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NASA NTRS2005

Designing Agent Utilities for Coordinated, Scalable and Robust Multi-Agent Systems

Coordinating the behavior of a large number of agents to achieve a system level goal poses unique design challenges. In particular, problems of scaling (number of agents in the thousands to tens of thousands), observability (agents have limited sensing capabilities), and robustness (the agents are unreliable) make it impossible to simply apply methods developed for small multi-agent systems composed of reliable agents. To address these problems, we present an approach based on deriving agent goals that are aligned with the overall system goal, and can be computed using information readily available to the agents. Then, each agent uses a simple reinforcement learning algorithm to pursue its own goals. Because of the way in which those goals are derived, there is no need to use difficult to scale external mechanisms to force collaboration or coordination among the agents, or to ensure that agents actively attempt to appropriate the tasks of agents that suffered failures. To present these results in a concrete setting, we focus on the problem of finding the sub-set of a set of imperfect devices that results in the best aggregate device. This is a large distributed agent coordination problem where each agent (e.g., device) needs to determine whether to be part of the aggregate device. Our results show that the approach proposed in this work provides improvements of over an order of magnitude over both traditional search methods and traditional multi-agent methods. Furthermore, the results show that even in extreme cases of agent failures (i.e., half the agents failed midway through the simulation) the system's performance degrades gracefully and still outperforms a failure-free and centralized search algorithm. The results also show that the gains increase as the size of the system (e.g., number of agents) increases. This latter result is particularly encouraging and suggests that this method is ideally suited for domains where the number of agents is currently in the thousands and will reach tens or hundreds of thousands in the near future.

Tumer, Kagan↗

NASA NTRS2009

An LED Approach for Measuring the Photocatalytic Breakdown of Crystal Violet Dye

A simple technique to assess the reactivity of photocatalytic coatings sprayed onto transmissive glass surfaces was developed. This new method uses ultraviolet (UV) gallium nitride (GaN) light-emitting diodes (LEDs) to drive a photocatalytic reaction (the photocatalytic breakdown of a UV-resistant dye applied to a surface coated with the semiconductor titanium dioxide); and then a combination of a stabilized white light LED and a spectrometer to track the dye degradation as a function of time. Simple, standardized evaluation techniques that assess photocatalytic materials over a variety of environmental conditions, including illumination level, are not generally available and are greatly needed prior to in situ application of photocatalytic technologies. To date, much research pertaining to this aspect of photocatalysis has been limited and has focused primarily on laboratory experiments using mercury lamps. Mercury lamp illumination levels are difficult to control over large ranges and are temporally modulated by line power, limiting their use in helping to understand and predict how photocatalytic materials will behave in natural environmental settings and conditions. The methodology described here, using steady-state LEDs and time series spectroradiometric techniques, is a novel approach to explore the effect of UV light on the photocatalytic degradation of a UV resistant dye (crystal violet). GaN UV LED arrays, centered around 365 nm with an adjustable DC power supply, are used to create a small, spatially uniform light field where the steady state light level can be varied over three to four orders of magnitude. For this study, a set of glass microscope slides was custom coated with a thinly sprayed layer of photocatalytic titanium dioxide. Crystal violet was then applied to these titanium-dioxide coated slides and to uncoated control slides. The slides were then illuminated at various light levels from the dye side of the slide by the UV LED array. To monitor dye degradation on the slides over time, a temperature-stabilized white light LED was used to illuminate the opposite side of the slides. As the dye degraded, the amount of light from the white light LED transmitted through the slide was monitored with a spectrometer and subsequently analyzed to determine and compare the rate of dye degradation for photocatalytically coated versus uncoated slide surfaces. The long-term stability of the spectrometer/white light LED combination, which required only a single reference spectra to be taken for a time series sequence of several hours, enabled accurate measurements of transmitted light over time. Time series transmission curves were generated and results demonstrated that over time the transmission increased much more rapidly on the coated slides than on the control slides. This experimental configuration and methodology for photocatalytic activity measurement minimizes many external variable effects and allows low light level studies to be performed. This study also compares the advantages of this novel LED light source design to traditional mercury lamp systems and non-LED lamp approaches that have conventionally been used. The methodology and experimental design research summarized in this abstract is partly funded by the Department of Homeland Security, Science and Technology Directorate, and by the NASA Stennis Space Center Innovative Partnerships Program.

Ryan, Robert E.↗

NASA NTRS2012

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/ deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗

NASA NTRS2012

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗

NASA NTRS1995

Equivalent plate modeling for conceptual design of aircraft wing structures

This paper describes an analysis method that generates conceptual-level design data for aircraft wing structures. A key requirement is that this data must be produced in a timely manner so that is can be used effectively by multidisciplinary synthesis codes for performing systems studies. Such a capability is being developed by enhancing an equivalent plate structural analysis computer code to provide a more comprehensive, robust and user-friendly analysis tool. The paper focuses on recent enhancements to the Equivalent Laminated Plate Solution (ELAPS) analysis code that significantly expands the modeling capability and improves the accuracy of results. Modeling additions include use of out-of-plane plate segments for representing winglets and advanced wing concepts such as C-wings along with a new capability for modeling the internal rib and spar structure. The accuracy of calculated results is improved by including transverse shear effects in the formulation and by using multiple sets of assumed displacement functions in the analysis. Typical results are presented to demonstrate these new features. Example configurations include a C-wing transport aircraft, a representative fighter wing and a blended-wing-body transport. These applications are intended to demonstrate and quantify the benefits of using equivalent plate modeling of wing structures during conceptual design.

Giles, Gary L.↗

NASA NTRS2003

Carbon Nanotubes as Resonators for RF Spectrum Analyzers

Electromechanical resonators of a proposed type would comprise single carbon nanotubes suspended between electrodes (see Figure 1). Depending on the nanotube length, diameter, and tension, these devices will resonate at frequencies in a range from megahertz through gigahertz. Like the carbon-nanotube resonators described in the preceding article, these devices will exhibit high quality factors (Q values), will be compatible with integration with electronic circuits, and, unlike similar devices made from silicone and silicone carbide, will have tunable resonant frequencies as high as several GHz. An efficient electromechanical transduction method for the carbon nanotube resonators is provided by the previously observed variation of carbon nanotube length with charge injection. It was found that injection of electrons or holes, respectively, lengthens or shortens carbon nanotubes, by amounts of the order of a percent at bias levels of a few volts. The charge-dependent length change also enables a simple and direct means of tuning the resonant frequency by varying the DC bias and hence the tension along the tube, much like tuning a guitar string. In its basic form, the invention is a tunable high-Q resonator based on a suspended carbon nanotube bridge with attached electrodes (see Figure 1). An applied DC bias controls the tension and thus the frequency of resonance. If one were to superimpose a radio-frequency (RF) bias on the DC bias, then the resulting rapid variation in tension or length would set the tube into vibration. If, on the other hand, the carbon nanotube were to be set into vibration by interaction between an incident RF electric field and electric charges in the nanotube, then the vibration would give rise to an RF signal output that is proportional to the RF amplitude at the resonance frequency. Because the transduction mechanism is extremely sensitive and the active volume is only a few nanometers in diameter, this device is not well suited for use as a microwave power device. Instead, this carbon nanotube mechanical resonator would be useful primarily as part of a highly precise, sensitive, frequency-selective detector. An array of such devices featuring nanotubes of different lengths (and thus different frequencies) could be made to operate as a highspeed spectrum analyzer (see Figure 2)

Hunt, Brian↗

NASA NTRS2011

Towards a State Based Control Architecture for Large Telescopes: Laying a Foundation at the VLT

Large telescopes are characterized by a high level of distribution of control-related tasks and will feature diverse data flow patterns and large ranges of sampling frequencies; there will often be no single, fixed server-client relationship between the control tasks. the architecture is also challenged by the task of integrating heterogeneous subsystems which will be delivered by multiple different contractors. Due to the high number of distributed components, the control system needs to effectively detect errors and faults, impede their propagation, and accurately mitigate them in the shortest time possible, enabling the service to be restored. The presented Data-Driven Architecture is based on a decentralized approach with an end-to-end integration of disparate, independently developed software components. These components employ a high-performance standards-based communication middle-ware infrastructure, based on the Data Distribution Service. A set of rules and principles, based on JPL's State Analysis method and architecture, are use to constrain component-to component interactions, where the Control System and System Under Control are clearly separated. State Analysis provide a model-based process for capturing system and software requirements and design, greatly reducing the gap between the requirements on software specified by systems engineers and the implementation by software engineers. The method and architecture has been field tested at the Very Large Telescope, where it has been integrated into an operational system.

European Extremely Large Telescope (E-ELT)↗

NASA NTRSDate not supplied

Preliminary Results Using Galvanic Vestibular Reduction as a Non-Pharmaceutical Tool for Motion Sickness Mitigation

Introduction: Alterations in vestibular sensory processing following G-transitions lead to motion sickness and spatial disorientation upon return to Earth’s gravity. The use of non-pharmaceutical mitigation for motion sickness has several potential advantages over drug treatment options. The purpose of this study was to validate a non-pharmaceutical tool using galvanic vestibular reduction (GVR) to mitigate G-transitional induced motion sickness and spatial disorientation. Methods: Using a repeated measures counter-balanced design, motion sickness and perception are obtained during Coriolis cross-coupling stimuli on a rotating chair across three GVR treatment interventions: throughout stimulus testing (prevention), following symptom onset (rescue), and placebo control. Subjects perform up to 10 sets of pitch head movements during constant rotation. For each set, head movement is cued every 10 seconds, alternating between pitch forward (chin resting to chest) and pitch backward (head upright) for a total of 7 forward and backward movements. During each head movement, subjects are asked to use a joystick to record the magnitude of their perceived rotation along all three axes. During the 2-minute pause between sets, motion sickness symptom scoring was obtained using the Pensacola Diagnostic Index and subject discomfort (0-20) ratings. Performance on a sensorimotor and cognitive test battery is measured during a fourth session to map changes in GVR level with functional performance. Results: Fifteen of 30 subjects have completed testing to date. Preliminary findings suggest GVR may be more effective in reducing symptoms in subjects who self-report less susceptibility on a pre-test motion sickness susceptibility questionnaire. Based on the joystick measures, GVR significantly reduces both the magnitude (mean 22% - 34%) and duration (mean 42% - 49%) of perceived roll and pitch sensation with head movements during constant rotation. It is important to note that comparable levels of GVR (up to 2.5mA) does not impair performance on a functional test battery including mobility and balance tasks. Discussion: Our preliminary findings suggest GVR may be useful in reducing disorienting roll and pitch illusions associated with Coriolis cross-coupling stimuli. While transfer to post-flight treatment will need to be validated, the potential advantages of our non-pharmaceutical countermeasure approach would be to provide rapid therapeutic effect while allowing continuous titration of GVR amplitude during recovery to maintain operational performance.

Gaurav Pradhan↗

NASA NTRS1994

New Developments in the Method of Space-Time Conservation Element and Solution Element-Applications to Two-Dimensional Time-Marching Problems

A new numerical discretization method for solving conservation laws is being developed. This new approach differs substantially in both concept and methodology from the well-established methods, i.e., finite difference, finite volume, finite element, and spectral methods. It is motivated by several important physical/numerical considerations and designed to avoid several key limitations of the above traditional methods. As a result of the above considerations, a set of key principles for the design of numerical schemes was put forth in a previous report. These principles were used to construct several numerical schemes that model a 1-D time-dependent convection-diffusion equation. These schemes were then extended to solve the time-dependent Euler and Navier-Stokes equations of a perfect gas. It was shown that the above schemes compared favorably with the traditional schemes in simplicity, generality, and accuracy. In this report, the 2-D versions of the above schemes, except the Navier-Stokes solver, are constructed using the same set of design principles. Their constructions are simplified greatly by the use of a nontraditional space-time mesh. Its use results in the simplest stencil possible, i.e., a tetrahedron in a 3-D space-time with a vertex at the upper time level and other three at the lower time level. Because of the similarity in their design, each of the present 2-D solvers virtually shares with its 1-D counterpart the same fundamental characteristics. Moreover, it is shown that the present Euler solver is capable of generating highly accurate solutions for a famous 2-D shock reflection problem. Specifically, both the incident and the reflected shocks can be resolved by a single data point without the presence of numerical oscillations near the discontinuity.

Chang, Sin-Chung↗

NASA NTRS2001

Cockpit Adaptive Automation and Pilot Performance

The introduction of high-level automated systems in the aircraft cockpit has provided several benefits, e.g., new capabilities, enhanced operational efficiency, and reduced crew workload. At the same time, conventional 'static' automation has sometimes degraded human operator monitoring performance, increased workload, and reduced situation awareness. Adaptive automation represents an alternative to static automation. In this approach, task allocation between human operators and computer systems is flexible and context-dependent rather than static. Adaptive automation, or adaptive task allocation, is thought to provide for regulation of operator workload and performance, while preserving the benefits of static automation. In previous research we have reported beneficial effects of adaptive automation on the performance of both pilots and non-pilots of flight-related tasks. For adaptive systems to be viable, however, such benefits need to be examined jointly in the context of a single set of tasks. The studies carried out under this project evaluated a systematic method for combining different forms of adaptive automation. A model for effective combination of different forms of adaptive automation, based on matching adaptation to operator workload was proposed and tested. The model was evaluated in studies using IFR-rated pilots flying a general-aviation simulator. Performance, subjective, and physiological (heart rate variability, eye scan-paths) measures of workload were recorded. The studies compared workload-based adaptation to to non-adaptive control conditions and found evidence for systematic benefits of adaptive automation. The research provides an empirical basis for evaluating the effectiveness of adaptive automation in the cockpit. The results contribute to the development of design principles and guidelines for the implementation of adaptive automation in the cockpit, particularly in general aviation, and in other human-machine systems. Project goals were met or exceeded. The results of the research extended knowledge of automation-related performance decrements in pilots and demonstrated the positive effects of adaptive task allocation. In addition, several practical implications for cockpit automation design were drawn from the research conducted. A total of 12 articles deriving from the project were published.

Parasuraman, Raja↗

NASA NTRS2019

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗

NASA NTRSDate not supplied

Identifying Trends in Landing Profiles After Long Duration Spaceflight

BACKGROUND As NASA’s mission programs begin to shift from Low Earth Orbit (LEO) to planetary mission profiles, the importance of understanding the phenomena a human experience when returning from spaceflight is of increased importance. The purpose of this study was to assess trends across individuals in the symptoms experienced during the landing process of long duration ISS missions. METHODS Data for this study is an aggregation of mission level data from forms used by crew surgeons at R+0, electronic medical records, notes from weekly Space Medicine Operation Team meetings, records in the Shuttle Mission Data Archive, and data collected by research teams in the Human Research Program (HRP). Aggregated data was used in descriptive analysis of the trends in medical events and countermeasure use. The data was also used to identify high value targets for emphasis in on going surveillance efforts. RESULTS Completeness of reporting varied greatly over time and across missions dependent on information sources available for data extraction. Landing forms provided the most complete data but still missed or left unconfirmed, several, common symptoms, and countermeasures. Data aggregation did show to cover gaps within individual data sources. Commonly reported symptoms included nystagmus, vertigo, and nausea. Common protocols for fluid loading and meclizine are reflected within the data set. DISCUSSION The data set generated in this project provides a foundation that show how symptoms of astronauts as they return to Earth varies across the long duration ISS missions. While there is an abundance of information provided within the data set, there are still inconsistencies in reporting especially in the absence of the landing day form. Further data collection practices should be standardized to ease the burden on crew surgeons during R+0 exams and better collect high value variables.

Sam Jacobs↗

NASA NTRS2002

Atomic Data for the K-Vacancy States of Fe XXIV

As part of a project to compute improved atomic data for the spectral modeling of iron K lines, we report extensive calculations and comparisons of atomic data for K-vacancy states in Fe XXIV. The data sets include: (i) energy levels, line wavelengths, radiative and Auger rates; (ii) inner-shell electron impact excitation rates and (iii) fine structure inner-shell photoionization cross sections. The calculations of energy levels and radiative and Auger rates have involved a detailed study of orbital representations, core relaxation, configuration interaction, relativistic corrections, cancellation effects and semi-empirical corrections. It is shown that a formal treatment of the Breit interaction is essential to render the important magnetic correlations that take part in the decay pathways of this ion. As a result, the accuracy of the present A-values is firmly ranked at better than 10% while that of the Auger rates at only 15%. The calculations of collisional excitation and photoionization cross sections take into account the effects of radiation and spectator Auger dampings. In the former, these effects cause significant attenuation of resonances leading to a good agreement with a simpler method where resonances are excluded. In the latter, resonances converging to the K threshold display symmetric profiles of constant width that causes edge smearing.

Bautista, M. A.↗

NASA NTRS2003

Atomic Data for the K-vacancy States of Fe XXIV

Bautista, M. A.↗

NASA NTRS2019

High-Fidelity Multidisciplinary Sensitivity Analysis Framework for Multipoint Rotorcraft Optimization

A multidisciplinary, gradient-based sensitivity-analysis methodology is evaluated for optimization of rotorcraft configurations. The tightly coupled discipline models include physics-based fluid dynamics and rotorcraft comprehensive analysis. A discretely-consistent adjoint method accounts for sensitivities of the unsteady flow and unstructured, dynamic, over set grids, while sensitivities of structural responses to aerodynamic loads are computed using a complex-variable method. The methodology is applied to optimize the shape of UH-60A Blackhawk helicopter blades for hover and forward flight conditions. The objective of the multipoint design is to simultaneously increase the rotorcraft figure of merit in a hover flight and reduce the rotor power in a forward flight. Trimmed loose-coupling solutions for the baseline configuration are used to initiate the tight-coupling multidisciplinary analysis. Target thrust and rolling and pitching moments are enforced as optimization constraints. The optimized configuration improves the optimization metrics at both design points. The improved performance and all constraints are maintained over many revolutions beyond the optimization interval, satisfying the required flight conditions. Computational cost of the optimization cycle is assessed in a high-performance computing environment and found affordable for design of rotorcraft in general level-flight conditions.

Wang, Li↗

NASA NTRSDate not supplied

Deriving Climate Change Signal from Hyperspectral Sounders Using Spectral Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric temperature, water vapor and trace gas vertical profiles. We have developed a radiometrically consistent spectral fingerprinting method to derive climate change signals from Aqua AIRS/AMSU and S-NPP CrIS/ATMS data. The climate variables include temperature and water vapor profiles, cloud, trace gases, and surface skin temperature. The radiative kernels obtained via a single field of view physical retrieval algorithm under all-sky conditions. A key component to this work is a Principal Component-based Radiative Transfer Model (PCRTM). It is 4 orders of magnitude faster than a line-by-line radiative transfer model while keeping a similar accuracy (0.03 K RMS errors with close to zero bias). The PCRTM includes multiple scattering of clouds and non-thermodynamics equilibrium of CO2 in the RT calculations. Instead of quantifying the radiometric differences between AIRS/AMSU and CrIS/ATMS measurements directly using Simultaneous Nadir Overpass (SNO) or Double Difference Technique (DDT), we use the radiometric consistent fingerprinting scheme to derive two sets of space-time averaged anomalies from the Level 1 data of AIRS/AMSU and CrIS/ATMS. The derived anomalies in geophysical space will form a long-term, stable, and continuous climate data record. We can further infer the causes of any offset or drift by studying the differences between two overlapping data sets. For example, the offset in surface skin temperature anomaly time series will most likely caused by the Blackbody temperature calibration errors of the sounder instruments.

climate↗

NASA NTRSDate not supplied

NASA Langley FUN3D Analyses in Support of the 1st AIAA Stability and Control Prediction Workshop

This work summarizes the results of FUN3D analyses conducted for the 1st AIAA Stability and Control Workshop on behalf of participants from the NASA Langley Research Center. The workshop was created to establish best practices for the prediction of stability and control derivatives using computational fluid dynamics and assess the limitations of these methods when those best practices are applied. The inaugural workshop considered the ONERA version of the NASA/Boeing Common Research Model, which includes the wing, body, horizontal tail, and a vertical tail designed by ONERA. Wind tunnel data at small sideslip angles remain unpublished and served as ‘blind’ data for computational comparisons. The present research generated workshop test case data using the NASA FUN3D code, which is a parallelized, unstructured, node-based, finite-volume discretization, Reynolds-averaged Navier-Stokes flow solver. Steady- state numerical simulations were conducted for workshop test cases investigating the following: grid convergence, Mach number effect on static stability, wind tunnel sting increments, static stability-derivative calculations, and a sideslip angle sweep. Results were generated for two series of unstructured, mixed-element grids, one set provided by the workshop and another set created using the HeldenMesh grid generation software. The results provided include total- and component-level breakdowns of the force and moment coefficients, in addition to sectional pressure distributions for the wing and tail components for comparisons to wind tunnel data.

CFD↗

NASA NTRS2020

Quasi-Static and Dynamic Analysis of Composite Panels: Challenges in Engineering-Level Commercial Software

In engineering applications, where analysis time and efficiency are essential, analytical models and commercially available finite element (FE) material models are the two mainstream methods used to analyze composite crush scenarios. A reliable numerical model addressing the crushing response of composite materials requires a nonlinear progressive damage analysis which includes appropriate failure mechanisms such as matrix cracking, fragmentation, delamination, and fiber breakage. One might be able to address all these interacting failure responses through implementation/validation of a user defined material model or by utilization of a commercially available model, the latter being the most efficient engineering approach. In this paper, the quasi-static and dynamic crushing response of composite specimens, consisting of a C-channel and a corrugated geometry manufactured with carbon fiber/epoxy matrix fabric, are modeled using the progressive composite damage model within ABAQUS. The novel part of this work, which has not been previously addressed in the literature, is the utilization of a detailed parametric study to optimize composite damage model parameters for a given quasi-static crush simulation in ABAQUS. C-channel experiments were used to calibrate the model and then refine/optimize a set of material parameters that best fit the experimental results. These identical parameters were then used to simulate the crush response of the corrugated channel specimens, thereby making it a pure prediction and not a double recalibration. Next, the dynamic response of both panels were predicted, further confirming the predictive capability of the developed numerical model. The effect of parameter variation on the crush response is fully documented for future use in engineering applications utilizing this specific ABAQUS damage model.

Paria Naghipour↗