relevant for various engineering applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Identifying High-Performance Metal–Organic Frameworks for Low-Temperature Oxygen Recovery from Helium by Computational Screening

Metal–organic frameworks (MOFs) are an important class of porous crystalline materials for applications ranging from gas adsorption and separation to catalysis. There are thousands of potential MOFs available for separation applications. Here, we developed a computational approach to screen MOFs for the separation of oxygen–helium mixtures at low temperatures (100–200 K), conditions that were motivated by issues associated with propulsion in space-based settings. We used detailed molecular simulations for a small number of MOFs to develop screening methods that were then used to estimate the optimum temperatures for separations using pressure swing adsorption for 2932 MOFs from the CoRE MOF database and the swing capacity and oxygen–helium selectivity at these temperatures. We used the stability of the best-performing structures in the presence of moisture as a means to provide a short list of high-performance materials. In addition to identifying specific materials for oxygen–helium separations, this approach could prove useful for selecting adsorbents for other gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

In Situ Phosphatizing of Triphenylphosphine Encapsulated within Metal–Organic Frameworks to Design Atomic Co 1 –P 1 N 3 Interfacial Structure for Promoting Catalytic Performance

The engineering coordination environment offers great opportunity in performance tunability of isolated metal single-atom catalysts. For the most popular metal–N x (MN x ) structure, the replacement of N atoms by some other atoms with relatively weak electronegativity has been regarded as a promising strategy for optimizing the coordination environment of an active metal center and promoting its catalytic performance, which is still a challenge. Herein, we proposed a new synthetic strategy of an in situ phosphatizing of triphenylphosphine encapsulated within metal–organic frameworks for designing atomic Co 1 –P 1 N 3 interfacial structure, where a cobalt single atom is costabilized by one P atom and three N atoms (denoted as Co-SA/P-in situ). In the acidic media, the Co-SA/P-in situ catalyst with Co 1 –P 1 N 3 interfacial structure exhibits excellent activity and durability for the hydrogen evolution reaction (HER) with a low overpotential of 98 mV at 10 mA cm –2 and a small Tafel slope of 47 mV dec –1 , which are greatly superior to those of catalyst with Co 1 –N 4 interfacial structure. We discover that the bond-length-extended high-valence Co 1 –P 1 N 3 atomic interface structure plays a crucial role in boosting the HER performance, which is supported by in situ X-ray absorption fine structure (XAFS) measurements and density functional theory (DFT) calculation. With this work, we hope to promote the development of high performance metal single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

New Trick for an Old Dog: From Prediction to Properties of “Hidden Clathrates” Ba 2 Zn 5 As 6 and Ba 2 Zn 5 Sb 6

The zinc–antimony phase space has been heavily investigated due to the structural complexity and abundance of high-performing thermoelectric materials. Consequentially, the desire to use zinc and antimony as framework elements to encage rattling cations and achieve phonon-glass-electron-crystal-type properties has remained an enticing goal with only two alkali metal clathrates to date, Cs 8 Zn 18 Sb 28 and K 58 Zn 122 Sb 207 . Guided by Zintl electron-counting predictions, here we explored the Ba–Zn–Pn (Pn = As, Sb) phase space proximal to the expected composition of the type-I clathrate. In situ powder X-ray diffraction studies revealed two “hidden” compounds which can only be synthesized in a narrow temperature range. The ex situ synthesis and crystal growth unveiled that instead of type-I clathrates, compositionally close but structurally different new clathrate-like compounds formed, Ba 2 Zn 5 As 6 and Ba 2 Zn 5 Sb 6 . These materials crystallize in a unique structure, in the orthorhombic space group Pmna with the Wyckoff sequence i 2 h 6 gfe. Single-phase synthesis enabled the exploration of their transport properties. Rattling of the Ba cations in oversized cages manifested low thermal conductivity, which, coupled with the high Seebeck coefficients observed, are prerequisites for a promising thermoelectric material. Potential for further optimization of the thermoelectric performance by aliovalent doping was computationally analyzed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Economic Extraction and Recovery of REEs and Production of Clean Value-Added Products from Low-Rank Coal Fly Ash

The University of North Dakota (UND) Energy & Environmental Research Center (EERC) teamed with Pacific Northwest National Laboratory (PNNL) , the North Dakota Industrial Commission Lignite Research Program, and commercial partners Basin Electric Power Cooperative, Great River Energy, and Southern Company to execute a Cooperative Agreement funded by the U.S. Department of Energy’s (DOE’s) National Energy Technology Laboratory (NETL) focused on identifying unique pathways and pretreatments to extract rare-earth elements (REEs) from low-rank coal (LRC) ash in a more economical and environmentally benign manner than current methods. The EERC drew upon the unique and deep knowledge of the team regarding LRC geochemistry, ash transformation mechanisms during combustion, and fly ash chemistry in the approach to understand the portioning of REEs in LRC ash. A comprehensive characterization effort was undertaken to fully establish the form, associations, and partitioning of the REEs and other elements/minerals of interest in fly ash, as well as the ash chemistry, mineralogy, and morphology. Using this information, the team tested methods of REE extraction to take advantage of the unique and advantageous properties of LRC ash. Multiple complementary approaches were evaluated that combined both novel and proven methods to develop an extractive process for REEs and other high-value metals from LRC ash that provide technological and economic progress on the current state of the art. Methodologies were also evaluated for the potential to synergistically remove toxic metals while extracting other high-value metals from the ash, generating a clean, safe ash material as a value-added product. This would eliminate waste and offer significant additional revenue potential. Based on laboratory-scale testing, an initial high-level technical and economic analysis to estimate operating expenses and product revenues to guide future phases of technology development was implemented. By focusing on minimizing process steps and consumptive use of extraction solutions, a tunable, economically viable process for REE extraction from LRC ash was developed. The tunable process has the ability to be adjusted to adapt to the differing ash chemical and physical properties that are characteristic of LRC ash. This is key to deployment as a commercial process. In demonstrating the process, the EERC was able to illustrate mixed REE concentration greater than the goal of 2 wt%. High-level economic analysis of the process with LRC ash of moderate REE levels demonstrated the potential of the process, but recovery of just the REEs was insufficient to cover operational costs. With the additional extraction of other high-value metals found in LRC ash, the process economics approach would break even, and it is anticipated that with process optimization, the developed process could potentially be economically sound. The same economic analysis performed utilizing LRC ash with high levels of REEs showed the recovery of the REEs alone would make the process economically viable even without further optimization.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1986

Performance of high area ratio nozzles for a small rocket thruster

Theoretical estimates of supersonic nozzle performance have been compared to experimental test data for nozzles with an area ratio of 100:1 conical and 300:1 optimum contour, and 300:1 nozzles cut off at 200:1 and 100:1. These tests were done on a Hughes Aircraft Company 5 lbf monopropellant hydrazine thruster with chamber pressures ranging from 25 to 135 psia. The analytic method used is the conventional inviscid method of characteristic with correction for laminar boundary layer displacement and drag. Replacing the 100:1 conical nozzle with the 300:1 contoured nozzle resulted in an improvement in thrust performance of 0.74 percent at chamber pressure of 25 psia to 2.14 percent at chamber pressure of 135 psia. The data is significant because it is experimental verification that conventional nozzle design techniques are applicable even where the boundary layer is laminar and displaces as much as 35 percent of the flow at the nozzle exit plane.

Kushida, R. O.↗
DOE OSTI2026

Ground and excited state gradients with end-to-end differentiable semiempirical quantum chemistry

Accurate and efficient gradients of molecular energy with respect to nuclear degrees of freedom are essential for geometry optimization and molecular dynamics, including simulations that go beyond the Born–Oppenheimer regime. A common approach involves deriving analytical formulas for new electronic structure methods, which is often conceptually difficult and requires tedious coding. Here, we implement analytical, semi-numerical, and automatic differentiation (AD)-based gradient pathways for semiempirical Hamiltonian models in the PYSEQM software package, leveraging both graphics processing unit (GPU) and central processing unit (CPU) architectures. We further extend these capabilities to excited states calculated using the configuration interaction singles and time-dependent Hartree–Fock ansätze. We benchmark wall time, peak memory usage, and accuracy across three molecular families of varying chemical complexity, including systems of up to a thousand atoms. For ground-state simulations, analytical and AD gradients achieve near-identical GPU runtimes, while semi-numerical gradients are slower on GPU but remain competitive on CPU. For excited states, both analytical and custom AD approaches using implicit differentiation show similar performance and low memory requirements, whereas gradients with full AD are memory-limited. AD gradients match analytical ones in accuracy across all tested systems, aided by a quaternion-based diatomic frame rotation for two-center quantities that ensures smooth energy surfaces. Overall, automatic differentiation emerges as a practical alternative to analytical gradients in semiempirical quantum chemistry, offering high accuracy while allowing seamless integration in AI-driven workflows and popular packages, such as PyTorch and JAX. Our results provide actionable guidance for selecting optimal gradient strategies in large-scale ground- and excited-state molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

CODEX weak lensing mass catalogue and implications on the mass–richness relation

The COnstrain Dark Energy with X-ray clusters (CODEX) sample contains the largest flux limited sample of X-ray clusters at 0.35 < z < 0.65. It was selected from ROSAT data in the 10 000 square degrees of overlap with BOSS, mapping a total number of 2770 high-z galaxy clusters. We present here the full results of the CFHT CODEX programme on cluster mass measurement, including a reanalysis of CFHTLS Wide data, with 25 individual lensing-constrained cluster masses. We employ lensfit shape measurement and perform a conservative colour–space selection and weighting of background galaxies. Using the combination of shape noise and an analytic covariance for intrinsic variations of cluster profiles at fixed mass due to large-scale structure, miscentring, and variations in concentration and ellipticity, we determine the likelihood of the observed shear signal as a function of true mass for each cluster. We combine 25 individual cluster mass likelihoods in a Bayesian hierarchical scheme with the inclusion of optical and X-ray selection functions to derive constraints on the slope α, normalization β, and scatter σln λ|μ of our richness–mass scaling relation model in log-space: ${\langle {\rm In}\,\, \lambda\!\!\mid\!\!\mu\rangle = \alpha\mu + \beta,} $ with μ = ln (M 200c /M piv ), and M piv = 10 14.81 M ⊙ . We find a slope $\alpha = 0.49^{+0.20}_{-0.15}$, normalization $\exp (\beta) = 84.0^{+9.2}_{-14.8}$, and $\sigma _{\ln \lambda | \mu } = 0.17^{+0.13}_{-0.09}$ using CFHT richness estimates. In comparison to other weak lensing richness–mass relations, we find the normalization of the richness statistically agreeing with the normalization of other scaling relations from a broad redshift range (0.0 < z < 0.65) and with different cluster selection (X-ray, Sunyaev–Zeldovich, and optical).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Global Experiences with HPC Operational Data Measurement, Collection and Analysis

As we move into the exascale era, supercomputers grow larger, denser, more heterogeneous, and ever more complex. Operating such machines reliably and efficiently requires deep insight into the operational parameters of the machine itself as well as its supporting infrastructure. To fulfill this need, early adopter sites have started the development and deployment of Operational Data Analytics (ODA) frameworks allowing the continuous monitoring, archiving, and analysis of near realtime performance data from the machine and infrastructure levels, providing immediately actionable information for multiple operational uses. To understand their ODA goals, requirements, and use cases, we have conducted a survey among eight early adopter sites from the US, Europe, and Japan that operate top 50 high-performance computing systems. We have assessed the technologies leveraged to build their ODA frameworks, identified use cases and other push and pull factors that drive the sites' ODA activities, and report on their operational lessons.

Ott, Michael↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Development and Validation of a Non-Invasive, Chairside Oral Cavity Cancer Risk Assessment Prototype Using Machine Learning Approach

Oral cavity cancer (OCC) is associated with high morbidity and mortality rates when diagnosed at late stages. Early detection of increased risk provides an opportunity for implementing prevention strategies surrounding modifiable risk factors and screening to promote early detection and intervention. Historical evidence identified a gap in the training of primary care providers (PCPs) surrounding the examination of the oral cavity. The absence of clinically applicable analytical tools to identify patients with high-risk OCC phenotypes at point-of-care (POC) causes missed opportunities for implementing patient-specific interventional strategies. This study developed an OCC risk assessment tool prototype by applying machine learning (ML) approaches to a rich retrospectively collected data set abstracted from a clinical enterprise data warehouse. We compared the performance of six ML classifiers by applying the 10-fold cross-validation approach. Accuracy, recall, precision, specificity, area under the receiver operating characteristic curve, and recall–precision curves for the derived voting algorithm were: 78%, 64%, 88%, 92%, 0.83, and 0.81, respectively. The performance of two classifiers, multilayer perceptron and AdaBoost, closely mirrored the voting algorithm. Integration of the OCC risk assessment tool developed by clinical informatics application into an electronic health record as a clinical decision support tool can assist PCPs in targeting at-risk patients for personalized interventional care.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1982

Shuttle lidar resonance fluorescence investigations. I - Analysis of Na and K measurements. II - Analysis of thermospheric Mg/+/ measurements

Optical radar systems (lidar) have a number of advantages compared to passive techniques with respect to applications involving the measurement of alkali atoms (Na and K) in the atmosphere. By using Shuttle-borne optical radar systems, analytical capabilities can be extended to cover wider geographic areas. One of the objectives of the present investigation is to assess the performance and application of a recently defined Shuttle optical radar system for the measurements of sodium and potassium in the 80-110-km region. A second objective is related to a study of the effects of high-intensity laser beams on the optical radar measurements, giving particular attention to the saturation in the atomic absorption of laser photons. A numerical simulation is conducted of the measurements of magnesium ions (Mg/+/) over the 80-500-km altitude range using recently defined Shuttle optical radar system parameters to study the performance of such a system.

Yeh, S.-D.↗
NASA NTRS1987

Computational fluid dynamics: Transition to design applications

The development of aerospace vehicles, over the years, was an evolutionary process in which engineering progress in the aerospace community was based, generally, on prior experience and data bases obtained through wind tunnel and flight testing. Advances in the fundamental understanding of flow physics, wind tunnel and flight test capability, and mathematical insights into the governing flow equations were translated into improved air vehicle design. The modern day field of Computational Fluid Dynamics (CFD) is a continuation of the growth in analytical capability and the digital mathematics needed to solve the more rigorous form of the flow equations. Some of the technical and managerial challenges that result from rapidly developing CFD capabilites, some of the steps being taken by the Fort Worth Division of General Dynamics to meet these challenges, and some of the specific areas of application for high performance air vehicles are presented.

Bradley, R. G.↗
NASA NTRS1993

Numerical simulation of a complete STOVL aifcraft in ground effect

The aerodynamic environment encountered by powered-lift aircraft operating in ground effect is unique among flight vehicles. It is characterized by low forward speed with embedded regions of high subsonic or supersonic jet flows. During ground effect operations, complex recirculating flows generated by the jets produce large changes in the aerodynamic loads on the flight vehicle. Analytic prediction and small-scale experimental methods have produced mixed results in this flight regime, with the result that costly full-scale powered tests are required to evaluate the performance of candidate designs. The ability to accurately predict vehicle performance without resorting to full-scale tests will be critical to future powered-lift aircraft projects. This paper summarizes efforts to predict the flow field about a powered-lift aircraft, the YAV-8B Harrier, in low level jet-borne flight by solution of the Reynolds-averaged Navier-Stokes equations. Results are compared to infrared images of the NASA YAV-8B Harrier V/STOL Systems Research Aircraft (VSRA) under similar flight conditions.

Smith, Merritt H.↗