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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

High-Resolution and Analytical TEM Investigation of Space Radiation Processing Effects in Primitive Solar System Materials and Airless Planetary Surface Environments

Energetic ions present in the diverse plasma conditions in space play a significant role in the formation and modification of solid phases found in environments ranging from the interstellar medium (ISM) to the surfaces of airless bodies such as asteroids and the Moon. These effects are often referred to as space radiation processing, a term that encompasses changes induced in natural space-exposed materials that may be only structural, such as in radiation-induced amorphization, or may involve ion-induced nanoscale to microscale chemical changes, as occurs in preferential sputtering and ion-beam mixing. Ion sputtering in general may also be responsible for partial or complete erosion of space exposed materials, in some instances possibly bringing about the complete destruction of free-floating solid grains in the ISM or in circumstellar nebular dust clouds. We report here on two examples of the application of high-resolution and analytical transmission electron microscopy (TEM) to problems in space radiation processing. The first problem concerns the role of space radiation processing in controlling the overall fate of Fe sulfides as hosts for sulfur in the ISM. The second problem concerns the known, but as yet poorly quantified, role of space radiation processing in lunar space weathering.

Christoffersen, R.↗
NASA NTRS1990

Structural evaluation of composite fuselage structure fabricated using a THERM-X process

An experimental and analytical program has been implemented to evaluate the structural performance of complex composite parts made using THERM-X processing techniques. Preliminary analysis shows 22-percent cost savings for parts made with a THERM-X process over parts made with conventional manufacturing methods. Results of building-block tests from the coupon to the element level, which represent structural details of the curved integrally stiffened panel selected as the full-scale article, are also reported. Comparisons with baseline results and analytical predictions show that THERM-X processing yields parts with stiffness and strength comparable to or slightly better than conventional manufacturing procedures. Compression strength after low-speed impact damage (caused by a drop weight impactor) is also comparable to parts fabricated with conventional methods.

Kassapoglou, Christos↗
NASA NTRS1986

Nonlinear sensitivity coefficients and corrections in system identification

The evaluation of sensitivity coefficients which are the changes in the eigencharacteristics with respect to changes in the structural parameters is important in the identification of structural systems. In such studies the commonly used linearized sensitivity coefficients for system identification have occasionally resulted in poor convergence or even divergence during the iteration process to update analytical models for better correlation with the test data. Nonlinear sensitivity coefficients and nonlinear correction terms, usually eliminated during the linearization process, have been developed to evaluate sensitivity coefficients of linear systems. Application to computer simulated example problems indicates a more rapid and stable convergence of the iteration processes to update the analytical model for the improvement of the correlation with test data. The successful application of combining the nonlinear sensitivity coefficients and nonlinear correction terms with the Multiple Boundary Condition Tests enhances the ability to validate large space structures by ground tests.

Kuo, C. P.↗
NASA NTRS2016

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

data analytics↗
NASA NTRS2010

Modeling of Failure for Analysis of Triaxial Braided Carbon Fiber Composites

In the development of advanced aircraft-engine fan cases and containment systems, composite materials are beginning to be used due to their low weight and high strength. The design of these structures must include the capability of withstanding impact loads from a released fan blade. Relatively complex triaxially braided fiber architectures have been found to yield the best performance for the fan cases. To properly work with and design these structures, robust analytical tools are required that can be used in the design process. A new analytical approach models triaxially braided carbon fiber composite materials within the environment of a transient dynamic finite-element code, specifically the commercially available transient dynamic finite-element code LS-DYNA. The geometry of the braided composites is approximated by a series of parallel laminated composites. The composite is modeled by using shell finite elements. The material property data are computed by examining test data from static tests on braided composites, where optical strain measurement techniques are used to examine the local strain variations within the material. These local strain data from the braided composite tests are used along with a judicious application of composite micromechanics- based methods to compute the stiffness properties of an equivalent unidirectional laminated composite required for the shell elements. The local strain data from the braided composite tests are also applied to back out strength and failure properties of the equivalent unidirectional composite. The properties utilized are geared towards the application of a continuum damage mechanics-based composite constitutive model available within LS-DYNA. The developed model can be applied to conduct impact simulations of structures composed of triaxially braided composites. The advantage of this technology is that it facilitates the analysis of the deformation and damage response of a triaxially braided polymer matrix composite within the environment of a transient dynamic finite-element code such as LS-DYNA in a manner which accounts for the local physical mechanisms but is still computationally efficient. This methodology is tightly coupled to experimental tests on the braided composite, which ensures that the material properties have physical significance. Aerospace or automotive companies interested in using triaxially braided composites in their structures, particularly for impact or crash applications, would find the technology useful. By the development of improved design tools, the amount of very expensive impact testing that will need to be performed can be significantly reduced.

Goldberg, Robert K.↗
NASA NTRS1972

An investigation of the open-loop amplification of Reynolds number dependent processes by wave distortion

Analytical and experimental studies were initiated to determine if the response of a constant temperature hot wire anemometer to acoustic oscillations could serve as an analog to the response of the drop vaporization burning rate process to acoustic oscillations, and, perhaps, also as an analog to any Reynolds number dependent process. The motivation behind this study was a recent analytical study which showed that distorted acoustic oscillations could amplify the open-loop response of vaporization limited combustion. This type of amplification may be the cause of unstable combustion in liquid propellant rocket engines. The analytical results obtained for the constant temperature anemometer are similar in nature to those previously obtained for vaporization limited combustion and indicate that the response is dependent on the amount and type of distortion as well as other factors, such as sound pressure level, Mach number and hot wire temperature. Preliminary results indicate qualitative agreement between theory and experiment.

Purdy, K. R.↗
NASA NTRS1992

Analysis and testing of propellant feed system priming process

This paper presents the analytical and the experimental results pertaining to the priming process of the propellant feed system with initial line pressures starting from 0 psia and greater. The analytical methods employ the method of characteristics to solve for the one-dimensional liquid transients in the liquid-full segments and the lumped inertia technique to model the dynamics of the partially filled segments or the two-phase segments. The advantages of these methods are (1) fluid compressibility and piping flexibility are accounted for in the solution; and (2) the characteristics method can be used in the solution of a complex system. The analytical results were compared with test results. Excellent correlation was obtained between predictions and test results verifying the essential aspects of the analytical modeling techniques and providing the foundation for analyzing a complicated network system.

Lin, T. Y.↗
NASA NTRS2011

Sample Handling and Processing on Mars for Future Astrobiology Missions

In most analytical investigations, there is a need to process complex field samples for the unique detection of analytes especially when detecting low concentration organic molecules that may identify extraterrestrial life. Sample processing for analytical instruments is time, resource and manpower consuming in terrestrial laboratories. Every step in this laborious process will have to be automated for in situ life detection. We have developed, and are currently demonstrating, an automated wet chemistry preparation system that can operate autonomously on Earth and is designed to operate under Martian ambient conditions. This will enable a complete wet chemistry laboratory as part of future missions. Our system, namely the Automated Sample Processing System (ASPS) receives fines, extracts organics through solvent extraction, processes the extract by removing non-organic soluble species and delivers sample to multiple instruments for analysis (including for non-organic soluble species).

Beegle, Luther↗
NASA NTRS1992

Structural ceramics

This presentation gives a brief history of the field of materials sciences and goes on to expound the advantages of the fastest growing area in that field, namely ceramics. Since ceramics are moving to fill the demand for lighter, stronger, more corrosion resistant materials, advancements will rely more on processing and modeling from the atomic scale up which is made possible by advanced analytical, computer, and processing techniques. All information is presented in viewgraph format.

Craig, Douglas F.↗
NASA NTRS1998

Full Flight Envelope Direct Thrust Measurement on a Supersonic Aircraft

Direct thrust measurement using strain gages offers advantages over analytically-based thrust calculation methods. For flight test applications, the direct measurement method typically uses a simpler sensor arrangement and minimal data processing compared to analytical techniques, which normally require costly engine modeling and multisensor arrangements throughout the engine. Conversely, direct thrust measurement has historically produced less than desirable accuracy because of difficulty in mounting and calibrating the strain gages and the inability to account for secondary forces that influence the thrust reading at the engine mounts. Consequently, the strain-gage technique has normally been used for simple engine arrangements and primarily in the subsonic speed range. This paper presents the results of a strain gage-based direct thrust-measurement technique developed by the NASA Dryden Flight Research Center and successfully applied to the full flight envelope of an F-15 aircraft powered by two F100-PW-229 turbofan engines. Measurements have been obtained at quasi-steady-state operating conditions at maximum non-augmented and maximum augmented power throughout the altitude range of the vehicle and to a maximum speed of Mach 2.0 and are compared against results from two analytically-based thrust calculation methods. The strain-gage installation and calibration processes are also described.

Conners, Timothy R.↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben D Phillips↗
NASA NTRSDate not supplied

End-To-End Uncertainty Quantification with Analytical Derivatives for Design Under Uncertainty

Uncertainty quantification (UQ) is a rapidly growing and evolving discipline, especially within the aerospace community. Performing analysis with UQ can provide decision makers with a wealth of information about a candidate design. However, the value of UQ is fully realized when the information gained during UQ analysis is leveraged in a feedback loop of a design optimization process, often referred to as design under uncertainty. Although design under uncertainty can be a powerful risk mitigation technique, there are a number of roadblocks that prevent its implementation. Two primary factors are computational costs and added complexity of the analysis. High fidelity simulations on the order tens of uncertain variables quickly become computationally infeasible. Also, implementing UQ into an existing multidisciplinary design and optimization (MDO) process often requires extensive knowledge of the UQ methods and careful treatment of the problem formulation. The objective of this work is to address these two primary roadblocks and enable practitioners to efficiently perform design under uncertainty with limited knowledge of the UQ discipline. Methods outlined in this paper demonstrate MDO incorporating UQ into the design process, leveraging an analytic derivative tool chain through the entire optimization. The proposed approach leverages machine learning techniques to generate a differentiable confidence interval output from polynomial chaos models. This technique, coupled with the incorporation of analytical derivatives through the Polynomial Chaos Expansion (PCE) process, eliminates the need to estimate derivatives which are usually obtained from finite difference, complex step, or similar methods. Developing a differentiable confidence interval allows mixed uncertainty problems (both epistemic and aleatory) to be modeled. Without such modeling, these problems cannot accurately predict objective functions containing statistical quantities such as mean and variance. The addition of analytic derivatives to a polynomial chaos-based UQ method decreases the computational costs of performing design under uncertainty by orders of magnitude in comparison with methods such as complex step. The method and codes developed are modular in nature and are a drop-in solution for design under uncertainty within existing MDO problems. A low-fidelity analytical multidisciplinary optimization under uncertainty for a wing design in OpenMDAO is detailed in this paper. This demonstration case will include both objective functions and constraints which are influenced by uncertain parameters.

Ben Phillips↗
NASA NTRS2016

Space Launch System Vibration Analysis Support

The ultimate goal for my efforts during this internship was to help prepare for the Space Launch System (SLS) integrated modal test (IMT) with Rodney Rocha. In 2018, the Structural Engineering Loads and Dynamics Team will have 10 days to perform the IMT on the SLS Integrated Launch Vehicle. After that 10 day period, we will have about two months to analyze the test data and determine whether the integrated vehicle modes/frequencies are adequate for launching the vehicle. Because of the time constraints, NASA must have newly developed post-test analysis methods proven well and with technical confidence before testing. NASA civil servants along with help from rotational interns are working with novel techniques developed and applied external to Johnson Space Center (JSC) to uncover issues in applying this technique to much larger scales than ever before. We intend to use modal decoupling methods to separate the entangled vibrations coming from the SLS and its support structure during the IMT. This new approach is still under development. The primary goal of my internship was to learn the basics of structural dynamics and physical vibrations. I was able to accomplish this by working on two experimental test set ups, the Simple Beam and TAURUS-T, and by doing some light analytical and post-processing work. Within the Simple Beam project, my role involves changing the data acquisition system, reconfiguration of the test set up, transducer calibration, data collection, data file recovery, and post-processing analysis. Within the TAURUS-T project, my duties included cataloging and removing the 30+ triaxial accelerometers, coordinating the removal of the structure from the current rolling cart to a sturdy billet for further testing, preparing the accelerometers for remounting, accurately calibrating, mounting, and mapping of all accelerometer channels, and some testing. Hammer and shaker tests will be performed to easily visualize mode shapes at low frequencies. Short analytical projects using MATLAB were also assigned to aid in research efforts. These included integration of acceleration data for comparison to measured displacement data. Laplace and Fourier transforms were also investigated to determine viability as a method of modal decoupling. In addition to these projects, I was also able contribute work that would benefit future interns and the division as a whole. I gave a short presentation and answered questions to aid in the recruitment of subsequent interns and co-ops for the division. I also assisted in revisions and additions to Intern/Co-Op Handbook to provide incoming employees with background information on the organization they are about to work for. I further developed tutorial on Pulse software, which was used for data acquisition for both experiments and will be helpful to interns and engineers that may be unfamiliar to the software. I gained a diverse range of experience throughout my internship. I was introduced to advanced dynamics and analytical techniques. This was through new experience with both hands on experimentation and analytical post processing methods. I was exposed to the benefits of interdepartmental collaboration and developed stronger skills in time management by coordinating two different tests at once. This internship provided an excellent opportunity to see how engineering theories applied to real life scenarios, and an introduction to how NASA/JSC solves technical problems.

Johnson, Katie↗
NASA NTRS2006

A Rotating Plug Model of Friction Stir Welding Heat Transfer

A simplified rotating plug model is employed to study the heat transfer phenomena associated with the fiction stir welding process. An approximate analytical solution is obtained based on this idealized model and used both to demonstrate the qualitative influence of process parameters on predictions and to estimate temperatures produced in typical fiction stir welding situations.

Raghulapadu J. K.↗
NASA NTRS2026

NASA JSC’s Simulant Development Lab Capabilities and Artemis Testing

The Simulant Development Lab (SDL) is a multifunctional collaborative workspace that supports the development, curation, analysis, testing, and distribution of planetary regolith simulants – including lunar, Martian, asteroidal, and other granular materials. The lab provides a multidisciplinary setting for scientific characterization of simulant physical properties and for engineering evaluations conducted with simulant test beds. To enable this work, the SDL curates and maintains a stock of more than 35 metric tons of simulant material. To evaluate these materials and support testing goals, the lab is equipped with a comprehensive suite of processing tools and analytical instruments. These capabilities enable the SDL’s mission at NASA’s Johnson Space Center to distribute, develop, process, characterize, and test regolith simulants for mission relevant applications. Through controlled and repeatable testing environments that replicate the physical and compositional properties of lunar regolith, the SDL supports Artemis hardware maturation, providing safe, Earth‑based analogs for evaluating systems that must withstand regolith dust interactions, physical wear and abrasion, and operational loads. The facility’s extensive simulant inventory and integrated geological and engineering test infrastructure accelerate technology readiness for Artemis and future exploration campaigns (e.g., future crewed or robotic missions to Mars).

Simulant Development Lab↗
NASA NTRS1992

Uncertainty management by relaxation of conflicting constraints in production process scheduling

Mathematical-analytical methods as used in Operations Research approaches are often insufficient for scheduling problems. This is due to three reasons: the combinatorial complexity of the search space, conflicting objectives for production optimization, and the uncertainty in the production process. Knowledge-based techniques, especially approximate reasoning and constraint relaxation, are promising ways to overcome these problems. A case study from an industrial CIM environment, namely high-grade steel production, is presented to demonstrate how knowledge-based scheduling with the desired capabilities could work. By using fuzzy set theory, the applied knowledge representation technique covers the uncertainty inherent in the problem domain. Based on this knowledge representation, a classification of jobs according to their importance is defined which is then used for the straightforward generation of a schedule. A control strategy which comprises organizational, spatial, temporal, and chemical constraints is introduced. The strategy supports the dynamic relaxation of conflicting constraints in order to improve tentative schedules.

Dorn, Juergen↗
NASA NTRS1980

Methods for Monte Carlo simulation of the exospheres of the moon and Mercury

A general form of the integral equation of exospheric transport on moon-like bodies is derived in a form that permits arbitrary specification of time varying physical processes affecting atom creation and annihilation, atom-regolith collisions, adsorption and desorption, and nonplanetocentric acceleration. Because these processes usually defy analytic representation, the Monte Carlo method of solution of the transport equation, the only viable alternative, is described in detail, with separate discussions of the methods of specification of physical processes as probabalistic functions. Proof of the validity of the Monte Carlo exosphere simulation method is provided in the form of a comparison of analytic and Monte Carlo solutions to three classical, and analytically tractable, exosphere problems. One of the key phenomena in moonlike exosphere simulations, the distribution of velocities of the atoms leaving a regolith, depends mainly on the nature of collisions of free atoms with rocks. It is shown that on the moon and Mercury, elastic collisions of helium atoms with a Maxwellian distribution of vibrating, bound atoms produce a nearly Maxwellian distribution of helium velocities, despite the absence of speeds in excess of escape in the impinging helium velocity distribution.

Hodges, R. R., Jr.↗
NASA NTRS2025

Components Refurbishment and Chemical Analysis Facility, SWMU #041 - Per- and Polyfluoroalkyl Substances Site Assessment Report Kennedy Space Center, Florida

This PFAS Site Assessment (SA) Report presents the activities and results associated with PFAS investigations at the Components Refurbishment and Chemical Analysis (CRCA) facility located at Kennedy Space Center (KSC), Florida. In 2022, CRCA was identified as an Area of Potential Concern because the facility stores several potential PFAS-containing chemicals. A groundwater sample collected from an onsite monitoring well detected PFOA and PFOS at concentrations greater than State of Florida provisional Groundwater Cleanup Target Levels (pGCTLs). PFAS SA activities were conducted between March 2022 and February 2024. During this timeframe, a total of 16 direct-push technology (DPT) locations and 82 discrete samples were collected from these locations, along with 90 monitoring well samples. The analytical data screening process focused on State of Florida pGCTLs and United States Environmental Protection Agency (USEPA) Regional Screening Level (RSLs) from November 2023 to evaluate the data. Analytical results identified PFOS, PFOA, and PFBA at concentrations exceeding their respective RSLs at each depth interval (shallow, intermediate, and deep). PFOS and PFOA had the largest footprint of RSL exceedances in each depth interval, but pGCTL exceedances were only observed at limited locations in the shallow and intermediate intervals. PFBA had the highest detections of any PFAS compound, with concentrations exceeding 180,000 nanograms per liter (ng/L), which is 100-times the RSL of 1,800 ng/L in the shallow and intermediate intervals and 10-times the RSL in the deep interval. The maximum PFBA detection was 841,000 ng/L at shallow monitoring well, MW0006. The PFAS SA also included samples collected from the onsite hydraulic containment system (HCS) which was installed to control and treat the onsite chlorinated volatile organic compound (CVOC) plume. Influent and effluent aqueous samples were collected monthly from the system. PFAS concentrations were relatively the same for both influent and effluent samples, indicating that while the HCS has been effective for CVOC treatment, it does not provide any additional treatment for PFAS compounds. Since the HCS has achieved its objectives, the system was shut down in December 2024. PFAS data gaps still exist, to include surface water and soil, which were not sampled during this SA. Soil sampling near the Chemical Process Area is recommended. Surface water and soil sampling at select stormwater outfalls is also recommended. Additionally, further groundwater sampling is recommended (DPT and monitoring well) in all depth intervals to delineate the extent of PFAS impacts at CRCA.

K Alex Murphy↗