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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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At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Fluid Mechanics Challenges in Direct-Ink-Writing Additive Manufacturing

Direct-ink writing (DIW) has rapidly become a versatile 3D fabrication method due to its ability to deposit a wide range of complex fluids into customizable 3D geometries. This review highlights key fundamental fluid mechanics and soft matter challenges across the different stages of the DIW printing process. The rheology of fluids and suspensions governs the flow behavior through narrow nozzles, posing questions about extrudability, confined flow dynamics, and clogging mechanisms. Downstream, the formation and deposition of extruded filaments involve extensional flows and potential instabilities, while postdeposition dynamics introduces complexities related to yield stress and structural stability. These stages are inherently interdependent, as optimizing material composition without considering filament stability risks compromising the final structure. As DIW applications expand through advanced ink formulations, developing fundamental fluid mechanics frameworks is essential to replace trial-and-error approaches with predictive design methodologies to enable more precise control and improved reliability of the printing process.

3D printing↗
DOE OSTI2021

Influence of Diffuse and Ground-Reflected Irradiance on the Spectral Modeling of Solar Reference Cells

Thermal Energy Storage (TES) is a key component for solar thermal applications to bridge the gap between the demand for thermal energy and the supply of solar energy, whose availability depends on the time of day and season. Thus, cost-effective packed-bed thermal containers filled with a solid storage medium have been proposed for high-temperature sensible heat storage as materials are abundant and relatively cheap. Thus, it is necessary to investigate their performance and temperature profiles during the charge-discharge cycle. Several models are available for this purpose. Typically, the more detailed a model, the greater the computational effort required to solve it, and hence a time-efficient model is needed to prevent excessively long computation times for long-term analysis. At the more basic level, the common Hughes E-NTU model and the less realistic simplified Infinite-NTU model are very important for their less time and computational effort. In this paper, the appropriateness of employing the Infinite-NTU model was evaluated to investigate the performance of a typical and scalable rock-bed TES as a case study. The results presented provide a methodology to quickly test the validity of the model and predict the temperature profile for the case under study. Accordingly, such simple charge-discharge cycle thermal performance predictions are important to plan, design, and rapidly deploy a reliable and economical solar thermal system for the supply of valuable heat to high-temperature demanding applications of power generation and industrial processes as part of a rapid shift towards non-polluting renewable energy. Keywords: Solar Thermal, TES, Packed-bed, NTU model, Temperature profile

PV modeling↗
DOE OSTI2021

High Efficiency OLED Light Engine

LED Specialists has accomplished the program objective in designing a high efficiency OLED light engine combining high-performance OLED panels in the 5W-8W range. We achieved our goal by using an Active-Clamp Flyback circuit topology using state-of-the-art electronics. Evaluation testing of our second-generation prototype PC board has demonstrated an efficiency rating of 93% and dimming capability between 100% and 5% of OLED brightness. A reliability analysis of the design shows it to have a predicted Mean Time Between Failures (MTBF) of approximately 1,000,000 hours.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Next-Level Energy Management in Manufacturing: Facility-Level Energy Digital Twin Framework Based on Machine Learning and Automated Data Collection

This research introduces an energy prediction framework at the facility level supported by automated data collection and machine learning models. It investigates whether reducing the prediction time scale allows for applying more complex machine learning techniques and if those techniques improve the prediction accuracy. The primary advantages of this framework lie in its automation of the energy prediction process and its provision of real-time energy data suitable for use in energy dashboards or digital twins. A sitewide dataset was created by combining 15 min energy and daily production data of five shops—assembly, battery, body (electric), body (gas), and paint—from a globally recognized electric vehicle manufacturer. Various machine learning models were evaluated on daily, weekly, and monthly datasets, including, in increasingly complex order: naïve, simple linear regression, net regularized generalized linear regression, principal component regression, k-nearest neighbor, random forest, and Bayesian regularized neural network. Compared to the current state-of-the-art energy consumption prediction for the industrial facility level, this research investigates more complex models and smaller time intervals for higher accuracy. The findings revealed that the more complex monthly models require a minimum of a year and a half of data to operate, while weekly models demand a year of data to achieve improved accuracy. Daily models can operate with only six months of data but exhibit poor performance due to reduced prediction accuracy of production. Key challenges identified include access to reliable, high-quality energy and production data and the initial demand for human labor.

digital twin↗
NASA NTRS1973

Demonstration of intercontinental DSN clock synchronization by VLBI

The prototype system for Deep Space Network clock synchronization by VLBI has been demonstrated to operate successfully over intercontinental baselines in a series of experiments between Deep Space Stations at Madrid, Spain, and Goldstone, California. As predicted by analysis and short baseline demonstration, the system achieves reliable synchronization between 26m and 64m antenna stations with 17 and 37K nominal system temperatures using under one million bits of data from each station. Semi-real-time operation is feasible since this small amount of data can be transmitted to JPL and processed within minutes. The system resolution is 50 to 400ns, depending on the amount of data processed and the source intensity. The accuracy is believed to be comparable to the resolution, although it could be independently confirmed to only about 5 microseconds using LORAN C.

Hurd, W. J.↗
NASA NTRS1997

A Comprehensive Reliability Methodology for Assessing Risk of Reusing Failed Hardware Without Corrective Actions with and Without Redundancy

This paper deals with the development of a reliability methodology to assess the consequences of using hardware, without failure analysis or corrective action, that has previously demonstrated that it did not perform per specification. The subject of this paper arose from the need to provide a detailed probabilistic analysis to calculate the change in probability of failures with respect to the base or non-failed hardware. The methodology used for the analysis is primarily based on principles of Monte Carlo simulation. The random variables in the analysis are: Maximum Time of Operation (MTO) and operation Time of each Unit (OTU) The failure of a unit is considered to happen if (OTU) is less than MTO for the Normal Operational Period (NOP) in which this unit is used. NOP as a whole uses a total of 4 units. Two cases are considered. in the first specialized scenario, the failure of any operation or system failure is considered to happen if any of the units used during the NOP fail. in the second specialized scenario, the failure of any operation or system failure is considered to happen only if any two of the units used during the MOP fail together. The probability of failure of the units and the system as a whole is determined for 3 kinds of systems - Perfect System, Imperfect System 1 and Imperfect System 2. in a Perfect System, the operation time of the failed unit is the same as that of the MTO. In an Imperfect System 1, the operation time of the failed unit is assumed as 1 percent of the MTO. In an Imperfect System 2, the operation time of the failed unit is assumed as zero. in addition, simulated operation time of failed units is assumed as 10 percent of the corresponding units before zero value. Monte Carlo simulation analysis is used for this study. Necessary software has been developed as part of this study to perform the reliability calculations. The results of the analysis showed that the predicted change in failure probability (P(sub F)) for the previously failed units is as high as 49 percent above the baseline (perfect system) for the worst case. The predicted change in system P(sub F) for the previously failed units is as high as 36% for single unit failure without any redundancy. For redundant systems, with dual unit failure, the predicted change in P(sub F) for the previously failed units is as high as 16%. These results will help management to make decisions regarding the consequences of using previously failed units without adequate failure analysis or corrective action.

Putcha, Chandra S.↗
NASA NTRS2001

Life Prediction Issues in Thermal/Environmental Barrier Coatings in Ceramic Matrix Composites

Issues and design requirements for the environmental barrier coating (EBC)/thermal barrier coating (TBC) life that are general and those specific to the NASA Ultra-Efficient Engine Technology (UEET) development program have been described. The current state and trend of the research, methods in vogue related to the failure analysis, and long-term behavior and life prediction of EBCITBC systems are reported. Also, the perceived failure mechanisms, variables, and related uncertainties governing the EBCITBC system life are summarized. A combined heat transfer and structural analysis approach based on the oxidation kinetics using the Arrhenius theory is proposed to develop a life prediction model for the EBC/TBC systems. Stochastic process-based reliability approach that includes the physical variables such as gas pressure, temperature, velocity, moisture content, crack density, oxygen content, etc., is suggested. Benefits of the reliability-based approach are also discussed in the report.

Shah, Ashwin R.↗
NASA NTRS2006

An Examination of Sunspot Number Rates of Growth and Decay in Relation to the Sunspot Cycle

On the basis of annual sunspot number averages, sunspot number rates of growth and decay are examined relative to both minimum and maximum amplitudes and the time of their occurrences using cycles 12 through present, the most reliably determined sunspot cycles. Indeed, strong correlations are found for predicting the minimum and maximum amplitudes and the time of their occurrences years in advance. As applied to predicting sunspot minimum for cycle 24, the next cycle, its minimum appears likely to occur in 2006, especially if it is a robust cycle similar in nature to cycles 17-23.

Wilson, Robert M.↗
NASA NTRS2008

Monitoring Damage Accumulation in Ceramic Matrix Composites Using Electrical Resistivity

The electric resistance of woven SiC fiber reinforced SiC matrix composites were measured under tensile loading conditions. The results show that the electrical resistance is closely related to damage and that real-time information about the damage state can be obtained through monitoring of the resistance. Such self-sensing capability provides the possibility of on-board/in-situ damage detection and accurate life prediction for high-temperature ceramic matrix composites. Woven silicon carbide fiber-reinforced silicon carbide (SiC/SiC) ceramic matrix composites (CMC) possess unique properties such as high thermal conductivity, excellent creep resistance, improved toughness, and good environmental stability (oxidation resistance), making them particularly suitable for hot structure applications. In specific, CMCs could be applied to hot section components of gas turbines [1], aerojet engines [2], thermal protection systems [3], and hot control surfaces [4]. The benefits of implementing these materials include reduced cooling air requirements, lower weight, simpler component design, longer service life, and higher thrust [5]. It has been identified in NASA High Speed Research (HSR) program that the SiC/SiC CMC has the most promise for high temperature, high oxidation applications [6]. One of the critical issues in the successful application of CMCs is on-board or insitu assessment of the damage state and an accurate prediction of the remaining service life of a particular component. This is of great concern, since most CMC components envisioned for aerospace applications will be exposed to harsh environments and play a key role in the vehicle s safety. On-line health monitoring can enable prediction of remaining life; thus resulting in improved safety and reliability of structural components. Monitoring can also allow for appropriate corrections to be made in real time, therefore leading to the prevention of catastrophic failures. Most conventional nondestructive evaluation (NDE) techniques such as ultrasonic C-scan, x-ray, thermography, and eddy current are limited since they require structural components of complex geometry to be taken out of service for a substantial length of time for post-damage inspection and assessment. Furthermore, the typical NDE techniques are useful for identifying large interlaminar flaws, but insensitive to CMC materials flaws developed perpendicular to the surface under tensile creep conditions. There are techniques such as piezoelectric sensor [7,8], and optical fiber [9,10] that could be used for on-line health monitoring of CMC structures. However, these systems involve attaching an external sensor or putting special fibers in CMC composites, which would be problematic at high temperature applications.

Smith, Craig E.↗
NASA NTRS2010

Agricultural Productivity Forecasts for Improved Drought Monitoring

Water stresses on agricultural crops during critical phases of crop phenology (such as grain filling) has higher impact on the eventual yield than at other times of crop growth. Therefore farmers are more concerned about water stresses in the context of crop phenology than the meteorological droughts. However the drought estimates currently produced do not account for the crop phenology. US Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) have developed a drought monitoring decision support tool: The U.S. Drought Monitor, which currently uses meteorological droughts to delineate and categorize drought severity. Output from the Drought Monitor is used by the States to make disaster declarations. More importantly, USDA uses the Drought Monitor to make estimates of crop yield to help the commodities market. Accurate estimation of corn yield is especially critical given the recent trend towards diversion of corn to produce ethanol. Ethanol is fast becoming a standard 10% ethanol additive to petroleum products, the largest traded commodity. Thus the impact of large-scale drought will have dramatic impact on the petroleum prices as well as on food prices. USDA's World Agricultural Outlook Board (WAOB) serves as a focal point for economic intelligence and the commodity outlook for U.S. WAOB depends on Drought Monitor and has emphatically stated that accurate and timely data are needed in operational agrometeorological services to generate reliable projections for agricultural decision makers. Thus, improvements in the prediction of drought will reflect in early and accurate assessment of crop yields, which in turn will improve commodity projections. We have developed a drought assessment tool, which accounts for the water stress in the context of crop phenology. The crop modeling component is done using various crop modules within Decision Support System for Agrotechnology Transfer (DSSAT). DSSAT is an agricultural crop simulation system, which integrates the effects of soil, crop phenotype, weather, and management options. It has been in use for more than 15 years by researchers, growers and has become a de-facto standard in crop modeling communities spanning over 100 countries. The meteorological forcings to DSSAT are provided by NASA s National Land Data Assimilation System (NLDAS) datasets. NLDAS is a framework that incorporates atmospheric forcing and land parameter values along with land surface models to diagnose and predict the state of the land surface.

Limaye, Ashutosh↗
NASA NTRS2010

Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

Ng, Hok K.↗
NASA NTRS2004

Displacement Damage Induced Catastrophic Second Breakdown in Silicon Carbide Schottky Power Diodes

A novel catastrophic breakdown mode in reversed biased Silicon carbide diodes has been seen for low LET particles. These particles are too low in LET to induce SEB, however SEB was seen from particles of higher LET. The low LET mechanism correlates with second breakdown in diodes due to increase leakage and assisted charge injection from incident particles. Percolation theory was used to predict some basic responses of the devices, but the inherent reliability issue with silicon carbide have proven challenging.

breakdown↗
NASA NTRS2013

Chandra Grating Spectroscopy of Three Hot White Dwarfs

High-resolution soft X-ray spectroscopic observations of single hot white dwarfs are scarce. With the Chandra Low-Energy Transmission Grating, we have observed two white dwarfs, one is of spectral type DA (LB1919) and the other is a non-DA of spectral type PG1159 (PG1520+525). The spectra of both stars are analyzed, together with an archival Chandra spectrum of another DA white dwarf (GD246). Aims. The soft X-ray spectra of the two DA white dwarfs are investigated in order to study the effect of gravitational settling and radiative levitation of metals in their photospheres. LB1919 is of interest because it has a significantly lower metallicity than DAs with otherwise similar atmospheric parameters. GD246 is the only white dwarf known that shows identifiable individual iron lines in the soft X-ray range. For the PG1159 star, a precise effective temperature determination is performed in order to confine the position of the blue edge of the GW Vir instability region in the HRD. Methods. The Chandra spectra are analyzed with chemically homogeneous as well as stratified NLTE model atmospheres that assume equilibrium between gravitational settling and radiative acceleration of chemical elements. Archival EUV and UV spectra obtained with EUVE, FUSE, and HST are utilized to support the analysis. Results. No metals could be identified in LB1919. All observations are compatible with a pure hydrogen atmosphere. This is in stark contrast to the vast majority of hot DA white dwarfs that exhibit light and heavy metals and to the stratified models that predict significant metal abundances in the atmosphere. For GD246 we find that neither stratified nor homogeneous models can fit the Chandra spectrum. The Chandra spectrum of PG1520+525 constrains the effective temperature to T(sub eff) = 150 000 +/- 10 000 K. Therefore, this nonpulsating star together with the pulsating prototype of the GWVir class (PG1159-035) defines the location of the blue edge of the GWVir instability region. The result is in accordance with predictions from nonadiabatic stellar pulsation models. Such models are therefore reliable tools to investigate the interior structure of GW Vir variables. Conclusions. Our soft X-ray study reveals that the understanding of metal abundances in hot DA white dwarf atmospheres is still incomplete. On the other hand, model atmospheres of hydrogen-deficient PG1159-type stars are reliable and reproduce well the observed spectra from soft X-ray to optical wavelengths.

Adamczak, J.↗
NASA NTRS2017

Getting NuSTAR on Target: Predicting Mast Motion

The Nuclear Spectroscopic Telescope Array (NuSTAR) is the first focusing high energy (3-79 keV) X-ray observatory operating for four years from low Earth orbit. The X-ray detector arrays are located on the spacecraft bus with the optics modules mounted on a flexible mast of 10.14m length. The motion of the telescope optical axis on the detectors during each observation is measured by a laser metrology system and matches the pre-launch predictions of the thermal flexing of the mast as the spacecraft enters and exits the Earths shadow each orbit. However, an additional motion of the telescope field of view was discovered during observatory commissioning that is associated with the spacecraft attitude control system and an additional flexing of the mast correlated with the Solar aspect angle for the observation. We present the methodology developed to predict where any particular target coordinate will fall on the NuSTAR detectors based on the Solar aspect angle at the scheduled time of an observation. This may be applicable to future observatories that employ optics deployed on extendable masts. The automation of the prediction system has greatly improved observatory operations efficiency and the reliability of observation planning.

NASA small explorer↗
NASA NTRS2019

MARGInS Model-Based Analysis of Realizable Goals in Systems

The high complexity of modern aircraft and spacecraft requires elaborate Verification and Validation (V&V) approaches to make sure that such complex systems work properly and reliably. MARGInS is a framework for the analysis, understanding, and prediction of the behavior of a complex, hybrid system. MARGInS contains a set of machine learning and statistical algorithms for multivariate clustering, treatment learning, critical factor determination, time-series analysis, event prediction, and safety-boundary detection and characterization. The framework supports system testing and can be configured to find novel features in test suites, determine classes of behavior, propose new experiments that can efficiently explore and characterize the boundaries between classes of system behavior, and to create visualizations and reports.

He, Yuning↗
DOE OSTI2015

Progress in the Investigation of Nuclear Power Plant Cable Aging

The thousands of miles of polymer-insulated cables used for power, control and communications in nuclear power plants were originally qualified for forty years of plant operation. Continued use of cable in existing plants for periods much beyond their original qualified life will require a detailed understanding of cable degradation under plant operating conditions to assess and mitigate risk of continued use. The effect and relative importance of individual and combined environmental stresses including radiation, heat and moisture on reliable cable performance is essential to inform condition monitoring, lifetime prediction and required cable replacement planning. We present an overview and update of the nuclear cable aging program at the Pacific Northwest National Laboratory and the Oak Ridge National Laboratory supported by the U.S. Department of Energy, Office of Nuclear Energy, Light Water Reactor Sustainability program

Fifield, Leonard S.↗
DOE OSTI2015

PROGRESS IN THE INVESTIGATION OF NUCLEAR POWER PLANT CABLE AGING

The thousands of miles of polymer-insulated cables used for power, control and communications in nuclear power plants were originally qualified for forty years of plant operation. Continued use of cable in existing plants for periods much beyond their original qualified life will require a detailed understanding of cable degradation under plant operating conditions to assess and mitigate risk of continued use. The effect and relative importance of individual and combined environmental stresses including radiation, heat and moisture on reliable cable performance is essential to inform condition monitoring, lifetime prediction and required cable replacement planning. We present an overview and update of the nuclear cable aging program at the Pacific Northwest National Laboratory and the Oak Ridge National Laboratory supported by the U.S. Department of Energy, Office of Nuclear Energy, Light Water Reactor Sustainability program.

cable, insulation, polymer, EPR, XLPE, aging, degr↗