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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Benchmark Exercise for the Control Rod Swelling Evaluation

The VTR core has six reactivity control assemblies and three safety assemblies. The control assemblies or primary control rods are adjusted during the normal operation to balance the core reactivity and to control the reactor power. A typical control assembly radial layout is presented in Figure 1. The figure shows the swelled absorber (B 4 C) rod. Initially, helium gas fills the gap between the pin and the cladding before irradiation swelling takes place. For VTR, HT9 steel was selected as the cladding and duct material. The main neutron absorbing material used in the VTR is B 4 C. When residing in the core, the neutronics, thermophysical, and mechanical properties of the materials used in a control assembly will degrade due to accumulated neutron damage. Material degradation limits how long a control assembly can reside in the core. Many phenomena affect the control assembly lifetime, such as the loss of reactivity worth due to B 4 C depletion, the mechanical interaction of the absorber rod and the cladding due to B 4 C swelling, the helium gas buildup in the pin due to B-10 capture, etc. B 4 C swelling, which causes closure of the gap between the absorber rod and the cladding, is usually considered as the main limiting factor from past experience. An initial study was conducted at PNNL to evaluate the irradiation behavior of a VTR control assembly. The evaluation was performed using the CNRD2 code that was initially developed for the FFTF. The study also included an assessment of the VTR control assembly and focused on a 61-pin control assembly design, which is different from that used (37-pin design) in the core design study. The study conducted by PNNL was reviewed independently by ANL. A Python script referred to as the Control Assembly Evaluation Script (CAES) was developed for the independent review and additional assessment of 37-pin control assembly design. The script has focused on the assessment of the absorber rod swelling for its importance in determining the control assembly lifetime. CAES uses geometry, neutronics, materials data as input to predict the swelling of the absorber rod during its residence in the reactor core. The results from CAES showed some non-negligible differences against the PNNL results. Some of the differences can be attributed to the different interpretation of the control rod assembly dimensions. To resolve this issue, a benchmark exercise was proposed. The benchmark specification was developed by PNNL. The benchmark exercise was performed independently at PNNL and ANL using different codes/scripts (CRND2 and CAES). This memo documents the results calculated using the different codes. However, this report is limited to presenting the results obtained. Further investigation of the cause of the observed difference will be performed as part of future activities, pending continuation of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2004

Oh! I Slipped the Surly Bounds of Earth....and Ran into Space Weather!

Over the past decade the concept of space weather has been introduced and matured in both the scientific community and popular press. Likewise the concept of space climatology recently also is being advanced. Closely linked to these concepts are their impacts on ground- and space-based technological systems; one such system commonly mentioned is manned space flight exemplified by the Space Shuttle and International Space Station (ISS). From a manned space flight perspective, space weather and space climatology have significant effects on the amount of radiation exposure received by humans in space from the ambient high-energy charged particles present in interplanetary space and trapped in the geomagnetosphere. Whereas the impact of space weather for most technological systems is usually discrete and well correlated in time, the principle impact of space weather and space climatology is to increase the probability of latent cancer formation in thetraveler cohort. In this regard, while space weather may be the dominating factor for a given mission, over the life of a long-term program such as the Space Shuttle or ISS space climatology is the controlling factor of latent cancer risk. Human radiation exposure enhancements associated with space weather disturbances has been a concern among scientist and mission controllers since the inception of manned spaceflight nearly forty years ago. This led NASA to develop, in conjunction with the Environmental Science Services Administration s Space Disturbance Forecast Center and the USAF/AWS, the Solar Particle Alert Network (SPAN)-the foundation of an initial U.S. space weather monitoring and forecasting service. Since Apollo, routine space flight operations have evolved to include the use of space weather and climatology data provided through a world-wide network of operational space weather data services to predict and recommend actions to minimize astronaut radiation exposures. NASA Space Radiation Analysis Group (SRAG) flight controllers use real-time space weather data to detect and assess the impact of solar particle events, outer electron belt enhancements, the formation of pseudo-stable additional trapped radiation belts, and the solar cycle modulation of trapped radiation belts and galactic cosmic rays. Energetic particle data from GOES spacecraft are automatically ingested from NOAA Space Environment Center data servers and used to drive a model for the estimating the exposure to astronauts from solar particle events. While adequate for current manned space flight support, the existing operational space weather support system requires improvements to address the anticipated evolution in both the character of manned missions as well as space flight operations management. Necessary space weather data improvements include: reliably available (near) real-time space weather data on a fixed schedule via redundant access methods that support autonomous data acquisition by computer systems behind enterprise firewalls; and rapid transition of promising research sensors into operational systems.

Golightly, Michael J.↗
NASA NTRS2006

Flight Test Determined Aerodynamics Force and Moment Characteristics of the X-43A Research Vehicle at Mach 7.0

The second flight of the HYPER-X Program afforded a unique opportunity to determine the aerodynamic force and moment characteristics of an airframe integrated scramjet powered aircraft in hypersonic flight. These data were gathered via a repeated series of pitch, yaw, and roll doublets, frequency sweeps, and pull-up/push-over maneuvers performed throughout the X-43A cowl-closed descent phase. The subject flight research maneuvers were conducted in a Mach number range of 6.8 to 0.95 at altitudes from 92,000 ft to sea level. In this flight regime, the dynamic pressure varied from 1300 psf to 400 psf with angle-of-attack ranging from 0 deg to 14 deg. The flight-extracted aerodynamics were compared with pre-flight predictions based on wind tunnel test data. The X-43A flight-derived axial force was found to be 10 to 15 percent higher than prediction. Under-predictions of similar magnitude were observed for the normal force. For Mach numbers greater than 4, the X-43A flight-derived stability and control characteristics resulted in larger than predicted static margins, with the largest discrepancy approximately 5-inches forward along the X(CG) at Mach 6. This would result in less static margin in pitch. The X-43A predicted lateral-directional stability and control characteristics matched well with flight data when allowance was made for the high uncertainty in angle-of-sideslip.

Davis, Mark C.↗
DOE OSTI2022

A Comparison of Preconstruction and Operational Wake Loss Estimates for Land-Based Wind Plants

Recent studies suggest that biases between wind plant pre-construction energy yield estimates and actual energy production are decreasing over time. However, variability in energy yield prediction accuracy across different projects and wind energy consultants remains high. Wake effects are one of the largest categories comprising the pre-construction energy yield assessment process. To assess the accuracy of wake loss predictions, we compare pre-construction wake loss estimates provided by 8 consultants to the estimated operational wake losses for 10 North American wind plants, as part of the Wind Plant Performance Prediction (WP3) Benchmark project. We estimate operational wake losses using supervisory control and data acquisition (SCADA) data by comparing total wind plant energy production to the potential energy production based on the power produced by freestream wind turbines. In the presentation, we will discuss the overall wake loss prediction bias as well as the project-to-project variability in the prediction accuracy. Further, we will highlight challenges encountered when estimating operational wake losses, including the impact of complex terrain and the presence of neighboring wind plants.

benchmark↗
DOE OSTI2025

Benchmark microgravity experiments and computations for 3D dendritic-array stability in directional solidification

In this study, we present a comprehensive quantitative analysis of stability bands for dendritic arrays during directional solidification of a transparent succinonitrile-0.46 wt % camphor alloy, spanning a broad range of pulling velocities. Taking advantage of the microgravity environment aboard the International Space Station where most convection effects are suppressed, we obtain unique measurements that quantify the stable primary spacing range of spatially extended three-dimensional dendritic array structures under purely diffusive growth conditions. Through carefully designed velocity jump experiments and detailed examination of sub-grain boundary dynamics, we characterize key instabilities, including elimination and tertiary branching, shedding new light on the mechanisms governing dynamic dendritic spacing selection in extended 3D arrays. Phase field simulations are performed to characterize the stability limits of dendritic array structures for quantitative comparison with the flight experiments. Although the simulations capture general trends, significant deviations are noted at the upper stability boundary, indicating the influence of additional, unexplored factors. These findings contribute to a deeper understanding of dendritic growth dynamics and offer valuable benchmark data that could aid in refining predictive models and improving control of dendritic microstructures in metallurgical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Machine learning models of intermittent operation of RO wellhead water treatment for salinity reduction and nitrate removal

Machine learning models were developed for intermittent multi-mode operation of a wellhead reverse osmosis water purification and desalination system to predict salt passage, nitrate passage, and permeate flux. The models, based on long short-term memory (LSTM) recurrent neural network (RNN) architecture, included an attention mechanism to increase model performance in proximity of the regulatory limit for nitrate. Training and testing of the models for the Startup, Production, Shutdown and Flushing operational modes were based on operational data (consisting of 22 process variables per data sample) acquired every 2–5 s over a six-month period. The significant sets of model input attributes for the different operational modes were assessed via Spearman ranking correlation, Self-Organizing Map (SOM) analysis and feed forward feature selection (FFFS). Although the variability of nitrate passage, salt passage and permeate flux was significant over the four operational modes, prediction performance for the three outcomes were with R2 and Average Absolute Relative Error (AARE) of 0.78–0.95 and 2.96–6.16 %, respectively. Model updates post membrane elements replacement demonstrated similar levels of prediction accuracy. The study results suggest that there is merit in exploring the utility of multi-mode models for sensor fault detection, data imputation, and for potential use in model-predictive control.

Intermittent RO operation↗
DOE OSTI2022

Material Resilience in Harsh Service Conditions

Resilience describes the attributes of a material that allow it to withstand or resist detrimental environmental effects degrading properties and performance. In service, materials may experience harsh or extreme conditions, but even modest thermal or load conditions experienced over a long period can degrade performance. Thus, the National Nuclear Security Administration mission requires predictive understanding of materials performance in harsh and extreme conditions over long periods. This performance is particularly relevant for applications in which replacement is impractical, impossible, or costly. This area of leadership addresses the evolution of material properties in environments that include static and dynamic stress, radiation, and chemical or thermal extremes. A particular focus is on situations when environments coexist or for which collection of experimental data is challenging or impossible. The capability to predict and control the nature and evolution of properties to allow designing resilience is a crucial aspect of mission success in national nuclear, global, and energy security.

36 MATERIALS SCIENCE↗
NASA NTRS1976

A new experimental flight research technique: The remotely piloted airplane

The results obtained so far with a remotely piloted research vehicle (RPRV) using a 3/8 scale model of an F-15 airplane, to determine the usefulness of the RPRV testing technique in high risk flight testing, including spin testing, were presented. The program showed that the RPRV technique, including the use of a digital control system, is a practical method for obtaining flight research data. The spin, stability, and control data obtained with the 3/8-scale model also showed that predictions based on wind-tunnel tests were generally reasonable.

Layton, G. P.↗
NASA NTRS1983

DC-10 winglet flight evaluation

Results of a flight evaluation of winglets on a DC-10 Series 10 aircraft are presented. For sensitive areas of comparison, effects of winglets were determined back-to-back with and without winglets. Basic and reduced-span winglet configurations were tested. After initial encounter with low-speed buffet, a number of acceptable configurations were developed. For maximum drag reduction at both cruise and low speeds, lower winglets were required, having leading edge devices on upper and lower winglets for the latter regime. The cruise benefits were enhanced by adding outboard aileron droop to the reduced-span winglet aircraft. Winglets had no significant impact on stall speeds, high-speed buffet boundary, and stability and control. Flutter test results agreed with predictions and ground vibration data. Flight loads measurement, provided in a concurrent program, also agreed with predictions. It was estimated that a production version of the aircraft, using the reduced-span winglet and aileron droop, would yield a 3-percent reduction in fuel burned with capacity payload. This range was 2% greater than with winglets. A 5% reduction in takeoff distance at maximum takeoff weight would also result.

Taylor, A. B.↗
NASA NTRS1998

X-34 Experimental Aeroheating at Mach 6 and 10

Critical technologies are being developed to support the goals of the NASA Office of Aeronautics and Space Transportation Technology Access to Space initiative for next-generation reusable space transportation systems. From the perspective of aerothermodynamic performance throughout the flight trajectory, the Reusable Launch Vehicle program incorporates conceptual analysis, ground-based testing, and computational fluid dynamics to provide flyable suborbital flight demonstrator vehicles. This report provides an overview of the hypersonic aeroheating wind tunnel test program conducted at the NASA Langley Research Center in support of one of these vehicles, the X-34 small reusable technology demonstrator program. Global surface heat transfer images, surface streamline patterns, and shock shapes were measured on 0.0153- and 0.0183-scale models of proposed X-34 flight vehicles at Mach 6 and 10 in air. The primary parametrics that were investigated include angles-of-attack from 0 to 35 deg. and freestream unit Reynolds numbers from 0.5 to 8 million per foot (which was sufficient to produce laminar, transitional, and turbulent heating data), both with and without control surface deflections. Comparisons of the experimental data to computational predictions are included, along with a discussion of the implications of some of the experimental flow features for the flight vehicle.

Berry, Scott A.↗
NASA NTRS2018

ST7 Disturbance Reduction System (DRS) Colloid Micronewton Thruster Performance and Control Algorithm Model Simulation Validation in Flight

Colloid Micronewton Thrusters (CMNT) were flight demonstrated for the first time on the ST7Disturbance Reduction System (DRS) payload on the European Space Agency (ESA) Laser Interferometer Space Antenna (LISA) Pathfinder spacecraft for attitude and drag-free spacecraft control. LISA Pathfinder was a technology demonstration mission for ESA’s LISA gravitational wave observatory, currently in Phase A with a launch date of 2034. The DRS included the Integrated Avionics Unit (IAU), eight Colloid Micronewton Thrusters (CMNT), Dynamic Control Software (DCS) and Flight Software (FSW). The CMNT technology met performance requirements operating at 5-30 µN of thrust with ≤0.1 µN resolution and ≤0.1 µN/Hz thrust noise to deliver the required nanometer-level precision spacecraft control measured by the gravitational reference sensor (GRS) in the ESA LISA Technology Package (LTP). The performance of seven of the CMNT in flight was consistent with ground test results. The colloid thruster performance model of thrust and thrust noise as a function of operational parameters (i.e. beam current, voltage, temperature, etc.) was validated in flight over a wide range of conditions. A model and simulation of the thruster control algorithm was developed and validated with flight data to predict thrust noise. This capability is important because it is considered to be a significant source of position noise on the spacecraft and, therefore, the acceleration noise on the test masses, which provide the gravity wave measurements. The CMNT thruster model data and validation with LISA Pathfinder/ST7-DRS flight experiments are discussed in this paper.

Hruby, Vlad↗
NASA NTRS2018

In-Flight Verification and Validation of Colloid Microthruster Performance

Colloid Micronewton Thrusters (CMNTs) use an electrospray to provide precision spacecraft position and pointing control. They were demonstrated in space for the first time as part of NASA’s Space Technology 7 (ST7) payload hosted by the European Space Agency’s (ESA’s) LISA Pathfinder (LPF) technology demonstration mission in January, 2016. CMNTs were the actuator in the disturbance reduction system (DRS) that provided drag-free operation of the LPF spacecraft, which will be necessary for future gravity wave observatories such as ESA’s Laser Interferometer Space Antenna (LISA) mission, currently in Phase A and scheduled for launch in 2034. The CMNT technology met performance requirements operating at 5-30 µN of thrust with 0.1 µN resolution and ≤0.1 µN/ÖHz thrust noise to deliver the required nanometer-level precision spacecraft control measured by the gravitational reference sensor (GRS) in the ESA LISA Technology Package (LTP). The performance of seven of the eight CMNTs in flight was consistent with ground test results, and as a system, all eight thrusters met mission-level performance requirements. The colloid microthruster performance model of thrust and thrust noise as a function of operational parameters (i.e. beam current, voltage, temperature, etc.) was validated in flight over a wide range of conditions. A model and simulation of the thruster control algorithm was developed and validated with flight data to predict thrust noise. This capability is important for future missions because it relates directly to the acceleration noise on the test masses, which provide the gravity wave measurements. The CMNT thruster model data and validation with LISA Pathfinder/ST7-DRS flight experiments are presented in this paper.

"O'Donnell, James"↗
NASA NTRS1995

Experimental Aerodynamic Characteristics of the Pegasus Air-Launched Booster and Comparisons with Predicted and Flight Results

Experimental longitudinal and lateral-directional aerodynamic characteristics were obtained for the Pegasus and Pegasus XL configurations over a Mach number range from 1.6 to 6 and angles of attack from -4 to +24 degrees. Angle of sideslip was varied from -6 to +6 degrees, and control surfaces were deflected to obtain elevon, aileron, and rudder effectiveness. Experimental data for the Pegasus configuration are compared with engineering code predictions performed by Nielsen Engineering & Research, Inc. (NEAR) in the aerodynamic design of the Pegasus vehicle, and with results from the Aerodynamic Preliminary Analysis System (APAS) code. Comparisons of experimental results are also made with longitudinal flight data from Flight #2 of the Pegasus vehicle. Results show that the longitudinal aerodynamic characteristics of the Pegasus and Pegasus XL configurations are similar, having the same lift-curve slope and drag levels across the Mach number range. Both configurations are longitudinally stable, with stability decreasing towards neutral levels as Mach number increases. Directional stability is negative at moderate to high angles of attack due to separated flow over the vertical tail. Dihedral effect is positive for both configurations, but is reduced 30-50 percent for the Pegasus XL configuration because of the horizontal tail anhedral. Predicted longitudinal characteristics and both longitudinal and lateral-directional control effectiveness are generally in good agreement with experiment. Due to the complex leeside flowfield, lateral-directional characteristics are not as well predicted by the engineering codes. Experiment and flight data are in good agreement across the Mach number range.

Rhode, M. N.↗
DOE OSTI2022

Software Architecture and Hardware Organization in Mu2e Solenoid Field Mapping System

Herein, the Mu2e field mapping system is designed to produce high accuracy field maps of the detector solenoid used in the experiment. The data acquisition system is mobile and uses a self-propelled mapper with rotating arms equipped with 3D Hall probes. The measurements require not only accurate magnetic field readouts, but also accurate locations of all Hall probes while measuring data. The latter is accomplished by using the laser tracker to measure positions of several retroreflectors on the field mapper during data acquisition. The measurement process requires scanning the whole space inside the large solenoid and takes many hours to complete, which necessitates its full automation. The automation software includes control of the mapper, readout of Hall and NMR probes and control of a laser tracker, including prediction of retroreflector positions and execution of quality control checks. The software architecture and data acquisition hardware of the field mapping system are described, with special attention given to control of the laser tracker and its integration with the rest of the system.

3d hall probes↗
DOE OSTI2022

Porewater Geochemical Assessment of Seismic Indications for Gas Hydrate Presence and Absence: Mahia Slope, East of New Zealand’s North Island

We compare sediment vertical methane flux off the Mahia Peninsula, on the Hikurangi Margin, east of New Zealand’s North Island, with a combination of geochemical, multichannel seismic and sub-bottom profiler data. Stable carbon isotope data provided an overview of methane contributions to shallow sediment carbon pools. Methane varied considerably in concentration and vertical flux across stations in close proximities. At two Mahia transects, methane profiles correlated well with integrated seismic and TOPAS data for predicting vertical methane migration rates from deep to shallow sediment. However, at our “control site”, where no seismic blanking or indications of vertical gas migration were observed, geochemical data were similar to the two Mahia transect lines. This apparent mismatch between seismic and geochemistry data suggests a potential to underestimate gas hydrate volumes based on standard seismic data interpretations. To accurately assess global gas hydrate deposits, multiple approaches for initial assessment, e.g., seismic data interpretation, heatflow profiling and controlled-source electromagnetics, should be compared to geochemical sediment and porewater profiles. A more thorough data matrix will provide better accuracy in gas hydrate volume for modeling climate change and potential available energy content.

03 NATURAL GAS↗
DOE OSTI2023

Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *

Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1981

On the internal target model in a tracking task

An optimal control model for predicting operator's dynamic responses and errors in target tracking ability is summarized. The model, which predicts asymmetry in the tracking data, is dependent on target maneuvers and trajectories. Gunners perception, decision making, control, and estimate of target positions and velocity related to crossover intervals are discussed. The model provides estimates for means, standard deviations, and variances for variables investigated and for operator estimates of future target positions and velocities.

Caglayan, A. K.↗
DOE OSTI2020

Prediction of histone post-translational modifications using deep learning

Abstract Motivation Histone post-translational modifications (PTMs) are involved in a variety of essential regulatory processes in the cell, including transcription control. Recent studies have shown that histone PTMs can be accurately predicted from the knowledge of transcription factor binding or DNase hypersensitivity data. Similarly, it has been shown that one can predict PTMs from the underlying DNA primary sequence. Results In this study, we introduce a deep learning architecture called DeepPTM for predicting histone PTMs from transcription factor binding data and the primary DNA sequence. Extensive experimental results show that our deep learning model outperforms the prediction accuracy of the model proposed in Benveniste et al. (PNAS 2014) and DeepHistone (BMC Genomics 2019). The competitive advantage of our framework lies in the synergistic use of deep learning combined with an effective pre-processing step. Our classification framework has also enabled the discovery that the knowledge of a small subset of transcription factors (which are histone-PTM and cell-type-specific) can provide almost the same prediction accuracy that can be obtained using all the transcription factors data. Availabilityand implementation https://github.com/dDipankar/DeepPTM. Supplementary information Supplementary data are available at Bioinformatics online.

Baisya, Dipankar Ranjan (ORCID:0000000267847359)↗