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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
DOE OSTI2022

Heavy Duty Natural Gas Single Cylinder Research Engine Installation, Commissioning, and Baseline Testing

Natural Gas (NG) Internal Combustion Engines (ICE) are a promising alternative to diesel engines for on-road heavy-duty applications to reduce greenhouse gas and harmful pollutant emissions. NG engines have not been widely adopted due to the lower thermal efficiency compared with diesel engine counterparts. To develop the base knowledge required to reach the desired efficiency, a Single Cylinder Engine (SCE) is the most effective platform to acquire reliable and repeatable data. A SCE test cell was developed using a Cummins 15-liter six-cylinder heavy-duty engine block modified to fire one cylinder (2.5-liter displacement). A Woodward Large Engine Control Module (LECM) is integrated to permit implementation of real-time advanced combustion control. Intake and exhaust characteristics, fuel composition, and exhaust gas recirculated substitution rate (EGR) are fully adjustable. A high-speed data acquisition system acquires in-cylinder, intake, and exhaust pressure for combustion analysis. The baseline testing shows reliable and consistent results for engine thermal efficiency, indicated mean effective pressure (IMEP), and coefficient of variance of the IMEP over a wide range of operating conditions while achieving effective control of all engine control and operation variables. This test cell will be used to conduct a research program to develop new and innovative control algorithms and CFD optimized combustion chamber designs, allowing ultra-high efficiency and low emissions for NG ICE heavy-duty on-road applications.

03 NATURAL GAS↗
DOE OSTI2026

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗
DOE OSTI2020

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. Here, we have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ~77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

System Risk Assessment and Allocation in Conceptual Design

As aerospace systems continue to evolve in addressing newer challenges in air and space transportation, there exists a heightened priority for significant improvement in system performance, cost effectiveness, reliability, and safety. Tools, which synthesize multidisciplinary integration, probabilistic analysis, and optimization, are needed to facilitate design decisions allowing trade-offs between cost and reliability. This study investigates tools for probabilistic analysis and probabilistic optimization in the multidisciplinary design of aerospace systems. A probabilistic optimization methodology is demonstrated for the low-fidelity design of a reusable launch vehicle at two levels, a global geometry design and a local tank design. Probabilistic analysis is performed on a high fidelity analysis of a Navy missile system. Furthermore, decoupling strategies are introduced to reduce the computational effort required for multidisciplinary systems with feedback coupling.

Mahadevan, Sankaran↗
DOE OSTI2022

Cell dark current–voltage from non-calibrated module electroluminescence image analysis

Here, we present a fast, accurate, and reliable method of obtaining cell dark current–voltage (I–V) curves from module electroluminescence (EL) images without requiring calibration or correction. For a pristine module, EL-derived dark I–V are compared to directly probed data for a variety of changing imaging parameters: camera sensor, lens, filter, aperture width, exposure time (level of sensor saturation), number of images used, and various combinations of these. Pristine modules and those experiencing different modes and degrees of degradation are examined. A recent study of modules using five different cell technologies demonstrates the practicality of our “EL sweep” technique for performance and degradation studies.

14 SOLAR ENERGY↗
DOE OSTI2024

Modulated Thermomechanical Analysis of Compression-Molded High-Density Polyethylene

Thermomechanical analysis (TMA) experiments conducted on high-density polyethylene (HDPE) show both reversible and irreversible dimensional changes. To further explore these reversible and irreversible processes, modulated thermomechanical analysis (MTMA) was used. Before reliable data on compression-molded HDPE was collected, a parameter optimization was performed to obtain a suitable MTMA method. Once a suitable method was obtained, several MTMA experiments were conducted on compression-molded HDPE. This work highlights the steps taken during the MTMA parameter optimization and the results obtained from MTMA experiments conducted on pristine compression-molded HDPE samples.

36 MATERIALS SCIENCE↗
DOE OSTI2024

R&D to Ensure a Scientific Basis for Qualification Tests and Standards (Final Report)

Project return on investment in a photovoltaic (PV) system depends increasingly on maintaining high energy yields, and the system lifetime is a major factor in levelized cost of electricity (LCOE). Thus, the rate of PV deployment and the success of these assets depends upon reliable long-term power generation. The overarching objective of this program is to improve photovoltaic (PV) module reliability via development of tests and standards. Where reliability problems or risk are discovered, we can design tests to ensure that these liabilities don't affect future generations of products. Customers can use these tests to understand which products are susceptible to certain degradation mechanisms, and manufacturers can use the tests to design unwanted characteristics out of their products. The work under this program identifies PV reliability needs, performs characterization that provides scientific understanding of targeted degradation mechanisms, and translates those data into practical and predictive test protocols and standards. Major accomplishments include: A model for polarization-type potential induced degradation (PID-p) was developed and validated against experimental data. NREL is currently leading a new edition of IEC 62804-1 for PID detection. PID-p can cause large losses in current and voltage for some module designs on cloudy days. Finite element modeling (FEM) and experiment was used to determine when cells crack in a module. It was shown that cells in landscape orientation are much more likely to crack than those on portrait orientation. Shortly thereafter, the first products with portrait-oriented cells were introduced. Studies of how to test for light and elevated temperature degradation (LeTID) culminated with the publication of IEC TS 63342. Software to predict the progression of LeTID was developed, validated, and made publicly available. Field validated tests and international standards for durability of PV module coatings abrasion, backsheets, and encapsulants were developed. Examples are IEC 62788-1-1, IEC 62788-2 ED2, IEC TS 62788-7-2, IEC 62788-7-3 ED1, IEC 63209-2. NREL led the development a high-temperature testing technical specification, and published guidelines that enable installers to determine whether higher-temperature testing is needed, simply based on location and mounting configuration. In a number of our case studies, variations in the bills of materials or workmanship have been associated with variations in reliability. These observations emphasize the importance of quality assurance to reliability. A framework for criticality (i.e. Pareto) analysis was developed and published. The framework helps us and other researchers determine what problems should be addressed for reliability research to have the biggest industry impact. NREL continues to participate actively in international standards development and stakeholder engagement activities, including organizing an annual PV Reliability Workshop. These activities are important for ensuring we address issues that are relevant and timely, and that we convey our results to those who may benefit.

14 SOLAR ENERGY↗
DOE OSTI2021

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗
NASA NTRS1998

Developments in Cylindrical Shell Stability Analysis

Today high-performance computing systems and new analytical and numerical techniques enable engineers to explore the use of advanced materials for shell design. This paper reviews some of the historical developments of shell buckling analysis and design. The paper concludes by identifying key research directions for reliable and robust methods development in shell stability analysis and design.

Knight, Norman F., Jr.↗
NASA NTRS2013

Modal Analysis with the Mobile Modal Testing Unit

Recently, National Aeronautics and Space Administration's (NASA's) White Sands Test Facility (WSTF) has tested rocket engines with high pulse frequencies. This has resulted in the use of some of WSTF's existing thrust stands, which were designed for static loading, in tests with large dynamic forces. In order to ensure that the thrust stands can withstand the dynamic loading of high pulse frequency engines while still accurately reporting the test data, their vibrational modes must be characterized. If it is found that they have vibrational modes with frequencies near the pulsing frequency of the test, then they must be modified to withstand the dynamic forces from the pulsing rocket engines. To make this determination the Mobile Modal Testing Unit (MMTU), a system capable of determining the resonant frequencies and mode shapes of a structure, was used on the test stands at WSTF. Once the resonant frequency has been determined for a test stand, it can be compared to the pulse frequency of a test engine to determine whether or not that stand can avoid resonance and reliably test that engine. After analysis of test stand 406 at White Sands Test Facility, it was determined that natural frequencies for the structure are located around 75, 125, and 240 Hz, and thus should be avoided during testing.

Wilder, Andrew J.↗
NASA NTRS1990

Computational analysis of flow in 3D propulsive transition ducts

A numerical analysis of fully three dimensional, statistically steady flows in propulsive transition ducts being considered for use in future aircraft of higher maneuverability is investigated. The purpose of the transition duct is to convert axisymmetric flow from conventional propulsion systems to that of a rectangular geometry of high aspect ratio. In an optimal design, the transition duct would be of minimal length in order to reduce the weight penalty, while the geometrical change would be gradual enough to avoid detrimental flow perturbations. Recent experiments conducted at the Propulsion Aerodynamics Branch have indicated that thrust losses in ducts of superelliptic cross-section can be surprisingly low, even if flow separation occurs near the divergent walls. In order to address the objective of developing a rational design procedure for optimal transition ducts, it is necessary to have available a reliable computational tool for the analysis of flows achieved in a sequence of configurations. Current CFD efforts involving complicated geometries usually must contend with two separate but interactive aspects: namely, grid generation and flow solution. The first two avenues of the present investigation were comprised of suitable grid generation for a class of transition ducts of superelliptic cross-section, and the subsequent application of the flow solver PAB3D to this geometry. The code, PAB3D, was developed as a comprehensive tool for the solution of both internal and external high speed flows. The third avenue of investigation has involved analytical formulations to aid in the understanding of the nature of duct flows, and also to provide a basis of comparison for subsequent numerical solutions. Numerical results to date include the generation of two preliminary grid systems for duct flows, and the initial application of PAB3D to the corresponding geometries, which are of the class tested experimentally.

Sepri, Paavo↗
DOE OSTI2023

Developing a Vorticity-Velocity-Based Off-Body Solver to Perform Multifidelity Simulations of Wind Farms

Wind power has become a key player in satisfying the global energy needs. With increased market penetration, unanticipated unsteady loading induced failures, installation related reductions in power generation, and significant maintenance costs have underscored the need to predict the unsteady fluid-structure interactions related to turbine layout and off-design wind conditions. Contemporary turbine design tools are incapable of accounting for such loadings. As a result, researchers have started utilizing high-Performance-Computing (HPC) based Computational Fluid Dynamics (CFD) solvers, such as the U.S. Department of Energy sponsored ExaWind software package, to investigate these phenomena. Unfortunately, such HPC tools are computationally expensive for routine industrial use, often because of the sheer number of cells required to resolve the wake flowfield. This paper describes a preliminary effort to address this issue by developing a vorticity-velocity based CFD off-body solver, VorTran-M2-AMReX, that integrates directly with DOE's ExaWind wind turbine analysis system to perform accurate and reliable simulations of wind turbine/farm at a lower computational cost than ExaWind alone. This article summarizes work undertaken to date concerning the assembly of the proposed analysis tool, and provides preliminary validation and verification of the VorTran-M2-AMReX off-body solver.

adaptive mesh refinement↗
DOE OSTI2018

Systematic search for tidal features around nearby galaxies: I. Enhanced SDSS imaging of the Local Volume

In hierarchical models of galaxy formation, stellar tidal streams are expected around most, if not all, galaxies. Although these features may provide useful diagnostics of the Λ CDM model, their observational properties remain poorly constrained because they are challenging to detect and interpret and have been studied in detail for only a sparse sampling of galaxy population. More quantitative, systematic approaches are required. We advocate statistical analysis of the counts and properties of such features in archival wide-field imaging surveys for a direct comparison against results from numerical simulations. We aim to study systematically the frequency of occurrence and other observational properties of tidal features around nearby galaxies. The sample we construct will act as a foundational dataset for statistical comparison with cosmological models of galaxy formation. Our approach is based on a visual classification of diffuse features around a volume-limited sample of nearby galaxies, using a post-processing of Sloan Digital Syk Survey (SDSS) imaging optimized for the detection of stellar structure with low surface brightness. At a limiting surface brightness of 28 mag arcsec –2 , 14% of the galaxies in our sample exhibit evidence of diffuse features likely to have arisen from minor merging events. Our technique recovers all previously known streams in our sample and yields a number of new candidates. Consistent with previous studies, coherent arc-like features and shells are the most common type of tidal structures found in this study. Here, we conclude that although some detections are ambiguous and could be corroborated or refuted with deeper imaging, our technique provides a reliable foundation for the statistical analysis of diffuse circumgalactic features in wide-area imaging surveys, and for the identification of targets for follow-up studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Structural Reliability Evaluation of Thermoelectric Generator Modules: Influence of End Conditions, Leg Geometry, Metallization, and Processing Temperatures

Structural reliability of thermoelectric generators (TEGs) in medium to high temperature applications still remains a challenge. Currently there are no established standards for evaluating the thermomechanical reliability of TEGs during new material and module development phases in the industry. In this work we implemented a procedure for evaluating the reliability of brittle TE materials based on the common practice in the ceramics industry. The probabilistic thermomechanical reliability of TEG couples and modules is evaluated using Weibull analysis. Finite element simulations were carried out to study the influence of TEG couple parameters such as element geometry, dimensions, spacing, metallization thickness, and processing conditions on the stresses, and the structural reliability evaluations are conducted based on the TE element stresses. We report results showed that the boundary conditions and processing temperatures have significant influence on the element and metallization stresses and overall device reliability. The external compressive load significantly enhanced structural reliability. Results also showed that among geometrical parameters the element length has a dominating influence on the element stresses compared to the leg cross-sectional shapes. The cross-section geometry of legs showed considerable effect at shorter lengths and the influence diminished with increased lengths. The proposed approach for evaluating the structural reliability could be integrated with performance optimization techniques for developing optimal and reliable TEG devices.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Artifact-Free Coring Procedures for Removing Samples from Photovoltaic Modules for Microscopic Analysis

An important step in producing more reliable and efficient photovoltaic modules is to establish a relationship between the microscopic properties of modules deployed in the field for many years and efficiency-related parameters. The first step in accomplishing this task is to be able to identify and remove small areas from these modules without causing any damage to these samples. In this work, we will describe two different procedures to core small areas of deployed and stressed solar panels produced with different materials (Si, CIGS, and CdTe), and we will prove that these processes did not damage the cored material. We will also show that the coring procedure changes for different types of photovoltaic modules.

14 SOLAR ENERGY↗
NASA NTRS2010

Reliability and Validity of Ultrasound Cross Sectional Area Measurements for Long-Duration Spaceflight

Limb muscle atrophy and the accompanying decline in function can adversely affect the performance of astronauts during mission-related activities and upon re-ambulation in a gravitational environment. Previous characterization of space flight-induced muscle atrophy has been performed using pre and post flight magnetic resonance imaging (MRI). In addition to being costly and time consuming, MRI is an impractical methodology for assessing in-flight changes in muscle size. Given the mobility of ultrasound (US) equipment, it may be more feasible to evaluate changes in muscle size using this technique. PURPOSE: To examine the reliability and validity of using a customized template to acquire panoramic ultrasound (US) images for determining quadriceps and gastrocnemius anatomical cross sectional area (CSA). METHODS: Vastus lateralis (VL), rectus femoris (RF), medial gastrocnemius (MG), and lateral gastrocnemius (LG) CSA were assessed in 10 healthy individuals (36+/-2 yrs) using US and MRI. Panoramic US images were acquired by 2 sonographers using a customized template placed on the thigh and calf and analyzed by the same 2 sonographers (CX50 Philips). MRI images of the leg were acquired while subjects were supine in a 1.5T scanner (Signa Horizon LX, General Electric) and were analyzed by 3 trained investigators. The average of the 2 US and 3 MRI values were used for validity analysis. RESULTS: High inter-experimenter reliability was found for both the US template and MRI analysis as coefficients of variation across muscles ranged from 2.4 to 4.1% and 2.8 to 3.8%, respectively. Significant correlations were found between US and MRI CSA measures (VL, r = 0.85; RF, r = 0.60; MG, r = 0.86; LG, r = 0.73; p < 0.05). Furthermore, the standard error of measurement between US and MRI ranged from 0.91 to 2.09 sq cm with high limits of agreement analyzed by Bland-Altman plots. However, there were significant differences between absolute values of MRI and US for all muscles. CONCLUSION: The present results indicate that utilizing a customized US template provides reliable measures of leg muscle CSA, and thus could be used to characterize changes in muscle CSA both in flight and on the ground.

Scott, Jessica M.↗
DOE OSTI2023

Spatiotemporal Variability of Electric System Reliability Metrics

As urbanization continues to grow, urban density also rises, placing significant stress on critical infrastructure. Cities often face challenges in investing in new infrastructure or upgrading existing ones. One area of infrastructure that has come under strain is the electric grid, leading to prolonged power outages. According to data from the U.S. Energy Information Administration, the average duration of power outages has steadily doubled from 2013 to 2021, primarily due to extreme weather events. The IEEE has developed a series of reliability metrics to assess the reliability of the electric system. However, these metrics are only applied at the utility level, making it challenging to comprehend the variations in these indices at finer spatial resolutions and, consequently, evaluate reliability at the non-utility level. In this study, we leveraged electric outage data collected at 15-minute intervals at the county level to estimate electric system reliability over a six-year period using a novel data analysis approach. Our findings reveal a gradual decline in reliability in the U.S. Southwest compared to national averages. Furthermore, the duration of outages per customer per event has significantly decreased in large portions of California and Florida. These discoveries can be valuable for utility companies as they seek to pinpoint regional anomalies and plan for prioritized remediation efforts.

Singh, Nagendra↗