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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

3D Localization of Defects in Facility Inspection

Wind tunnels are crucial facilities that support the aerospace industry. However, these facilities are large, complex, and pose unique maintenance and inspection requirements. Manual inspections to identify defects such as cracks, missing fasteners, leaks, and foreign objects are important but labor and schedule intensive. Our goal is to utilize small Unmanned Aircraft Systems (sUAS) and computer vision-based analysis to automate the inspection of the interior and exterior of NASA’s critical wind tunnel facilities. We detect missing fasteners as our defect class, and detect existing fasteners to provide potential future missing fastener sites for preventative maintenance. These detections are done on both 2D raw images and in 3D space to provide a visual reference and real world location to facilitate repairs. A dataset was created consisting of images taken along a grid-like pattern of an interior tunnel section in the AEDC National Full-Scale Aerodynamics Complex (NFAC) at NASA Ames Research Center. Our method uses object detection to create image level bounding boxes of the fasteners and missing fasteners, then uses photogrammetry to create a mapping from 2D image locations to 3D real world locations. The image level bounding boxes and the 2D to 3D mapping are then combined to determine the 3D location of the defects. We describe the data collection, photogrammetry, and computer vision techniques used for object detection as well as a quantitative analysis of the method.

Small Unmanned Aircraft Systems (sUAS)↗
NASA NTRSDate not supplied

SPIKE-Dx : A Low-Power High-Throughput Fault Diagnostics Tool using Spiking Neural Networks for Constrained Systems

Diagnostic systems are important for many aerospace systems, which are severely limited in available power, like cubesats or UAVs. Therefore, traditional diagnostics systems cannot be used due to their substantial footprint and constraints. In this paper, we present our very low power diagnostic tool SPIKE-DX to monitor critical systems with constrained computational and energy resources. This is made possible through spiking neural networks (SNNs), which are executable within optimized simulation environments and further implemented on on cutting-edge neuromorphic hardware. Based upon FMEA (Failure Mode and Effect Analysis) framework, Diagnostic Bayesian Networks (DBNs) can be constructed that provide powerful means for diagnostic reasoning. In this paper, we describe such DBNs and a method to automatically translate the DBN into highly structured networks of spiking neurons for execution in SPIKE-DX.

Spiking Neural Networks↗
NASA NTRS2017

A CFD Case Study of a Fan Stage with Split Flow Path Subject to Total Pressure Distortion Inflow

This report is the documentation of the work performed under the Hypersonic Project of the NASA's Fundamental Aeronautics Program. It was funded through Task Number NNC10E444T under GESS-2 Contract NNC06BA07B. The objective of the task is to develop advanced computational tools for the simulation of multi-stage turbomachinery in support of aeropropulsion. This includes work elements in extending the TURBO code and validating the multi-stage URANS (Unsteady Reynolds Averaged Navier Stokes) simulation results with the experimental data. The unsteady CFD (Computation Fluid Dynamics) calculations were performed in full wheel mode with and without screen generated total pressure distortion at the computational inflow boundary, as well as in single passage phase lag mode for uniform inflow. The experimental data were provided by NASA from the single stage RTA (Revolutionary Turbine Accelerator) fan test program.Significant non-uniform flow condition at the fan-face of the aeropropulsion system is frequentlyencountered in many of the advanced aerospace vehicles. These propulsion systems can be eithera podded or an embedded design employed in HWB (Hybrid Wing Body) airframe concept. It isalso a topic of interest in military applications, in which advanced air vehicles have already deployedsome form of embedded propulsion systems in their design because of the requirementsof compact and low observable inlets. Even in the conventional airframe/engine design, the fancould operate under such condition when the air vehicle is undergoing rapid maneuvering action.It is believed that a better understanding of the fan’s aerodynamic and aeromechanical responseto this type of operating condition or off design operation would be beneficial to designing distortiontolerant blades for improved engine operability.The objective for this research is to assess the capability of turbomachinery code as an analysistool in understanding the effects and evaluating the impact of flow distortion on the aerodynamicand aeromechanical performance of the fan in advanced propulsion systems. Results from thetesting of an advanced fan stage released by NASA are available and will be used here for CFDcode validation. The experiment was performed at NASA’s high speed compressor facility aspart of the RTA (Revolutionary Turbine Accelerator) demonstration project, a joint effort ofNASA Glenn Research Center and GE Aircraft Engines in developing an advanced Mach 4TBCC (Turbine Based Combined Cycle) turbofan/ramjet engine for access to space. Part of thetest was to assess the aerodynamic performance and operability of the fan stage under nonuniforminflow condition. Various flow distortion patterns were created at the fan-face by manipulatingsets of screens placed upstream of the wind tunnel. Measurements at the fan-face willprovide the necessary distortion flow information as the inflow boundary condition for the CFDin a full wheel simulation. Therefore the purpose of this work is to demonstrate the NASA supportedmulti-stage turbomachinery code, TURBO [1-5], in the aerodynamic performance analysisof a modern fan design operating under off design condition, and in particular to validate theCFD results with the RTA fan test data.A brief description of the RTA fan rig configuration is given in the next section, explaining onhow flow distortion were measured in the test and constructed for the CFD at the fan-face. It isfollowed by a section summarizing previous CFD work performed at NASA relevant to the currentfan configuration. A short description of the TURBO code is given next, followed by detailsin the computational model of the fan rig, the required computing resources, and the numericalprocedure for the simulations. The CFD results are presented in the discussion section and finallyconcluding remarks are summarized.

Fan Stage↗
DOE OSTI2025

Improving adhesive bonding of short carbon fiber thermoplastic composites to aluminum alloys with a hybrid laser-plasma surface modification strategy

This study investigates hybrid laser–plasma surface modification strategies for metal–CFRTP (carbon-fiber-reinforced thermoplastic polymer) dissimilar joints to improve their bonding performance, in contrast to existing literature that mostly focuses on either plasma or laser treatment alone. By conducting double cantilever beam (DCB) tests on adhesively-bonded AA5052 and CFRPA66 (carbon-fiber-reinforced polyamide 66) joints, as an example of metal–CFRTP joints, it was found that laser engraving on the metal surface combined with plasma treatment on the CFRTP surface significantly improved the specific fracture energy of the joint by 187% and 31% compared to as-received and plasma-treated-only joints, respectively. However, the hybrid treatment of laser engraving and plasma on the investigated CFRTP surface did not improve the bonding performance of the joints. The underlying mechanisms related to hybrid laser-plasma surface modification strategies were further investigated by examining the surface and cross-sectional morphologies after DCB testing using microscopy. Computational modeling was performed to elucidate the interaction between grooves on the metal substrate and the CFRTP–adhesive interfacial bonding in metal–CFRTP joints. This study provides new insights into developing surface modification methods for achieving strong metal–CFRTP adhesive joints, aimed at lightweighting structural components in automotive, aerospace, and other applications.

Adhesive bonding↗
NASA NTRS2001

Radiation transport modeling and assessment to better predict radiation exposure, dose, and toxicological effects to human organs on long duration space flights

NASA is very interested in improving its ability to monitor and forecast the radiation levels that pose a health risk to space-walking astronauts as they construct the International Space Station and astronauts that will participate in long-term and deep-space missions. Human exploratory missions to the moon and Mars within the next quarter century, will expose crews to transient radiation from solar particle events which include high-energy galactic cosmic rays and high-energy protons. Because the radiation levels in space are high and solar activity is presently unpredictable, adequate shielding is needed to minimize the deleterious health effects of exposure to radiation. Today, numerous models have been developed and used to predict radiation exposure. Such a model is the Space Environment Information Systems (SPENVIS) modeling program, developed by the Belgian Institute for Space Aeronautics. SPENVIS, which has been assessed to be an excellent tool in characterizing the radiation environment for microelectronics and investigating orbital debris, is being evaluated for its usefulness with determining the dose and dose-equivalent for human exposure. Thus far. the calculations for dose-depth relations under varying shielding conditions have been in agreement with calculations done using HZETRN and PDOSE, which are well-known and widely used models for characterizing the environments for human exploratory missions. There is disagreement when assessing the impact of secondary radiation particles since SPENVIS does a crude estimation of the secondary radiation particles when calculating LET versus Flux. SPENVIS was used to model dose-depth relations for the blood-forming organs. Radiation sickness and cancer are life-threatening consequences resulting from radiation exposure. In space. exposure to radiation generally includes all of the critical organs. Biological and toxicological impacts have been included for discussion along with alternative risk mitigation methods--shielding and anti-carcinogens. c 2001. Elsevier Science Ltd. All rights reserved.

STS-91 Shuttle Project↗
NASA NTRS2006

Hybrid Terrain Database

A prototype hybrid terrain database is being developed in conjunction with other databases and with hardware and software that constitute subsystems of aerospace cockpit display systems (known in the art as synthetic vision systems) that generate images to increase pilots' situation awareness and eliminate poor visibility as a cause of aviation accidents. The basic idea is to provide a clear view of the world around an aircraft by displaying computer-generated imagery derived from an onboard database of terrain, obstacle, and airport information.

Arthur, Trey↗
DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗
NASA NTRS2019

Generation of a Reduced-Order Model of an Unmanned Combat Air Vehicle Using Indicial Response Functions

Within the NATO STO AVT-251 Task Group, a generic Unmanned Combat Air Vehicle (UCAV) planform was redesigned based on requirements derived from parts of the flight envelope of the defined mission. Because of the lambda-shape planform and associated flow phenomena including shocks and vortices, the aerodynamic design process relies heavily on high-fidelity predictions from computational fluid dynamics (CFD). These simulations enable accurate flight dynamics predictions, allowing for the identification of any potential performance issues early in the design process. Potentially, a complete flight dynamics model can be derived from CFD calculations provided that the underlying reduced order model (ROM) captures the underlying physics contained within the CFD results. This work investigates the creation of a nonlinear ROM using indicial response functions. The response functions are obtained using a grid motion approach that separates the effects of angle of attack and pitch rate. This approach is demonstrated using three different CFD codes from various organizations: ENSOLV at Royal Netherlands Aerospace Centre, USM3D at NASA Langley Research Center, and Kestrel at the United States Air Force Academy. ROM predictions were generated for a manoeuver resembling a low-speed pull-up. The predictions are found to be sensitive to the quality of the steady-state solutions from which step-response calculations were started, as well as the convergence of the step responses themselves. Nevertheless, the indicial response method is shown to provide aerodynamic predictions with acceptable accuracy including transient effects, and as such is a promising method for computationally efficient flight dynamics predictions.

Michel P.C. van Rooij↗
DOE OSTI2025

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A deep learning and finite element approach for exploration of inverse structure–property designs of lightweight hybrid composites

Hybrid composites have important applications, such as high-performance and lightweight materials in aerospace and automotive industries. Hybrid composites utilize the synergy of diverse fillers to achieve desired material properties, but usually have more complicated microstructures. While topology optimization can optimize a particular property, designing hybrid composites for customized mechanical performances, e.g. full-range stress–strain curve, remains challenging. Here, a computational framework that integrated finite element analysis (FEA) and artificial intelligence (AI) methods of Conditional Generative Adversarial Networks (cGAN) deep learning and transfer learning was developed to establish inverse structure–property relationships and design tailor-made hybrid composites. Based on FEA-generated datasets of hybrid fiber-particle–matrix microstructures and their corresponding full-range stress–strain curves, a cGAN architecture was trained to generate tailored microstructures and establish structure–property relationships. Similarity in microstructural features and well-matched stress–strain curves based on the AI-generated composites were achieved. In conclusion, transfer learning was used to expand the pre-trained model for designing different materials systems.

Hybrid composites↗
NASA NTRS1980

Case study: Lockheed-Georgia Company integrated design process

A case study of the development of an Integrated Design Process is presented. The approach taken in preparing for the development of an integrated design process includes some of the IPAD approaches such as developing a Design Process Model, cataloging Technical Program Elements (TPE's), and examining data characteristics and interfaces between contiguous TPE's. The implementation plan is based on an incremental development of capabilities over a period of time with each step directed toward, and consistent with, the final architecture of a total integrated system. Because of time schedules and different computer hardware, this system will not be the same as the final IPAD release; however, many IPAD concepts will no doubt prove applicable as the best approach. Full advantage will be taken of the IPAD development experience. A scenario that could be typical for many companies, even outside the aerospace industry, in developing an integrated design process for an IPAD-type environment is represented.

Waldrop, C. T.↗
NASA NTRS1995

Investigation of wing upper surface flow-field disturbance due to NASA DC-8-72 in-flight inboard thrust-reverser deployment

An investigation of the wing upper surface flow-field disturbance due to in-flight inboard thrust reverser deployment on the NASA DC-8-72, which was conducted cooperatively by NASA Ames, the Federal Aviation Administration (FAA), McDonnell Douglas, and the Aerospace Industry Association (AIA), is outlined and discussed in detail. The purpose of this flight test was to obtain tufted flow visualization data which demonstrates the effect of thrust reverser deployment on the wing upper surface flow field to determine if the disturbed flow regions could be modeled by computational methods. A total of six symmetric thrust reversals of the two inboard engines were performed to monitor tuft and flow cone patterns as well as the character of their movement at the nominal Mach numbers of 0.55, 0.70, and 0.85. The tufts and flow cones were photographed and video-taped to determine the type of flow field that occurs with and without the thrust reversers deployed. In addition, the normal NASA DC-8 onboard Data Acquisition Distribution System (DADS) was used to synchronize the cameras. Results of this flight test will be presented in two parts. First, three distinct flow patterns associated with the above Mach numbers were sketched from the motion videos and discussed in detail. Second, other relevant aircraft parameters, such as aircraft's angular orientation, altitude, Mach number, and vertical descent, are discussed. The flight test participants' comments were recorded on the videos and the interested reader is referred to the video supplement section of this report for that information.

Hamid, Hedayat U.↗
NASA NTRS1987

NAECON 87; Proceedings of the IEEE National Aerospace and Electronics Conference, Dayton, OH, May 18-22, 1987. Volumes 1, 2, 3, & 4

The present conference discusses topics in VLSI components and their packaging, signal processing, uses of cartographic data, data transmission, advanced avionics architectures, fiber-optics, information control and display, image processing, airborne radar and fire control, navigation, air data, Kalman filtering, power generation and control, spacecraft power structures, aircraft flying qualities, flight management, fault-tolerant computer architectures, actuation technologies, self-repairing flight control system technology, multivariable control, stability and control methods, and AFTI/F-16 flight test reports. Also discussed are the ADA/JOVIAL language and its applications, software acquisition and testing, advanced software concepts, software management, computer graphics and visual systems softwear, ADA in embedded avionics, 16- and 32-bit architectures, voice interaction applications, human/machine systems analysis, human factors and AI, mental workloads and displays, pilot acceleration protection research, communications system technology, space communications, reliability and maintainability, managerial techniques, engineering management, EM compatibility and nuclear hardening, expert systems, AI language/knowledge representation, expert system implementation, machine vision/optical processing, and advanced AI concepts and architectures.

Avionics↗
NASA NTRS2020

Unstructured Grid Development for the Space Launch System Liftoff and Transition Lineloads Computational Analysis

Production of aerodynamic lineloads databases for the Space Launch System (SLS) vehicle at Liftoff and Transition (LOT) conditions has required the development of a Computational Fluid Dynamics (CFD) workflow capable of producing high-quality solutions for this unique phase of flight. Aerodynamic considerations included a wide range of flow angles (from 0°up to 90°total angle of attack), resulting leeside separation, and interaction effects between the three bodies of the integrated SLS vehicle, as well as the nearby launch tower. Computational mesh development for similar problems at the NASA Langley Research Center (such as for the Constellation/Ares launch vehicles) has primarily relied on in-house tools such as VGRID/POSTGRID, with grids designed for NASA-developed and maintained flow solvers such as USM3D and FUN3D. The workflow for such problems has evolved over the development of the various SLS configurations to incorporate new tools such as the Heldenpatch/Heldenmesh grid generator (Helden Aerospace) and CREATE-AV Kestrel (US Department of Defense) flow solver. This paper describes efforts to benchmark a grid generation approach for LOT problems using Heldenpatch/Heldenmesh and Kestrel, verified against prior best practices from VGRID/POSTGRID. Parameters studied include surface grid density, first-layer viscous cell height, and volume grid growth rate parameters. Resulting solutions are compared based on total force and moment values, sectional line loads, and surface pressures, all validated against existing wind tunnel aerodynamic databases where available for the SLS Block 1B Cargo configuration.

Space launch systems↗
NASA NTRS1987

Automating the parallel processing of fluid and structural dynamics calculations

The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilities to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.

Arpasi, Dale J.↗
NASA NTRS1987

Yesterday, today and tomorrow: A perspective of CFD at NASA's Ames Research Center

The opportunity to reflect on the computational fluid dynamics (CFD) progam at the NASA Ames Research Center (its beginning, its present state, and its direction for the future) is afforded. Essential elements of the research program during each period are reviewed, including people, facilities, and research problems. The burgeoning role that CFD is playing in the aerospace business is discussed, as is the necessity for validated CFD tools. The current aeronautical position of this country is assessed, as are revolutionary goals to help maintain its aeronautical supremacy in the world.

Kutler, Paul↗
NASA NTRS1987

Automating the parallel processing of fluid and structural dynamics calculations

The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilties to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.

Arpasi, Dale J.↗
NASA NTRS1997

Dynamic Analysis of a Two Member Manipulator

Attenuating start-up and stopping vibrations when maneuvering large payloads attached to flexible manipulator systems is a great concern for many space missions. To address this concern, it was proposed that the use of smart materials, and their applications in smart structures, may provide an effective method of control for aerospace structures. In this paper, a modified finite element model has been developed to simulate the performance of piezoelectric ceramic actuators, and was applied to a flexible two-arm manipulator system. Connected to a control voltage, the piezoelectric actuators produce control moments based on the optimal control theory. The computer simulation modeled the end-effector vibration suppression of the NASA manipulator testbed for berthing operations of the Space Shuttle to the Space Station. The results of the simulation show that the bonded piezoelectric actuators can effectively suppress follow-up vibrations of the end-effector, stimulated by some external disturbance.

McGinley, W. Mark↗