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At least 1,747 records · Page 97

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NASA NTRS2017

A Computational Fluid Dynamics Study of Swirling Flow Reduction by Using Anti-Vortex Baffle

OBJECTIVES: To evaluate proposed anti-vortex design in suppressing swirling flow during US burn. APPROACH: Include two major body forces in the analysis a)Vehicle acceleration (all three components); b)Vehicle maneuvers (roll, pitch, and yaw). Perform two drainage analyses of Ares I LOX tank using 6 DOF body forces predicted by GN&C analysis (Guidance Navigation and Control) during vehicle ascent: one with baffle, one without baffle. MODEL: Use Ares I defined geometry. O-Grid for easy fitting of baffle. In this preliminary analysis the holes are sealed. Use whole 360 deg. model with no assumption of symmetry or cyclic boundary conditions. Read in 6DOF data vs time from a file.

Yang, H. Q.↗

NASA NTRS1999

System Identification for Integrated Aircraft Development and Flight Testing [l'Identification Des Systemes Pour le Developpement Integre des Aeronefs et les Essais en Vol]

Over the last decades flight vehicles such as aircraft and helicopters entering service and requiring increased operational effectiveness have with few exceptions experienced prolonged flight test development to achieve full certification. In many cases the original requirements had later to be reduced to enable release to service. The impact on the customer, and manufacturer has been considerable leading to increased costs and or reduced operational capabilities. These costly experiences are largely a result of the flight vehicle not behaving as modelled and designed. The evaluation of flight test data can be used as a tool for validating windtunnel results and mathematical models describing the flight dynamical behaviour. In this sense the uncertainty of important aerodynamic stability and control parameters can be reduced and the confidence of aircraft mathematical models improved. An additional important factor comes from the implementation of active control systems offering the promise of significantly increased flight vehicle performance and operational capability. This approach extends the traditional trade-offs between aerodynamics, structures and propulsion systems to include full- time, full-authority fly-by-wire/light systems. It is imperative that the aerodynamic stability and control parameters of such integrated flight and propulsion control systems have to turn out inflight as predicted, since inherent stability margins will be lower and the flight control system must correct these deficiencies to provide flight critical redundancy and safety. With the methodology of system identification from flight tests it is possible to sense the control inputs and the flight vehicle reactions Such as accelerations, rates and attitudes. The mathematical model, e.g. the model structure and parameters, has to be determined from the relationship of the measured control inputs and the system's responses. The aim of this symposium was to review the present state of the art of flight vehicle system and parameter identification techniques, and to provide a critical appraisal of current methods developed and applied to flight test data in a number of NATO nations. Particular emphasis was placed on practical aspects and lessons learned in order to generate information useful to the flight test community in industry and government agencies. The technical papers share invaluable experience and emphasize the advances of flight vehicle system identification over the last years to the point where confidence and robustness level is now reasonably high. The symposium covered overviews of identification methodologies, flight test techniques, recent aircraft and helicopter application programs, and a session of short papers covering up-to-the-minute flight test results. A final discussion included prepared comments from experts and concluded with key issues learned in the application of system identification and future research needs. The essential benefits to NATO nations can be condensed as follows: More accurate mathematical models for high bandwidth flight control systems, Improved assessment and evaluation of flying qualities, High fidelity mathematical models for flight vehicle development and mission training simulators, and generally, Reduced flight test time and costs.

Advisory Group for Aerospace Research and Developm↗

DOE OSTI2024

Large spatiotemporal variability in aerosol properties over central Argentina during the CACTI field campaign

Abstract. Few field campaigns with extensive aerosol measurements have been conducted over continental areas in the Southern Hemisphere. To address this data gap and better understand the interactions of convective clouds and the surrounding environment, extensive in situ and remote sensing measurements were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted between October 2018 and April 2019 over the Sierras de Córdoba range of central Argentina. This study describes measurements of aerosol number, size, composition, mixing state, and cloud condensation nuclei (CCN) collected on the ground and from a research aircraft during 7 weeks of the campaign. Large spatial and multiday variations in aerosol number, size, composition, and CCN were observed due to transport from upwind sources controlled by mesoscale to synoptic-scale meteorological conditions. Large vertical wind shears, back trajectories, single-particle measurements, and chemical transport model predictions indicate that different types of emissions and source regions, including biogenic emissions and biomass burning from the Amazon and anthropogenic emissions from Chile and eastern Argentina, contribute to aerosols observed during CACTI. Repeated aircraft measurements near the boundary layer top reveal strong spatial and temporal variations in CCN and demonstrate that understanding the complex co-variability of aerosol properties and clouds is critical to quantify the impact of aerosol–cloud interactions. In addition to quantifying aerosol properties in this data-sparse region, these measurements will be valuable to evaluate predictions over the midlatitudes of South America and improve parameterized aerosol processes in local, regional, and global models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2012

An Assessment of CFD/CSD Prediction State-of-the-Art by Using the HART II International Workshop Data

Over the past decade, there have been significant advancements in the accuracy of rotor aeroelastic simulations with the application of computational fluid dynamics methods coupled with computational structural dynamics codes (CFD/CSD). The HART II International Workshop database, which includes descent operating conditions with strong blade-vortex interactions (BVI), provides a unique opportunity to assess the ability of CFD/CSD to capture these physics. In addition to a baseline case with BVI, two additional cases with 3/rev higher harmonic blade root pitch control (HHC) are available for comparison. The collaboration during the workshop permits assessment of structured, unstructured, and hybrid overset CFD/CSD methods from across the globe on the dynamics, aerodynamics, and wake structure. Evaluation of the plethora of CFD/CSD methods indicate that the most important numerical variables associated with most accurately capturing BVI are a two-equation or detached eddy simulation (DES)-based turbulence model and a sufficiently small time step. An appropriate trade-off between grid fidelity and spatial accuracy schemes also appears to be pertinent for capturing BVI on the advancing rotor disk. Overall, the CFD/CSD methods generally fall within the same accuracy; cost-effective hybrid Navier-Stokes/Lagrangian wake methods provide accuracies within 50% the full CFD/CSD methods for most parameters of interest, except for those highly influenced by torsion. The importance of modeling the fuselage is observed, and other computational requirements are discussed.

Smith, Marilyn J.↗

DOE OSTI2024

A methodology to develop multi-physics dynamic fuel cell system models validated with vehicle realistic drive cycle data

Fuel cell (FC) technology has been identified as a technically attractive solution to decarbonize the transportation sector, especially for heavy-duty vehicles. In this context, the industry and the scientific community are in need of advanced fuel cell systems (FCS) models that are able to replicate real -world operating conditions. Due to the scarcity of said models in the open literature, this study aimed to develop a comprehensive methodology to calibrate and validate multi -physics dynamic FCS models. Therefore, the key contribution of this paper is the detailed description of the calibration process for each component and the calibration order. The specific focus here was to accurately describe the behavior of the FC stack as well as the cathode, anode, and cooling circuits of the balance of plant. The model was calibrated with the aid of experimental data from a Toyota Mirai FC electric vehicle, which was predominantly retrieved from the vehicle's Controller Area Network (CAN) bus system thereby negating the need for major intrusion into the powertrain system. The validation process was deemed successful with the model being able to truthfully replicate the characteristics of the FC vehicle operated on the World-wide harmonized Light duty Test Cycle (WLTC) 3b and US06 driving cycle. The time -resolved physical parameters such as the cathode pressure, mass flow, or the FC stack temperature were captured with high fidelity, while the overall performance parameters such as the H2 consumption in the stack and the system, and the compressor energy consumption were predicted accurately with a deviation lower than 0.47%, 1.75% and 1.89% with respect to the experimental data, respectively.

Lopez-Juarez, Marcos↗

DOE OSTI2020

HDG-1 Graphite Preirradiation Data Package Report

This report documents all pre-irradiation examination material-property measurement data for graphite specimens that are going to be used within the first high dose graphite (HDG) -1 irradiation capsule. The two new HDG capsules signify a major change to the AGC Experiment. HDG-1 and HDG-2 will replace the last two Advanced Graphite Creep (AGC) capsules (AGC-5 and AGC-6) which were designed to irradiate graphite at the extreme upper operational temperatures for a very-high-temperature reactor (VHTR) design, 1100°C. These very high temperature AGC-5 and AGC-6 capsules have been repurposed to re-irradiated specimens (from AGC-2, AGC-3, and AGC-4) at the lower temperatures of 600°C and 800°C. HDG-1 will be irradiated at 600°C and HDG-2 will be irradiated at 800°C. By re-irradiating the previous AGC specimens a total maximum neutron dose of around 15 dpa (displacements per atom) can be achieved for all major graphite grades at irradiation temperatures of 600°C and 800°C. Specimens in the HDG-1 capsule are made up of previously irradiated specimens from the AGC-2 capsule and unirradiated specimens prepared for the now discontinued AGC-5 capsule. Utilizing the irradiated specimens, a maximum neutron dose of around 15 dpa is anticipated. These new maximum dose levels will provide irradiated material property data over a total neutron dose range of 1-15 dpa at a temperature of 600°C when combined with the previous AGC-1 and AGC-2 irradiation data. This will provide quantitative data necessary for predicting the irradiation behavior and operating performance of new nuclear graphite grades for use within high temperature reactor designs. Similar to previous AGC test trains, HDG-1 includes the major graphite grades (IG-110, NBG-17, NBG-18, PCEA, and 2114) as well as adding the very fine-grain grade IG-430 which is of interest to the Molten Salt Reactor (MSR) designs. Also new to the HDG-1 capsule are 90 smaller geometry specimens designated as pencil specimens. These specimens take up only one third the space of a standard creep size specimen. This increased number of specimens will enhance property measurement statistics because they will provide 3 times the control specimen data at a position that would otherwise only have a single measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

HDG-1 Graphite Preirradiation Data Package Report

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Proton radiation resilience of CdSeTe photovoltaics: High predicted end-of-life performance for space applications

Two types of cadmium selenide telluride (CdSeTe) photovoltaic devices have been exposed to high-energy (150–1500 keV) protons with fluences ranging from 1 × 10 11 to 9 × 10 13 cm −2 . Pre- and post-irradiation current density vs voltage characteristic data were collected and analyzed. Arsenic-doped CdSeTe devices retained 80% of the power conversion efficiency (PCE) relative to control devices after exposure to 10 12 cm −2 650 keV protons, while copper-doped CdSeTe devices retained about 95% of the control PCE under the same irradiation condition. Displacement damage dose analysis coupled with simulations for duration-dependent performance in a medium Earth orbit space mission revealed superior PCE remaining factors, indicating greater resilience to proton bombardment than state-of-the-art multijunction III-V based space photovoltaic technologies.

CdTe solar cells↗

DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2018

A Momentum-Based Indicator for Predicting the Peak Opening Load of Supersonic Parachutes

In this paper, a new empirical indicator for predicting the peak opening loads of supersonic parachutes is presented. The proposed indicator is proportional to twice the free-stream dynamic pressure and the projected area of the parachute, which is equivalent to estimating the opening load as a percentage of the free-stream momentum flux through the projected area at the moment of peak inflation. The form of this expression is motivated by a classical control volume analysis of the aerodynamic forces acting on a parachute during inflation, under the simplifying assumptions of quasi-static and one-dimensional flow. For parachute geometries and flight conditions typical of Mars Entry, Descent, and Landing systems, the largest contribution to the total drag is shown to be a momentum flux term that is associated with the entrainment of atmosphere within the inflating parachute volume. Using this new method, empirical constants are calculated from existing flight reconstruction data and are shown to have a smaller standard deviation than similar constants determined using the customary indicator form, which is based on the steady-state subsonic drag and proportional to the parachute reference area. These empirical constants are also compared to an analytic estimate, derived from the control volume analysis, and shown to have excellent agreement across a wide range of Mach numbers and dynamic pressures for several parachute geometries. While opening loads estimated using both methods produce similar results at low supersonic Mach numbers typical of past inflations, the proposed method predicts notably larger loads at higher Mach numbers, those above Mach 2.0, due to the omission of any Mach Efficiency Factor. Several current Mars EDL projects have adopted this new indicator.

Way, David W.↗

DOE OSTI2026

Attention-based 3D – convolutional neural network model for mechanical property predictions using visible light images in metal additive manufacturing

Additive manufacturing (AM), while commonly used for rapid prototyping and creating components with complex geometries, has not been widely adopted for critical applications across the aerospace, automotive, defense, energy, and medical industries. This is, in part, due to the challenges of controlling flaws and uncertainty in the mechanical behavior of additively manufactured components. In recent years, there has been an increase in research aimed at predicting the final mechanical properties of additively manufactured components during the printing process. To address these issues, a 3D-CNN model was trained using low-cost in situ visible-light camera data, anomaly classifications, and the chosen process parameters to predict the ultimate tensile strength (UTS), yield strength (YS), total elongation (TE), and uniform elongation (UE). The 3D-CNN layers of the model employed attention mechanisms to prioritize features in the data, thereby improving prediction accuracy. Furthermore, the effect of each process parameter and anomaly class is investigated using attention-based dynamic sigmoid weighted gates to interpret the influence each class has on the final prediction. Different combinations of the in situ data were fed into the 3D-CNN, with varying amounts of image layers, to determine the ideal combination for predicting mechanical properties in situ. Here, the 3D-CNN model achieved mean absolute percentage errors (MAPE) below 5% for both UTS and YS while using only a single camera input and under half of the available image layers.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Machine Learning-based Cyber-Physical Anomaly Detection in Wide Area Voltage Control Systems

Wide-area voltage control systems (WAVCS) are widely deployed in power grid to improve the voltage stability in transmission system using Flexible AC Transmission System (FACTS) devices. The WAVCS relies on wide-area measurement and control signals for closed-loop control of FACTS devices to improve the transient voltage stability in power grid in real-time. Since the WAVCS utilizes a cyber-layer communication during its normal operation, they are susceptible to cyber attacks from adversaries which can lead to a voltage collapse if the attacks go undetected and unmitigated. This paper proposes a supervised machine learning (ML)-based anomaly detection algorithm for detecting various stealthy cyber attacks in the context of WAVCS cybersecurity. In particular, a fuzzy logic-based wide-area controller, as proposed by the Bonneville Power Administration (BPA), is implemented on the Kundur’s four machine two-area system that is integrated with a static var compensator (SVC) to improve voltage profile on sensitive buses. Later, different types of data integrity attacks, including pulse and ramp attacks, are considered on the wide-area measurement and control signals to analyze the performance of the proposed anomaly detector. Our experimental evaluation shows a promising performance with a high true-positive rate (more than 99%) and low false-negative rate (less than 1%) while exhibiting a small prediction time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Understanding Transient Combustion Phenomena in Low-NO x Gas Turbines

The goal of this work was to understand, quantify, and eventually predict combustion instability during operational transients in low-NO x gas turbine combustors. Transient operation is defined as a mode where one or more key operating parameters, including equivalence ratio, fuel composition, or fuel splitting between nozzles in a combustor, are varying in time. The timescale over which this variation occurs will be referred to as the transient timescale, the magnitude of the change in the transient parameter will be referred to as the transient amplitude, and the direction of the variation will be referred to as the transient direction. Transients occur regularly in power generation gas turbine operation. For example, load-following gas turbines vary load to meet power demands while accounting for variation in unsteady grid contributors like wind and solar power. Operators achieve this by varying equivalence ratio and fuel splitting inside the combustors to produce more or less power. Another example of transient operation is during fuel-switching operations, a particular issue for turbines operating with syngas fuels in a co-generation facility. In this case, the composition of the fuel stream may vary in time either as a result of fluctuations in the pipeline, or in the case of a co-generation plant, variations in feedstock or gasification processes. This fluctuation in fuel composition can have significant implications for combustion processes, particularly with high-hydrogen fuels. A small number of studies have investigated transient behavior in gas turbine combustors, particularly in the context of flame blow-off; here, investigators have typically focused on issues of transient amplitude, though without the depth and physics-based experimental design that is proposed in this program. To our knowledge, there have been no studies that have quantified the impact of the transient timescale on combustion. The work helped us understand the impact of several types of transients on combustion stability. Both static and dynamic combustion stability will be considered. The transients will be quantified using their amplitude, direction, and timescale, and we will consider transients in equivalence ratio, fuel composition, and fuel splitting. There were two main objectives of this work: 1. Provide a fundamental understanding of combustion stability during transient operation using data obtained from a number of high-speed diagnostic techniques on experimental configurations that capture important gas turbine combustor features and operating conditions. This goal was met in conjunction with our industrial partner, GE Global Research, with whom we worked closely throughout the program. 2. Develop a stability prediction framework that will allow for the prediction, and possible control, of instabilities as a function of the transient amplitude, direction, and timescale. This input/output model should be physics-based and allow for screening of operating conditions and prediction of unstable behavior at the end of a transient by monitoring combustor health and precursor signals during operation.

03 NATURAL GAS↗

DOE OSTI2022

Verification of a Reduced-Order Extension Spring Model

Adopting reduced order models (ROMs) of springs lowers the computational cost of stronglink simulations. However, ROMs introduce currently unquantified error to such analyses. This study addresses that lack of data by comparing a hexahedral mesh to a commonly used ROM beam mesh. Two types of analyses were performed, a quasi-static displacement-controlled pull and a haversine shock, examining basic spring properties as well as dynamics and stress/strain data. Both tests showed good similarities between the hexahedral and beam meshes, especially when comparing reaction force and stress trends and maximums. Equivalent plastic strain results were not quite as favorable, indicating that the beam model may be less likely to correctly predict spring failure. Despite reducing computation times by over 48 hours in all shock cases, appropriate use of the ROM should carefully balance this advantage with its reduction in accuracy, especially when examining spring failure and outputting variables such as equivalent plastic strain.

42 ENGINEERING↗

NASA NTRS1973

Comparisons of Predictions of the XB-70-1 Longitudinal Stability and Control Derivatives with Flight Results for Six Flight Conditions

Preliminary correlations of flight-determined and predicted stability and control characteristics of the XB-70-1 reported in NASA TN D-4578 were subject to uncertainties in several areas which necessitated a review of prediction techniques particularly for the longitudinal characteristics. Reevaluation and updating of the original predictions, including aeroelastic corrections, for six specific flight-test conditions resulted in improved correlations of static pitch stability with flight data. The original predictions for the pitch-damping derivative, on the other hand, showed better correlation with flight data than the updated predictions. It appears that additional study is required in the application of aeroelastic corrections to rigid model wind-tunnel data and the theoretical determination of dynamic derivatives for this class of aircraft.

Wolowicz, C. H.↗

NASA NTRS1974

Evaporation in space manufacturing

'Normal evaporation' equations for predicting the compositional changes with time and temperature have been developed and correlated with actual experimental data. An evaporative congruent temperature is defined and used to explain, predict, or plan space experiments on anomalous constitutional melting (on cooling) or solidification (on heating). Uneven evaporation causes reactive jetting forces capable of initiating new convection currents, nongravitational accelerations, surface vibrations, or other disturbances. Applications of evaporation to space manufacturing are described concerning evaporative purification, surface cooling, specimen selection, particles splitting, freezing data interpretation, material loss and dimensional control, and surface contamination or compositional changes.

Li, C. H.↗

NASA NTRS1975

Biological indicators for monitoring water quality of MTF canals system

Biological models, diversity indexes, were developed to predict environmental effects of NASA's Mississippi test facility (MTF) chemical operations on canal systems in the area. To predict the effects on local streams, a physical model of unpolluted streams was established. The model is fed by artesian well water free of background levels of pollutants. The species diversity and biota composition of unpolluted MTF stream was determined; resulting information will be used to form baseline data for future comparisons. Biological modeling was accomplished by adding controlled quantities or kinds of chemical pollutants and evaluating the effects of these chemicals on the biological life of the stream.

Sethi, S. L.↗

NASA NTRS1976

In situ measurements of neon in the thermosphere

The open source neutral mass spectrometer on the Atmosphere Explorer-C satellite has measured neon in the thermosphere. The absolute density of Ne is close to that predicted by using the ground level fraction by volume of Ne along with the assumption of diffusive equilibrium above 100 km. Data is presented for both geomagnetically quiet and disturbed circular orbits. At 290 km, a typical low latitude value of Ne is 3.0 x 10 to the 4th/cu cm. At this altitude Ne appears to be predominantly controlled by temperature except during magnetic disturbances, when offsetting forces due to wind systems may be present.

Potter, W. E.↗