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At least 397 records · Page 22

A prediction of high-speed rotor noise

A combined computational (CFD) and integral approach solves the acoustic pressure fields of two high-speed helicopter rotors. A CFD code supplies boundary data to a non-linear type of Kirchhoff integral formulation to find the far-field pressures. Direct calculations of pressures are given by the CFD code up to the sonic cylinder where the Kirchhoff method takes over. This paper shows predictions and measurements of High-Speed Impulsive (HSI) noise in hover for two different rotor geometries. One rotor has a conventional rectangular planform, while the other rotor is highly swept and tapered. The swept rotor analysis forms the majority of this paper. Test data from both rotors are shown and compared with predictions for a range of tip Mach numbers from .85 to .95 (including delocalization). The correlation with the near-field pressures from the straight bladed experiment is excellent and good to excellent correlation is seen for the far-field pressures from both experiments.

Purcell, Timothy W.↗

Separability of soils in a tallgrass prairie using SPOT and DEM data

An investigation is conducted which uses a canonical transformation technique to reduce the features from SPOT and DEM data and evaluates the statistical separability of several prairie soils from the canonically transformed variables. Both SPOT and DEM data was gathered for a tallgrass prairie near Manhattan, Kansas, and high resolution SPOT satellite images were integrated with DEM data. Two canonical variables derived from training samples were selected and it is suggested that canonically transformed data were superior to combined SPOT and DEM data. High resolution SPOT images and DEM data can be used to aid second-order soil surveys in grasslands.

Su, Haiping↗

Advanced Stirling Convertor Heater Head Durability and Reliability Quantification

The National Aeronautics and Space Administration (NASA) has identified the high efficiency Advanced Stirling Radioisotope Generator (ASRG) as a candidate power source for long duration Science missions, such as lunar applications, Mars rovers, and deep space missions, that require reliable design lifetimes of up to 17 years. Resistance to creep deformation of the MarM-247 heater head (HH), a structurally critical component of the ASRG Advanced Stirling Convertor (ASC), under high temperatures (up to 850 C) is a key design driver for durability. Inherent uncertainties in the creep behavior of the thin-walled HH and the variations in the wall thickness, control temperature, and working gas pressure need to be accounted for in the life and reliability prediction. Due to the availability of very limited test data, assuring life and reliability of the HH is a challenging task. The NASA Glenn Research Center (GRC) has adopted an integrated approach combining available uniaxial MarM-247 material behavior testing, HH benchmark testing and advanced analysis in order to demonstrate the integrity, life and reliability of the HH under expected mission conditions. The proposed paper describes analytical aspects of the deterministic and probabilistic approaches and results. The deterministic approach involves development of the creep constitutive model for the MarM-247 (akin to the Oak Ridge National Laboratory master curve model used previously for Inconel 718 (Special Metals Corporation)) and nonlinear finite element analysis to predict the mean life. The probabilistic approach includes evaluation of the effect of design variable uncertainties in material creep behavior, geometry and operating conditions on life and reliability for the expected life. The sensitivity of the uncertainties in the design variables on the HH reliability is also quantified, and guidelines to improve reliability are discussed.

Krause, David L.↗

Evaluation of an Arrival Coordinator Position in a Terminal Metering Enviornment

NASA has developed an integrated arrival-management solution for terminal area precision scheduling (TAPSS). Ahuman-in-the-loop simulation investigated the performance of the components of the TAPSS system. The focus ofthis paper is set on the terminal radar approach control (TRACON) traffic management controller (TMC) and ArrivalRadar Coordinator (ARC) combined position, which played an integral part in coordinating, adjusting, and instantiatingthe arrival schedule computed by the TAPSS system. Analysis of the simulation data highlights the roleof the ARC within the described terminal metering environment, describes his planning strategies, the interactionswith his tools and coordination with controllers, and lends insights to the impact of the ARCs actions to the arrivalproblem. High levels of comfort and confidence were reported when working with the TAPSS system. Challengesposed the sequencing of unscheduled satellite arrival flights during periods of peak demand. To accommodate thoseflights into the arrival stream, the ARC had to identify sequence slots, while minimizing disruptions to the schedule.

terminal metering↗

Portable Laser Guided Robotic Metrology System

This paper introduces the new Portable Laser Guided Robotic antenna range (PLGR) at the National Aeronautics and Space Administration's (NASA) Glenn Research Center. Previous work used industrial robots in fixed facilities to characterize antennas and required fixtures that do not lend themselves to portable applications.NASA's PLGR system is designed for in-situ antenna measurements at a remote site. The system consists of a robot arm mounted on a vertical lift and a laser tracker, each on a portable base. The lift and laser tracker enable scanning a surface larger than the robot's reach. To accomplish this the robot first collects all points within its reach, then the system is moved and the laser tracker is used to relocate the robot before additional points are captured.The PLGR architecture will be discussed including how safety systems and path planning are combined to effectively characterize antennas. Software was written in high level languages for flexible integration of vector network analyzers and antenna controllers. Lastly, data will be shown to demonstrate the system functionality and accuracy.

Slater, Peter A.↗

Ares I and Ares V First Stage - Powering Exploration

The National Aeronautics and Space Administration (NASA) Ares Projects Office (APO) is continuing to make progress toward the final design of the first stage propulsion system for the Ares I crew launch vehicle and the Ares V cargo launch vehicle. Ares I and Ares V will provide the space launch capabilities needed to fulfill NASA' s exploration strategy of sending human beings to the Moon, Mars, and beyond. As primary propulsion for the Ares launch vehicles, the Space Shuttle-derived Reusable Solid Rocket Motor (RSRM) is one of the first and most important components to be tested. The first flight of Ares I, called Ares I-X, will occur in April 2009, with booster integration to begin at Kennedy Space Center (KSC) by autumn 2008. The Ares I-X flight will use a combination of flight and simulation hardware to obtain data on controlling the long and narrow crew launch vehicle configuration. The test will use a four-segment RSRM from the Shuttle inventory and a fifth spacer segment to simulate the size and weight of the operational five-segment motor to be used on later flights. The upper stage, Orion crew exploration vehicle, and launch abort system will all be replaced with simulator hardware. Manufacturing work has begun on the spacer segment, as well as the new forward hardware for the booster. Atlas V avionics will be adapted to control Ares I-X' s first stage. That hardware is undergoing hardware-in-the-loop testing in a contractor-provided systems integration laboratory (SIL); a critical design review (CDR) was completed in December 2007. Drogue and main parachute drop tests have also been conducted successfully at Yuma Proving Grounds, allowing the First Stage team to begin fabricating parachutes for Ares I-X. The Ares I-X flight test will be the first flight test for the parachutes. A series of preliminary design technical interchange meetings is being conducted prior to the Ares I-X CDR in January 2007 to ensure readiness for the flight. Much of the First Stage activity in 2007 has focused on a series of preliminary design (PDR) activities associated with each booster subsystem. These events will culminate in a formal preliminary design review in 2008, where subsystems and component specifications will be developed and associated analyses and drawings will be evaluated for technical adequacy. The first stage also has been undergoing a series of trade studies to determine means for upgrading booster performance and reducing operational costs. Performance improvement studies have included changing from polybutadiene acrylonitrile (PBAN) propellant to hydroxyl-terminated polybutadiene (HTPB); replacing aluminum with composite motor casings; and optimizing or upgrading the propellant grain and nozzle structures. Some or all of these changes could result in a block upgrade to the Ares I first stage, after becoming the standard configuration for the Ares V. The cost reduction studies included a change from reusable or recoverable boosters to completely expendable boosters; changing from hydrazine-powered to more environmentally friendly electrohydrostatic actuators (EHAs) on the thrust vector control (TVC) system; and changing the location of the separation plane to reduce the likelihood of recontact upon booster separation. The expendability trade study resulted in a decision to keep the recoverable boosters, as the new hardware costs significantly outweighed the potential operational cost savings due to reduced ground operations. Likewise, due to cost considerations, the team continued using existing hydrazine-powered actuators for the TVC system. The separation plane location for Ares I is still being studied, with results to be announced in 2008. In short, the Ares launch vehicles' first stage is building upon NASA's close familiarity with this Shuttle-derived system, while continuing to seek out improvements for long-term exploration.

Priskos, Alex S.↗

Projection-based multifidelity linear regression for data-scarce applications

Surrogate modeling for systems with high-dimensional quantities of interest remains challenging, particularly when training data are costly to acquire. This work develops multifidelity methods for multiple-input multiple-output linear regression targeting data-limited applications with high-dimensional outputs. Multifidelity methods integrate many inexpensive low-fidelity model evaluations with limited, costly high-fidelity evaluations. We introduce two projection-based multifidelity linear regression approaches with linear and nonlinear features that leverage principal component basis vectors for dimensionality reduction and combine multifidelity data through: (i) a direct data augmentation using low-fidelity data, and (ii) a data augmentation incorporating explicit linear corrections between low-fidelity and high-fidelity data. The data augmentation approaches combine high-fidelity and low-fidelity data into a unified training set and train the linear regression model through weighted least squares with fidelity-specific weights. We introduce a proximity-based weighting scheme with automatic weight selection strategy through cross-validation. Here, the proposed multifidelity linear regression methods are demonstrated on approximating the surface pressure field of a hypersonic vehicle in flight and the temperature field on an aircraft disc braking system. In an ultra low-data regime of no more than twelve high-fidelity samples, multifidelity linear regression achieves approximately 2% – 12% improvement in median accuracy and a higher R 2 score relative to single-fidelity methods at comparable computational cost.

data augmentation↗

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng↗

Software Tool Integrating Data Flow Diagrams and Petri Nets

Data Flow Diagram - Petri Net (DFPN) is a software tool for analyzing other software to be developed. The full name of this program reflects its design, which combines the benefit of data-flow diagrams (which are typically favored by software analysts) with the power and precision of Petri-net models, without requiring specialized Petri-net training. (A Petri net is a particular type of directed graph, a description of which would exceed the scope of this article.) DFPN assists a software analyst in drawing and specifying a data-flow diagram, then translates the diagram into a Petri net, then enables graphical tracing of execution paths through the Petri net for verification, by the end user, of the properties of the software to be developed. In comparison with prior means of verifying the properties of software to be developed, DFPN makes verification by the end user more nearly certain, thereby making it easier to identify and correct misconceptions earlier in the development process, when correction is less expensive. After the verification by the end user, DFPN generates a printable system specification in the form of descriptions of processes and data.

Thronesbery, Carroll↗

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

Initial Development of a Metric to Describe the Level of Safety Associated with Piloting an Aircraft with Synthetic Vision Systems (SVS) Displays

Synthetic Vision Systems (SVS) displays provide pilots with a continuous view of terrain combined with integrated guidance symbology in an effort to increase situation awareness (SA) and decrease workload during operations in Instrument Meteorological Conditions (IMC). It is hypothesized that SVS displays can replicate the safety and operational flexibility of flight in Visual Meteorological Conditions (VMC), regardless of actual out-the-window (OTW) visibility or time of day. Significant progress has been made towards evolving SVS displays as well as demonstrating their ability to increase SA compared to conventional avionics in a variety of conditions. While a substantial amount of data has been accumulated demonstrating the capabilities of SVS displays, the ability of SVS to replicate the safety and operational flexibility of VMC flight performance in all visibility conditions is unknown to any specific degree. In order to more fully quantify the relationship of flight operations in IMC with SVS displays to conventional operations conducted in VMC, a fundamental comparison to current day general aviation (GA) flight instruments was warranted. Such a comparison could begin to establish the extent to which SVS display concepts are capable of maintaining an "equivalent level of safety" with the round dials they could one day replace, for both current and future operations. A combination of subjective and objective data measures were used to quantify the relationship between selected components of safety that are associated with flying an approach. Four information display methods ranging from a "round dials" baseline through a fully integrated SVS package that includes terrain, pathway based guidance, and a strategic navigation display, were investigated in this high fidelity simulation experiment. In addition, a broad spectrum of pilots, representative of the GA population, were employed for testing in an attempt to enable greater application of the results and determine if "equivalent levels of safety" are achievable through the incorporation of SVS technology regardless of a pilot's flight experience.

Bartolone, Anthony P.↗

Automated and High-Throughput Phase Separation Control for Supramolecular Polymer Blends Enabled by Machine Learning

Supramolecular polymer blends (SPBs) offer tunable morphologies that dictate their macroscopic properties, yet their rational design is limited by the absence of predictive structure−morphology models. Here, we introduce a data-driven highthroughput workflow that integrates modular polymer synthesis, robotic formulation, automated morphology characterization, and machine learning (ML) for accelerated SPB discovery. Using a plug-and-play synthetic strategy, 33 hydrogen-bonding endfunctional homopolymers were prepared and orthogonally combined to generate 260 SPBs in 1 day. A fully automated atomic force microscopy (AFM) pipeline enabled systematic imaging, producing 2340 morphology data sets with minimal human intervention. Domain spacings were extracted through complementary imageprocessing methods and used to train ML models. A support vector regression (SVR) model accurately predicted target phase-separation sizes (50, 100, and 150 nm), which were experimentally validated. This work demonstrates the power of coupling high-throughput experimentation with ML to accelerate morphology discovery and provides one of the first large-scale experimental data sets for supramolecular polymer systems.

ML-guided polymer design↗

Preliminary NoMAD Results of the MUSIC Experiment

The Measurement of Uranium Subcritical and Critical (MUSiC) experiment was carried out from December 2020 through April 2021 at the National Criticality Experiments Research Center (NCERC). This measurement campaign featured bare configurations of the Rocky Flats highly-enriched uranium (HEU) shells, with each configuration having different numbers of these shells. The goal of the experiment was to test multiple neutron multiplicity detectors and measurement methods for a large range of neutron multiplication values, to see when the combination of detectors and methods break down as the configurations reach the delayed supercritical window. Adding subcritical integral benchmarks gives additional validation to nuclear data. These benchmarks provide additional parameters against which to validate the data. While critical benchmarks have just a single value, $K_{eff}$ , subcritical benchmarks can be used to infer multiple parameters. As an example, recent subcritical benchmarks utilizing the Hage-Cifarelli formalism have three quantities of interest ($R_{1}$, $R_{2}$, and $M_{L}$). This gives nuclear data evaluators additional data to use when performing their evaluations, and allows for these benchmarks to be useful for additional types of nuclear data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Spread-spectrum code acquisition in the presence of Doppler shift and data modulation

A spread-spectrum code acquisition technique for a direct-sequence (DS) system in the presence of Doppler effect and data modulation is investigated. Both the carrier-frequency offset and code-frequency offset due to severe Doppler effect are considered. The code-chip slipping during the correlation process caused by code-frequency offset can degrade the acquisition performance significantly. However, this issue can be alleviated by compensating code-frequency offset in an appropriate manner. Results are presented for the cases with and without data modulation. Coherent detection is considered when there is no data modulation. If data modulation is present, the authors partition the correlation time into subintervals and the integration results in these subintervals are square-law noncoherently combined for detection. The implementation of this code acquisition technique using the fast Fourier transform (FFT) algorithm is described. The use of theoretical results to estimate the hardware complexity of an actual system is illustrated step by step, showing that implementation is feasible with existing technology. The tradeoff between hardware complexity and acquisition performance is discussed.

Cheng, Unjeng↗

Experimental investigation of wing installation effects on a two-dimensional mixer/ejector nozzle for supersonic transport aircraft

Experimental results from a wind tunnel test conducted to investigate propulsion/airframe integration (PAI) effects are presented. The objectives of the test were to examine rough order-of-magnitude changes in the acoustic characteristics of a mixer/ejector nozzle due to the presence of a wing and to obtain limited wing and nozzle flow-field measurements. A simple representative supersonic transport wing planform, with deflecting flaps, was installed above a two-dimensional mixer/ejector nozzle that was supplied with high-pressure heated air. Various configurations and wing positions with respect to the nozzle were studied. Because of hardware problems, no acoustics and only a limited set of flow-field data were obtained. For most hardware configurations tested, no significant propulsion/airframe integration effects were identified. Significant effects were seen for extreme flap deflections. The combination of the exploratory nature of the test and the limited flow-field instrumentation made it impossible to identify definitive propulsion/airframe integration effects.

Anderson, David J.↗

Interpretation of Ion Irradiation and Neutron Irradiation Damage in Additively Manufactured 316 Stainless Steel using Multiscale Modeling

The accelerated adoption of nuclear energy necessitates advanced manufacturing technologies, such as additive manufacturing, to meet heightened supply chain requirements and support innovative reactor technologies. Due to the unique microstructural characteristics of additively manufactured materials under distinct solidification conditions, comprehensive evaluation of their performance in reactor environments is essential. The Advanced Materials and Manufacturing Technologies program under the Department of Energy's Office of Nuclear Energy focuses on understanding the irradiation performance and damage evolution of laser powder bed fusion 316 stainless steel, with an emphasis on integrating ion and neutron irradiation data to accelerate the development and qualification of materials for advanced nuclear reactor applications. While ion irradiation is a cost- and time-effective method, modeling and simulation are required to interpret the data for the broader range of irradiation conditions encountered in advanced reactors. In fiscal year 2025, integrated multiscale modeling and simulations were conducted to assess irradiation damage in additively manufactured 316 stainless steel. Key outcomes include predictions of chromium enrichment at grain boundaries, nickel enrichment at dislocation cell walls and void surfaces, and heterogeneous void evolution under ion and neutron irradiation conditions. Cluster dynamics simulations revealed the coarsening of voids at high irradiation temperatures and the suppression of void growth by high network dislocation density, while also demonstrating significant growth and coarsening of voids and self-interstitial atom loops at low dose rates. Machine learning-accelerated atomistic simulations highlighted the impact of the local environment and chromium concentration on vacancy diffusivity, providing key insights on the influence of composition on void swelling and radiation-induced segregation. Additionally, molecular dynamics simulations demonstrated the presence of defect production bias and a significant effect of carbon content on defect cluster behavior. These combined efforts aim to predict the performance of additively manufactured materials under various reactor conditions, supporting their qualification for nuclear reactor applications by interpreting ion irradiation data. This report underscores the potential of integrated multiscale modeling to analyze ion irradiation data in the effort to accelerate the qualification of additively manufactured materials for nuclear reactor components.

316 stainless steel↗

Modeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets

This project involves developing and integrating new modeling tools to simulate the dynamics of electric medium- and heavy-duty fleet vehicle adoption. A technical and economic modeling tool, combining a data-driven hardware cost model with a cost-optimal charging strategy microsimulation, enables tailored analysis of the costs and benefits of electrifying individual fleets. Next, a novel text synthesis process, applied to a curated corpus of literature, quantifies trade-offs between technical, economic, and other factors in the fleet vehicle procurement decision. The outcomes of these tasks combine with knowledge from recent literature on fleet decision processes to specify the vehicle procurement model used by fleets in an agent-based model of the medium- and heavy-duty electric vehicle market. This model embodies an especially disaggregated approach to adoption modeling, internalizing factors and dynamics that conventional adoption models externalize. In particular, explicitly modeling the formation and diffusion of opinions among agents enables experiments that conventional models cannot support. Demonstrations show, for example, that increasing the extent of interactions between populations with different proclivities to electric vehicles has an asymmetrical outcome. High-proclivity electric vehicle adoption is generally unaffected as interactions increase, but low-proclivity adoption is accelerated. By representing individual fleets' requirements and costs at a high level of detail, incorporating an adoption decision model informed by a wide body of empirical research, and broadening the array of variables and dynamics available for experimentation, this integrated model offers a new way to understand the urgent challenge of eliminating emissions from the most emissions-intensive transportation sectors.

Trinko, David A.↗