Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “empirical validation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

International Space Station Microgravity Analytical Model Correlation And Update

The acceleration environment aboard the completed International Space Station (ISS) is a key resource for scientific and technological endeavors. Hardware verification activIties and early measurements indicate that the ISS is well on the way of meeting these "Assembly Complete" "microgravity" provisions, however, the simulation models that compute these accelerations have, to date, lacked the high degree of empirical validation typical of standard aerospace industry practices. Assembly stage, on-orbit measurements are used to address this shortcoming and to develop higher confidence in the simulation models. The Phase I correlation results show the analyses to be consistently conservative, producing higher than measured levels. The 25 to 30% greater quasi-steady computations are deemed acceptable for verification. Updates are made to localized structural dynamic and vibroacoustic parameters that reduce responses in selected one-third octave bands by almost 50%. These models are then used for the Assembly Complete verification analysis which concludes that the ISS vehicle meets the ISS microgravity requirements with minor reservations. Two of the sixteen rack are marginally non-compliant in the quasi-steady regime, and operational constraints are needed on the U. S. Lab and ESA APM vacuum resource vents, and the Russian Resistive Exercise Device in the structural dynamic regime.

DelBasso, Steve↗
NASA NTRS2014

SUPERball: Exploring Tensegrities for Planetary Probes

The Dynamic Tensegrity Robotics Lab (DTRL) at NASA Ames Research Center is developing a compliant and distributed tensegrity robotic platform for planetary exploration. Working in collaboration with Ghent University, the DTRL built an untethered prototype robot, the SUPERball. In this work, multiple issues with the current SUPERball design are addressed, when considering an example mission to Titan. Specifically, engineering requirements for the mission are empirically validated, and the current design is extended under these requirements to meet expanded goals.Survival of impact forces under entry, descent, and landing are verified with a physical experiment performed in collaboration with the University of Idaho. Then, concepts for a fully-actuated redesign of SUPERball are generated, compared, and validated against current engineering requirements. This exploratory work moves the SUPERball project toward an eventual flight-ready design.\

Tensegrity↗
NASA NTRS2022

The Cooling Loop A Anomaly of 2013: A Case Study in Human-Systems Resilience

Throughout the history of human spaceflight, NASA has employed an operational paradigm of 24/7 dependence on experts in Mission Control Center (MCC). In addition to nominal flight control and mission operations, these 85+ experts per shift manage anomaly detection, diagnosis, and response, and support the crew in real-time in performing maintenance and repair, procedure execution, and other complex mission operations. Future long-duration exploration missions (LDEMs) beyond low-Earth orbit (LEO) will not operate successfully using this same Human-Systems Integration Architecture (HSIA) where crew rely on ground controllers, have ready access to resupply, and have a fallback plan of evacuation. As distance from Earth increases and the communication delay grows, crews will need to respond independently and adequately to time-critical vehicle malfunctions. It will not always be sufficient or even possible to ‘safe the system’ and then wait upon ground intervention. A new and radically different HSIA is needed to accommodate the paradigm shift of deep-space travel. Historical International Space Station (ISS) data show that for a 30-day mission, the likelihood of a high-consequence vehicle anomaly of uncertain origin that requires rapid response is greater than 10%. The likelihood of such an event is 50% by the fourth month of the mission, and it grows exponentially with time. Our team has conducted in-depth investigations into these events and their corresponding anomaly resolution activities. Using MCC and Mission Evaluation Room (MER) anomaly resolution artifacts (including meeting summaries, caution and warning data, and ISS daily summaries), we created timelines detailing ground actions and in-orbit events for two significant anomalies. We then mapped these timelines onto Mars transit conditions, introducing a ground-crew communications time delay and shifting immediate response, time-critical task execution, and vehicle commanding to the crew. In detailing successful anomaly resolution in transit to Mars, the timelines highlight where effective resolution requires drastically evolved onboard capabilities. Though this research has yielded a rich data set based on ground response in past missions, there is still insufficient knowledge to assess the potential impact of inflight anomalies on a small autonomous crew on future LDEMs beyond LEO. To begin building an evidence base that will inform future HSIA standards and requirements, we are developing an approach to systematically capture crew anomaly response and procedure execution during early Artemis missions. Being the first human spaceflight beyond LEO since Apollo, early Artemis missions provide a rare and unique opportunity to serve as a testbed for Mars missions. Our work aims to capitalize on planned data collection to derive crew operational responses to anomalous events in real-time. Our team is also researching the level of simulation fidelity required for empirically validating proposed HSIA standards and evaluating HSIA implementations for LDEMs beyond LEO. This work will produce a trade space study of HSIA simulation objectives and fidelity requirements. Ultimately, these research efforts will assist in developing the standards and technologies needed to build a next-generation HSIA for LDEMs beyond LEO.

human-systems integration architecture↗
NASA NTRSDate not supplied

The Examination of Individual Factors and AFTE Training Outcomes

Introduction: Motion sickness is common among military aviators. It describes a specific group of symptoms that include epigastric awareness, nausea, pallor, sweating, salivation, and fatigue. Occurrences of these symptoms can pose a significant risk to safety and adversely impact mission success. Accordingly, researchers have developed specific interventions to act as countermeasures. For example, Autogenic Feedback Training Exercise has been empirically validated as a training method that mitigates the impact of motion sickness. However, it remains unclear the extent to which individual factors moderate (or mediate) the effects of this intervention. The examination of individual factors such as interoceptive accuracy (IA) and specific personality traits might provide insight into whom may benefit most from AFTE. Methods: Participants were administered the Big Five Inventory (BFI) and State Trait Anxiety Inventory (STAI). In addition, they were given an interoceptive accuracy task (i.e., heartbeat counting task). The participants’ reported value was then compared to the actual number of heart beats obtained via ECG. Completion of the IA task was followed by pre- AFTE and Post-AFTE rotating chair tests to evaluate motion sickness and the effects of AFTE training. Results: Participants (n=16) were evaluated on IA, personality factors (i.e., BFI & STAI) and performance on the rotating chair. IA was unrelated to personality traits (p > .05), but inversely related to state anxiety post training (p < .05). Finally, IA did not predict performance (i.e., rotations or minutes tolerated ?) on rotating chair F (1, 14) = 1.18, p> .05). Discussion:(1) IA is unrelated to personality traits as measured by BFI and STAI. (2) Individual factors are unrelated to AFTE training outcome. (3) AFTE training can be beneficial for all.

motion sickness↗
NASA NTRS2021

Development and Validation of an Empirical Ocean Color Algorithm with Uncertainties: A Case Study with the Particulate Backscattering Coefficient

We explored how algorithm (model) and in situ measurement (observation) uncertainties can effectively be incorporated into empirical ocean color model development and assessment. In this study we focused on methods for deriving the particulate backscattering coefficient at 555 nm, b(bp)(555)/(m). We developed a simple empirical algorithm for deriving b(bp)(555) as a function of a remote sensing reflectance line height (LH) metric. Model training was performed using a high-quality bio-optical dataset that contains coincident in situ measurements of the spectral remote sensing reflectances, R(rs)(λ)/(sr), and the spectral particulate backscattering coefficients, b(bp)(λ). The LH metric used is defined as the magnitude of Rrs(555) relative to a linear baseline drawn between R(rs)(490) and R(rs)(670). Using an independent validation dataset, we compared the skill of the LH-based model with two other models. We used contemporary validation metrics, including bias and mean absolute error (MAE), that were corrected for model and observation uncertainties. The results demonstrated that measurement uncertainties do indeed impact contemporary validation metrics such as mean bias and MAE. Zeta-scores and z-tests for overlapping confidence intervals were also explored as potential methods for assessing model skill.

ocean color↗
NASA NTRS2014

Empirical and Face Validity of Software Maintenance Defect Models Used at the Jet Propulsion Laboratory

At the Mission Design and Navigation Software Group at the Jet Propulsion Laboratory we make use of finite exponential based defect models to aid in maintenance planning and management for our widely used critical systems. However a number of pragmatic issues arise when applying defect models for a post-release system in continuous use. These include: how to utilize information from problem reports rather than testing to drive defect discovery and removal effort, practical model calibration, and alignment of model assumptions with our environment.

software reliability↗
NASA NTRS2015

Development, Testing, and Validation of a Model-Based Tool to Predict Operator Responses in Unexpected Workload Transitions

One human factors challenge is predicting operator performance in novel situations. Approaches such as drawing on relevant previous experience, and developing computational models to predict operator performance in complex situations, offer potential methods to address this challenge. A few concerns with modeling operator performance are that models need to realistic, and they need to be tested empirically and validated. In addition, many existing human performance modeling tools are complex and require that an analyst gain significant experience to be able to develop models for meaningful data collection. This paper describes an effort to address these challenges by developing an easy to use model-based tool, using models that were developed from a review of existing human performance literature and targeted experimental studies, and performing an empirical validation of key model predictions.

model-based workload transition tool↗
NASA NTRSDate not supplied

Transfer Function Models and Sensitivity Analysis

In many situations, real or induced flaws such as tight cracks with known morphology cannot be manufactured in part configuration specimens or in real parts. Typically, fatigue cracks are manufactured in simple geometry specimens such as flat plates, dog-bone shaped flat or round specimens. If a nondestructive evaluation (NDE) technique is required to provide a reliably detectable target flaw size denoted as α_(90/95) for induced flaws in real part, then the direct method for qualifying the NDE procedure is to use the appropriate induced flaw specimens and perform probability of detection analysis using these flaws. This can be described as direct POD demonstration testing, which may follow guidelines of MIL-HDBK-1823. This paper considers a case, where induced flaws are not available in part configuration specimens. Therefore, a direct POD demonstration study cannot be undertaken. In such situation, general practice for NDE procedure qualification is to use artificial flaws in simple geometry and part configuration specimens, and induced flaws in the chosen simple geometry specimens. Signal response data is taken on all sets of artificial and induced flaws. NDE procedure testing on induced flaw in simple geometry specimen is called NDE demonstration testing here. A transfer function NDE procedure qualification method for forward case calculates predicted induced flaw size for demonstration using a chosen target flaw size. Another transfer function method for inverse case, calculates the target flaw size using a given demonstration flaw size. The transfer function analysis assumes relationship of artificial flaw signal responses in real parts and simple geometry specimens; and induced flaw responses in simple geometry specimens to induced flaws in real parts. The signal response transfer relationships model should be defined before transfer function models can be devised. Assuming that the signal response transfer relationships model is valid, forward and inverse case transfer function methods have been devised. Because of lack of signal response data from induced flaws in real part, 90/95% POD/confidence (P/C) cannot be demonstrated directly. However, the transfer function method may be assessed using simulation to evaluate whether the resulting target flaw size or demonstration flaw size provides adequate confidence to the assumed signal response transfer relationships model. Therefore, the transfer function approach is a risk assessment approach. Both the signal response transfer relationships model and the transfer function model are important in managing risk in results provided by the transfer function NDE technique qualification or assessment. The signal response transfer relationships model needs to be validated with empirical data and then transfer function model needs to be validated for desired P/C on case-by-case basis.

Nondestructive evaluation↗
NASA NTRS1990

Tank Pressure Control Experiment - A low-g mixing investigation

The Tank Pressure Control Experiment (TPCE) was conceived to meet the need for an aspect of cryogenic fluid management technology that is critical to several future national space missions: control of cryogenic storage tank pressures by active mixing. In-space testing is the only means of obtaining the fluid dynamic data necessary to develop and test predictive models of mixing. These models, when validated, will allow future cryogenic systems to be designed with more efficient and reliable pressure control systems. The objectives of the TPCE project are to characterize the fluid dynamics of jet-induced mixing in low gravity, evaluate the validity of empirical models and correlations, and provide data for use in developing and validating computational fluid dynamic models. This paper discusses prior studies of low-g mixing, the objectives and benefits of TPCE, the design and status of the payload, and preliminary results obtained from low-g aircraft testing.

Bentz, M. D.↗
NASA NTRSDate not supplied

Advanced Materials for the Lunar Surface: Multiscale Computational Design of Refractory Alloys and Carbides

Emerging operational environments, such as the lunar surface, present novel challenges for NASA and drive the need for advanced materials in applications like fission surface power systems. To address these demands, computational materials science is rapidly evolving to augment or replace costly and hazardous empirical testing. Although materials selection at NASA remains predominantly experimentally driven, advanced simulation methodologies are being steadily integrated into the engineering lifecycle. This work details the application of multiscale simulation techniques—including first-principles calculations, CALPHAD, dislocation dynamics, and molecular dynamics—at NASA's Ames Research Center to evaluate advanced materials for extreme environments. First, we present contributions to the Space Nuclear Propulsion Project. Be-cause propellant channel coatings in nuclear thermal rockets must withstand high-pressure, high-temperature hydro-gen, optimizing these materials is critical. First-principles calculations were employed to establish a rigorous quantitative and qualitative understanding of the behavior of the refractory carbides ZrC, NbC, and their mixtures in high-enthalpy hydrogen environments. This necessitated the generation of high-fidelity thermodynamic models for both stoichiometric and carbon-depleted carbides, both with and without the presence of hydrogen. Furthermore, we highlight efforts under the Refractory Alloy Additive Manufacturing Build Optimization (RAAMBO) project, where existing and novel alloy compositions were assessed for additive manufacturing printability and subsequent performance in applications such as heat pipes and rocket nozzle extensions. This was accomplished through a comprehensive multiscale simulation framework that bridged the gap from the nanometer to the millimeter scale. Across both initiatives, rigorous validation against empirical data was prioritized. By systematically employing a verified and validated computational frame-work, we demonstrate how simulation effectively supports multidisciplinary engineering efforts, builds project-wide confidence, and drives critical materials development.

computational materials↗
NASA NTRS2008

Solar Tower Experiments for Radiometric Calibration and Validation of Infrared Imaging Assets and Analysis Tools for Entry Aero-Heating Measurements

The NASA Engineering and Safety Center sponsored Hypersonic Thermodynamic Infrared Measurements assessment team has a task to perform radiometric calibration and validation of land-based and airborne infrared imaging assets and tools for remote thermographic imaging. The IR assets and tools will be used for thermographic imaging of the Space Shuttle Orbiter during entry aero-heating to provide flight boundary layer transition thermography data that could be utilized for calibration and validation of empirical and theoretical aero-heating tools. A series of tests at the Sandia National Laboratories National Solar Thermal Test Facility were designed for this task where reflected solar radiation from a field of heliostats was used to heat a 4 foot by 4 foot test panel consisting of LI 900 ceramic tiles located on top of the 200 foot tall Solar Tower. The test panel provided an Orbiter-like entry temperature for the purposes of radiometric calibration and validation. The Solar Tower provided an ideal test bed for this series of radiometric calibration and validation tests because it had the potential to rapidly heat the large test panel to spatially uniform and non-uniform elevated temperatures. Also, the unsheltered-open-air environment of the Solar Tower was conducive to obtaining unobstructed radiometric data by land-based and airborne IR imaging assets. Various thermocouples installed on the test panel and an infrared imager located in close proximity to the test panel were used to obtain surface temperature measurements for evaluation and calibration of the radiometric data from the infrared imaging assets. The overall test environment, test article, test approach, and typical test results are discussed.

Splinter, Scott C.↗
NASA NTRS1981

Synchrotron emissivity from mildly relativistic particles

A simple approximate method for the evaluation of the spectrum and directivity of the synchrotron radiation from an ensemble of particles in a given magnetic field is considered, taking into account the results of this method for the total emissivity at high harmonics. The general formula is presented along with the details of the derivation of the emissivity for an arbitrary energy spectrum and pitch angle distribution of particles. The emissivities for some commonly encountered particle distributions are provided and some empirical formulae valid for a large range of the parameters are given. The results from the analytic expressions are compared with those obtained by detailed numerical calculations. For isotropic pitch angle distributions, spectra from the simple analytic expressions agree with the numerical results to a high degree of accuracy even at lower harmonics.

Petrosian, V.↗
NASA NTRS1991

Dissociation of diatomic gases

The Landau-Zener theory of reactive cross sections has been applied to diatomic molecules dissociating from a ladder of rotational and vibrational states. Although the preexponential factor of the Arrhenius rate expression is shown to be a complex function of the dimensionless activation energy, the average over all states in the ladder is well represented by a single factor that varies about as T exp (-n), where the coefficient n is the order of unity. This relation agrees very well with experimental data for dissociation of O2 and N2, for example. The results validate previous empirical assignment of a single preexponential factor in the Arrhenius expression and justify the extrapolation of the expression well beyond the range of data. The theory is then used to calculate the effect of vibrational nonequilibrium on dissociation rate. For Morse oscillators the results are about the same as for harmonic oscillators, and the dissociation from a ladder of equilibrium rotational and nonequilibrium vibrational states is close to an analytic approximation provided by Hammerling, Kivel, and Teare for harmonic oscillators all dissociating from the ground rotational state.

Hansen, C. F.↗
NASA NTRS2000

Modeling Heat-Transfer in Animal Habitats in the Shuttle Orbiter Middeck

A mathematical model has been developed to evaluate the heat transfer characteristics of an Animal Enclosure Module (AEM) in the microgravity environment. The AEM is a spaceflight habitat that provides life support for up to six rodents in the Space Shuttle Middeck. Currently, temperatures within the AEM are recorded in real time using a solid state data recorder; however, the data are only available for analysis post-flight. This temperature information is useful for characterizing the thermal environment of the AEM for researchers, but is unavailable during flight operations. Because animal health in microgravity is directly linked to the thermal environment, the ability to predict internal AEM temperatures is extremely useful to life science researchers. NASA flight crews typically carry hand-held temperature measurement devices which allow them to provide ground researchers with near real time readings of AEM inlet temperature; however, higher priority operations limit the frequency at which these measurements can be made and subsequently downlinked. The mathematical model developed allows users to predict internal cage volume temperatures based on knowledge of the ambient air temperature entering the AEM air intake ports. Additionally, an average convective heat transfer coefficient for the AEM has been determined to provide engineers with the requisite information to facilitate future design improvements and product upgrades. The model has been validated using empirical data from a series of three Space Shuttle missions.

Eodice, Michael T.↗
NASA NTRSDate not supplied

A Machine Learning Approach to Predict Martensitic Transition Temperatures for Shape Memory Alloys

Shape memory alloys (SMAs) are a unique class of materials with several remarkable properties including shape recovery, superelasticity, etc. Especially important for many NASA applications is the ability to tune the martensitic phase transition temperature by varying the alloy composition. Nickel-titanium (NiTi) based alloys are the most widely studied of this class, with compositions involving ternary, quaternary, or higher additions being considered. Over the past several years, a significant database of SMA properties has been assembled by NASA researchers. Such a database is ideal for data science-based approaches including machine learning. We present results from a developed machine learning model capable of accurately predicting the transition temperature of SMAs across a wide range of compositions. Our model has the added benefit of interpretability and even provides confidence intervals for our predictions. This model will make rapid screening and design of new SMA materials possible. Predictions from the machine learning model can be validated by empirical and/or atomistic scale modeling.

Shreyas Honrao↗
NASA NTRS2013

Develop a Model Component

During my internship at NASA, I was a model developer for Ground Support Equipment (GSE). The purpose of a model developer is to develop and unit test model component libraries (fluid, electrical, gas, etc.). The models are designed to simulate software for GSE (Ground Special Power, Crew Access Arm, Cryo, Fire and Leak Detection System, Environmental Control System (ECS), etc. ~.) before they are implemented into hardware. These models support verifying local control and remote software for End-Item Software Under Test (SUT). The model simulates the physical behavior (function, state, limits and 110) of each end-item and it's dependencies as defined in the Subsystem Interface Table, Software Requirements & Design Specification (SRDS), Ground Integrated Schematic (GIS), and System Mechanical Schematic.(SMS). The software of each specific model component is simulated through MATLAB's Simulink program. The intensiv~ model development life cycle is a.s follows: Identify source documents; identify model scope; update schedule; preliminary design review; develop model requirements; update model.. scope; update schedule; detailed design review; create/modify library component; implement library components reference; implement subsystem components; develop a test script; run the test script; develop users guide; send model out for peer review; the model is sent out for verific~tionlvalidation; if there is empirical data, a validation data package is generated; if there is not empirical data, a verification package is generated; the test results are then reviewed; and finally, the user. requests accreditation, and a statement of accreditation is prepared. Once each component model is reviewed and approved, they are intertwined together into one integrated model. This integrated model is then tested itself, through a test script and autotest, so that it can be concluded that all models work conjointly, for a single purpose. The component I was assigned, specifically, was a fluid component, a discrete pressure switch. The switch takes a fluid pressure input, and if the pressure is greater than a designated cutoff pressure, the switch would stop fluid flow.

Ensey, Tyler S.↗