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All sources NASA NTRS DOE OSTI

NASA NTRS2007

A Case Study Using Modeling and Simulation to Predict Logistics Supply Chain Issues

Optimization of critical supply chains to deliver thousands of parts, materials, sub-assemblies, and vehicle structures as needed is vital to the success of the Constellation Program. Thorough analysis needs to be performed on the integrated supply chain processes to plan, source, make, deliver, and return critical items efficiently. Process modeling provides simulation technology-based, predictive solutions for supply chain problems which enable decision makers to reduce costs, accelerate cycle time and improve business performance. For example, United Space Alliance, LLC utilized this approach in late 2006 to build simulation models that recreated shuttle orbiter thruster failures and predicted the potential impact of thruster removals on logistics spare assets. The main objective was the early identification of possible problems in providing thruster spares for the remainder of the Shuttle Flight Manifest. After extensive analysis the model results were used to quantify potential problems and led to improvement actions in the supply chain. Similarly the proper modeling and analysis of Constellation parts, materials, operations, and information flows will help ensure the efficiency of the critical logistics supply chains and the overall success of the program.

Tucker, David A.↗

DOE OSTI2024

DOC-DICAM: Domain Aware One Class Defect Identification in Composite Aerostructure Material

Fiber-reinforced composites are a common material used in the design of aircraft structures due to their good tensile strength and resistance to compression. During the manufacturing process, these structures are thoroughly inspected for flaws and defects to ensure structural integrity during commercial use. Non-destructive testing (NDT) is a collection of inspection methods that allow inspectors to evaluate material without altering it. Due to the high safety standards in aerospace manufacturing, the NDT process is done manually and can be a significant bottleneck in the development workflow. In this paper, we develop an AI-based assistance tool to drastically reduce inspection time. Typical AI workflows require large amounts of annotated data, but defects rarely occur resulting in strong class imbalance. To overcome this, we formulate the problem of defect identification as an anomaly detection task in which our primary focus is learning non-defect characteristics. To do this, we develop a multi-task self-supervised learning framework that embeds problem specific domain knowledge into the deep learning model. We verify our method using fuselage data generated in a production environment. As a result, we show that our method can effectively identify defects and requires minimal training and inference time.

anomaly detection↗

NASA NTRS1987

Frequency domain synthesis of optimal inputs for adaptive identification and control

The input design problem of selecting appropriate inputs for use in SISO adaptive identification and model reference adaptive control algorithms is considered. Averaging theory is used to characterize the optimal inputs in the frequency domain. The design problem is formulated as an optimization problem which maximizes the smallest eigenvalue of the average information matrix over power constrained signals, and the global optimal solution is obtained using a convergent numerical algorithm. A bound on the frequency search range required in the design algorithm has been determined in terms of the desired performance.

Fu, Li-Chen↗

NASA NTRS1995

Wing-section optimization for supersonic viscous flows

The recent interest in High Speed Civil Transport (HSCT) has resulted in renewed research studies of optimized supersonic cruise transport configurations. Incorporation of flow viscosity effects in the design process of such a supersonic wing is currently under investigation. This may lead to more accurate problem formulations and, in turn, greater aerodynamic efficiency than can be obtained by the traditional, inviscid, linear theories. In this context, for a design code to be a candidate for a complex optimization problem, such as three-dimensional viscous supersonic wing design, it should be validated using simpler building-block shapes. To optimize the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wing design task, the present investigation concentrated on testing the flexibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with very similar features. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber, which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and the sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for problem formulations which should contribute to an effective wing shape optimization.

Item, Cem C.↗

NASA NTRS1995

Dissipative rendering and neural network control system design

Model-based control system designs are limited by the accuracy of the models of the plant, plant uncertainty, and exogenous signals. Although better models can be obtained with system identification, the models and control designs still have limitations. One approach to reduce the dependency on particular models is to design a set of compensators that will guarantee robust stability to a set of plants. Optimization over the compensator parameters can then be used to get the desired performance. Conservativeness of this approach can be reduced by integrating fundamental properties of the plant models. This is the approach of dissipative control design. Dissipative control designs are based on several variations of the Passivity Theorem, which have been proven for nonlinear/linear and continuous-time/discrete-time systems. These theorems depend not on a specific model of a plant, but on its general dissipative properties. Dissipative control design has found wide applicability in flexible space structures and robotic systems that can be configured to be dissipative. Currently, there is ongoing research to improve the performance of dissipative control designs. For aircraft systems that are not dissipative active control may be used to make them dissipative and then a dissipative control design technique can be used. It is also possible that rendering a system dissipative and dissipative control design may be combined into one step. Furthermore, the transformation of a non-dissipative system to dissipative can be done robustly. One sequential design procedure for finite dimensional linear time-invariant systems has been developed. For nonlinear plants that cannot be controlled adequately with a single linear controller, model-based techniques have additional problems. Nonlinear system identification is still a research topic. Lacking analytical models for model-based design, artificial neural network algorithms have recently received considerable attention. Using their universal approximation property, neural networks have been introduced into nonlinear control designs in several ways. Unfortunately, little work has appeared that analyzes neural network control systems and establishes margins for stability and performance. One approach for this analysis is to set up neural network control systems in the framework presented above. For example, one neural network could be used to render a system to be dissipative, a second strictly dissipative neural network controller could be used to guarantee robust stability.

Gonzalez, Oscar R.↗

NASA NTRS2009

Detection, Identification, Location, and Remote Sensing using SAW RFID Sensor Tags

In this presentation, we will consider the problem of simultaneous detection, identification, location estimation, and remote sensing for multiple objects. In particular, we will describe the design and testing of a wireless system capable of simultaneously detecting the presence of multiple objects, identifying each object, and acquiring both a low-resolution estimate of location and a high-resolution estimate of temperature for each object based on wireless interrogation of passive surface acoustic wave (SAW) radiofrequency identification (RFID) sensor tags affixed to each object. The system is being studied for application on the lunar surface as well as for terrestrial remote sensing applications such as pre-launch monitoring and testing of spacecraft on the launch pad and monitoring of test facilities. The system utilizes a digitally beam-formed planar receiving antenna array to extend range and provide direction-of-arrival information coupled with an approximate maximum-likelihood signal processing algorithm to provide near-optimal estimation of both range and temperature. The system is capable of forming a large number of beams within the field of view and resolving the information from several tags within each beam. The combination of both spatial and waveform discrimination provides the capability to track and monitor telemetry from a large number of objects appearing simultaneously within the field of view of the receiving array. In the presentation, we will summarize the system design and illustrate several aspects of the operational characteristics and signal structure. We will examine the theoretical performance characteristics of the system and compare the theoretical results with results obtained from experiments in both controlled laboratory environments and in the field.

Barton, Richard J.↗

DOE OSTI2024

Quantum-centric supercomputing for materials science: A perspective on challenges and future directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Computationally hard tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their resources for simulation, analysis, and data processing. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. Here in this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Minimum stabilizing energy release for mixing processes

Diffusive operations, which mix the populations of different elements of phase space, can irreversibly transform a given initial state into any of a spectrum of different states from which no further energy can be extracted through diffusive operations. We call these ground states. Here, the lower bound of accessible ground-state energies represents the maximal possible release of energy. This lower bound, sometimes called the diffusively accessible free energy, is of interest in theories of instabilities and wave-particle interactions. On the other hand, the upper bound of accessible ground-state energies has escaped identification as a problem of interest. Yet, as demonstrated here, in the case of a continuous system, it is precisely this upper bound that corresponds to the paradigmatic “quasilinear plateau” ground state of the bump-on-tail distribution. Although for general discrete systems the complexity of calculating the upper bound grows rapidly with the number of states, using techniques adapted from treatments of the lower bound, the upper bound can in fact be computed directly for the three-state discrete system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

TEMPEST

This repository solves the problem of driver identification through vehicular and biometric data. Through an embedding-based approach and a novel loss function, we're able to distinguish between different drivers' behaviors. This also provides preprocessing for reproducibility of results.The code preprocesses vehicular data, trains neural networks, and outputs predictions.This code introduces a novel embedding-based neural network with a 91% rank-1 accuracy, as well as all code to reproduce training and results.

Musgrove, Kyle↗

DOE OSTI2022

Adaptive Neurocontrol for Grid-Following Inverters

The new generation of power systems involve a large number of autonomous operating units with the flow of data being restricted by privacy concerns or infrastructure hurdles. The systems are also time-varying so the control should adjust in a timely manner to avoid failures that usually have very negative economical implications. Adaptive neurocontrol which takes elements from adaptive control (great for time-varying problems) and model identification (could be in the form of neural network) by using local available data is a compelling tool. In this work, we summarize analytical results for adaptive neurocontrol, followed with numerical verification of how the method could work for future grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

36 MATERIALS SCIENCE↗

NASA NTRS1971

Study of aircraft in intraurban transportation systems, volume 1

An analysis of an effective short range, high density computer transportation system for intraurban systems is presented. The seven county Detroit, Michigan, metropolitan area, was chosen as the scenario for the analysis. The study consisted of an analysis and forecast of the Detroit market through 1985, a parametric analysis of appropriate short haul aircraft concepts and associated ground systems, and a preliminary overall economic analysis of a simplified total system designed to evaluate the candidate vehicles and select the most promising VTOL and STOL aircraft. Data are also included on the impact of advanced technology on the system, the sensitivity of mission performance to changes in aircraft characteristics and system operations, and identification of key problem areas that may be improved by additional research. The approach, logic, and computer models used are adaptable to other intraurban or interurban areas.

Stout, E. G.↗

NASA NTRS1971

Determination of the charge of relativistic heavy nuclei from emulsion tracks

The number of delta rays with energies between 50 and 150 keV that are produced by heavy nuclei in emulsions is calculated. The Z(2) dependence predicted by the first Born approximation is corrected by a direct calculation of the Mott exact phase-shift scattering cross section. Comparisons are made with corrections predicted by the second Born approximation. When the phase-shift results are applied to the problem of charge identification, corrections of up to 4 units of charge for 1.457-GeV/nucleon nuclei with charge Z = 75 are found.

Morgan, S. H., Jr.↗

NASA NTRS1972

Rotor systems research aircraft predesign study. Volume 3: Predesign report

The features of two aircraft designs were selected to be included in the single RSRA configuration. A study was conducted for further preliminary design and a more detailed analysis of development plans and costs. An analysis was also made of foreseeable technical problems and risks, identification of parallel research which would reduce risks and/or add to the basic capability of the aircraft, and a draft aircraft specification.

Schmidt, S. A.↗

NASA NTRS1973

Thermal-dynamic modeling study

Study provides basic information for designing models and conducting thermal-dynamic structural tests. Factors considered are development and interpretation of thermal-dynamic structural scaling laws; identification of major problem areas; and presentation of model fabrication, instrumentation, and test procedures.

Ojalvo, I. U.↗

NASA NTRS1975

Importance of helicopter dynamics to the mathematical model of the helicopter

A mathematical model of the helicopter requires appropriate representation of the constituent elements of rotor dynamics. General-purpose programs that model a variety of configurations for a broad range of operating conditions result in varying and incompatible levels of sophistication. Analysis of specific dynamic problems facilitates the identification of configuration parameters which determine system behavior. For the present analysis, the nonlinear equations of a torsionally rigid hingeless rotor are linearized about an equilibrium condition to determine flap-lag stability characteristics in hover. A collocation method was used to obtain the coupled natural frequencies and modes. These modes allow exact treatment of the effect of elastic coupling which more than compensates for the destabilizing inertial coupling. The sensitivity of damping to the number of modes was found to be small, and reasonable accuracy was obtained the first flapwise and edgewise coupled modes. The range of destabilizing precone was found to be small.

White, W. F., Jr.↗

NASA NTRS1974

A search for soft X-ray emission from red-giant coronae

Hills has pointed out that if red-giant coronae are weak sources of soft X-rays, then the problems of the identification of the local component of the soft X-ray background and the observed lack of gas in globular clusters may be simultaneously resolved. Using instrumentation aboard OAO Copernicus, we have searched unsuccessfully for emission in the 10-100 A band from four nearby red giants. In all cases, our upper limits are of the order of the minimum theoretically predicted fluxes.

Margon, B.↗

NASA NTRS1975

The role of toxicology in the Apollo space program

Some of the major considerations are presented which governed the formation and application of the toxicology program employed in support of the Apollo program. The overriding concern of the program was the safety of crews exposed to trace contaminant gases for extended periods of time. The materials screening program employed, in conjunction with a well designed spacecraft environmental control system, helped to attain the goals set forth for the Apollo program. The knowledge gained from working with the toxicity problems and the identification of compounds in the space cabin atmosphere are of importance for continued efforts in manned space flight. Tabular data of spacecraft contaminants are presented.

Wayland J. Rippstein, Jr↗