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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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NASA NTRS1977

NASA 30,000 hour test demonstration of closed Brayton cycle reliability

Four Brayton rotating units (BRU) developed by an American company were tested in connection with studies concerning the feasibility to use closed Brayton power conversion systems for space applications. The rotating assembly operates at a speed of 36,000 rpm and consists of a radial outflow compressor, a four-pole Rice alternator/motor, and a radial inflow turbine. The cycle working fluid consists of a mixture of helium and xenon. After 20,000 hours of operation, there was no apparent wear on failure mode to prevent attainment of the 5-year BRU design life objective.

Mccormick, J. E.↗

NASA NTRS1980

A continuation of base-line studies for environmentally monitoring space transportation systems at John F. Kennedy Space Center. Volume 3, part 2: Ichthyological studies, sailfin molly reproduction study

The applicability of monitoring populations of Poccilia latipinna (sailfin molly) and its reproductive efforts as reliable indicators of environmental effects of aerospace activities in the Kennedy Space Center area was investigated. Results show that the sailfin molly experiences drastic fluctuations in population and reproductive success and is not an appropriate factor for monitoring to establish perturbations of the environment due to space transportation system related activities.

Snelson, F. F., Jr.↗

NASA NTRS2010

Probabilistic Simulation of Combined Thermo-Mechanical Cyclic Fatigue in Composites

A methodology to compute probabilistically-combined thermo-mechanical fatigue life of polymer matrix laminated composites has been developed and is demonstrated. Matrix degradation effects caused by long-term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress-dependent multifactor-interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability-integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/-45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical-cyclic loads and low thermal-cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical-cyclic loads and high thermal-cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

Chamis, Christos C.↗

NASA NTRS2011

Probabilistic Simulation of Combined Thermo-Mechanical Cyclic Fatigue in Composites

Chamis, Christos C.↗

NASA NTRS2017

Life Support Filtration System Trade Study for Deep Space Missions

The National Aeronautics and Space Administrations (NASA) technical developments for highly reliable life support systems aim to maximize the viability of long duration deep space missions. Among the life support system functions, airborne particulate matter filtration is a significant driver of launch mass because of the large geometry required to provide adequate filtration performance and because of the number of replacement filters needed to a sustain a mission. A trade analysis incorporating various launch, operational and maintenance parameters was conducted to investigate the trade-offs between the various particulate matter filtration configurations. In addition to typical launch parameters such as mass, volume and power, the amount of crew time dedicated to system maintenance becomes an increasingly crucial factor for long duration missions. The trade analysis evaluated these parameters for conventional particulate matter filtration technologies and a new multi-stage particulate matter filtration system under development by NASAs Glenn Research Center. The multi-stage filtration system features modular components that allow for physical configuration flexibility. Specifically, the filtration system components can be configured in distributed, centralized, and hybrid physical layouts that can result in considerable mass savings compared to conventional particulate matter filtration technologies. The trade analysis results are presented and implications for future transit and surface missions are discussed.

particulate matter filtration↗

NASA NTRS2009

Use of Raman Spectroscopy and Delta Volume Growth from Void Collapse to Assess Overwrap Stress Gradients Compromising the Reliability of Large Kevlar/Epoxy COPVs

Composite Overwrapped Pressure Vessels (COPVs) are frequently used for storing pressurized gases aboard spacecraft and aircraft when weight saving is desirable compared to all-metal versions. Failure mechanisms in fibrous COPVs and variability in lifetime can be very different from their metallic counterparts; in the former, catastrophic stress-rupture can occur with virtually no warning, whereas in latter, a leak before burst design philosophy can be implemented. Qualification and certification typically requires only one burst test on a production sample (possibly after several pressure cycles) and the vessel need only meet a design burst strength (the maximum operating pressure divided by a knockdown factor). Typically there is no requirement to assess variability in burst strength or lifetime, much less determine production and materials processing parameters important to control of such variability. Characterizing such variability and its source is crucial to models for calculating required reliability over a given lifetime (e.g. R = 0.9999 for 15 years). In this paper we present a case study of how lack of control of certain process parameters in COPV manufacturing can result in variations among vessels and between production runs that can greatly increase uncertainty and reduce reliability. The vessels considered are 40-inch ( NASA Glenn Research center, Cleveland, OH, 44135 29,500 in3 ) spherical COPVs with a 0.74 in. thick Kevlar49/epoxy overwrap and with a titanium liner of which 34 were originally produced. Two burst tests were eventually performed that unexpectedly differed by almost 5%, and were 10% lower than anticipated from burst tests on 26-inch sister vessels similar in every detail. A major observation from measurements made during proof testing (autofrettage) of the 40-inch vessels was that permanent volume growth from liner yielding varied by a factor of more than two (150 in3 to 360 in3 ), which suggests large differences in the residual stress gradient through their overwraps. This resulted in large uncertainty in true fiber stress ratio (fiber stress at operating pressure divided by fiber stress at burst) which governs lifetime. The vessels were originally designed with tight safety margins, so it became crucial to develop a non-destructive evaluation (NDE) technique to directly measure the overwrap residual stress state of each vessel, and to identify those vessels at highest risk of having poor reliability. This paper describes a Raman Spectroscopy technique for measuring certain patterns of fluctuation in fiber elastic strains over the outside vessel surface (where all but one wrap is exposed at certain locations) that are shown to directly correlate to increased fiber stress ratios and reduced reliability.

Kezirian, Michael T.↗

DOE OSTI2024

Interleaved Cuk Converter Wave Energy System With Advanced Control and Grid Support Functions for Seamless Integration: Preprint

This paper presents an innovative wave energy conversion system employing an interleaved Cuk converter and advanced nonlinear control for seamless integration with the grid. The proposed system utilizes the interleaved Cuk converter for efficient power extraction on the DC side, while an inverter facilitates power transfer to the grid or load on the AC side. A sophisticated nonlinear control architecture based on Lyapunov energy functions ensures stable and optimal operation under varying wave conditions. Case study results demonstrate the effectiveness of the proposed system, highlighting its ability to efficiently harness wave energy and seamlessly integrate with the grid, thus paving the way for sustainable and reliable renewable energy generation. The overall system is verified via computer simulations based on MATLAB/Simulink and various case study results are presented.

HYDRO ENERGY,TIDAL AND WAVE POWER↗

DOE OSTI2024

RuBisCO activity assays: a simplified biochemical redox approach for in vitro quantification and an RNA sensor approach for in vivo monitoring

Abstract Background Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is the most abundant soluble protein in nature. Extensive studies have been conducted for improving its activity in photosynthesis through approaches like protein engineering. Concurrently, multiple biochemical and radiolabeling assays have been developed for determining its activity. Although these existing assays yield reliable results, they require addition of multiple external components, rendering them less convenient and expensive. Therefore, in this study, we have developed two relatively cheaper, convenient, and easily reproducible assays for quantitative and qualitative estimation of RuBisCO activity. Results We simplified a contemporary NADH based spectrophotometric RuBisCO assay by using cyanobacterial cell lysate as the source for Calvin cycle enzymes. We analyzed the influence of inorganic carbon substrates, CO 2 and NaHCO 3 , and varying protein concentrations on RuBisCO activity. Ribulose-1,5-bisphosphate (RuBP) consumption rates for the cultures grown under 5% CO 2 were 5–7 times higher than the ones grown with 20 mM NaHCO 3 , at different protein concentrations. The difference could be due to the impaired activity of carbonic anhydrase in the cell lysate, which is required for the conversion of HCO 3 − to CO 2 . The highest RuBisCO activity of 2.13 nmol of NAD + / µg of Chl-a/ min was observed with 50 µg of protein and 5% CO 2 . Additionally, we developed a novel RNA-sensor based fluorescence assay that is based on the principle of tracking the kinetics of ATP hydrolysis to ADP during the conversion of 3-phosphoglycerate (3-PG) to 1,3-bisphosphoglycerate (1,3-BPG) in the Calvin cycle. Under in vitro conditions, the fluorometric assay exhibited ~ 3.4-fold slower reaction rate (0.37 min −1 ) than the biochemical assay when using 5% CO 2 . We also confirmed the in vivo application of this assay, where increase in the fluorescence was observed with the recombinant strain of Synechocystis sp. PCC 6803 (SSL142) expressing the ADP-specific RNA sensor, compared to the WT. In addition, SSL142 exhibited three-fold higher fluorescence when supplemented with 20 mM NaHCO 3 as compared to the cells that were grown without NaHCO 3 supplementation. Conclusions Overall, we have developed a simplified biochemical assay for monitoring RuBisCO activity and demonstrated that it can provide reliable results as compared to the prior literature. Furthermore, the biochemical assay using 5% CO 2 (100% relative activity) provided faster RuBP consumption rate compared to the biochemical assay utilizing 20 mM NaHCO 3 (30.70% relative activity) and the in vitro fluorometric assay using 5% CO 2 (29.64% relative activity). Therefore, the absorbance-based biochemical assay using 5% CO 2 or higher would be suitable for in vitro quantification of the RuBisCO activity. On the other hand, the RNA-sensor based in vivo fluorometric assay can be applied for qualitative analysis and be used for high-throughput screening of RuBisCO variants. As RuBisCO is an enzyme shared amongst all the photoautotrophs, the assays developed in this study can easily be extended for analyzing the RuBisCO activities even in microalgae and higher plants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Evaluation of smart charging for electric vehicle-to-building integration: A case study

Higher electric vehicle (EV) adoption will stress the importance of demand flexibility to achieve more economic, efficient, and reliable grid operation. Charging technologies will be paramount in shifting temporally to better fit the variable generation of wind and solar. As such, analysis is warranted on the benefits of EV charge scheduling with respect to installation cost, operation cost, difficulty of implementation, and grid flexibility. We tackle this by analyzing the cost savings of implementing an EV charge scheduling infrastructure to reduce demand charges and installation costs. In this paper, we analyze a case study for operation of 16 level 2 chargers and 1 fast charger for two different building types. We then evaluate various test phases for controlling building and charging loads using an adaptive charging network (ACN) algorithm to characterize the ACN’s potential to reduce overall project cost.

30 DIRECT ENERGY CONVERSION↗

NASA NTRS2008

Unmanned Aircraft System Control and ATC Communications Bandwidth Requirements

There are significant activities taking place to establish the procedures and requirements for safe and routine operation of unmanned aircraft systems (UAS) in the National Airspace System (NAS). Among the barriers to overcome in achieving this goal is the lack of sufficient frequency spectrum necessary for the UAS control and air traffic control (ATC) communications links. This shortcoming is compounded by the fact that the UAS control communications links will likely be required to operate in protected frequency spectrum, just as ATC communications links are, because they relate to "safety and regularity of flight." To support future International Telecommunications Union (ITU) World Radio Conference (WRC) agenda items concerning new frequency allocations for UAS communications links, and to augment the Future Communications Study (FCS) Technology Evaluation Group efforts, NASA Glenn Research Center has sponsored a task to estimate the UAS control and ATC communications bandwidth requirements for safe, reliable, and routine operation of UAS in the NAS. This report describes the process and results of that task. The study focused on long-term bandwidth requirements for UAS approximately through 2030.

Henriksen, Steve↗

DOE OSTI2023

A Bootstrap Approach to Quantifying Reliabilities and Uncertainties of Complex Systems

While much work has been done in analyzing margins and uncertainties at the component level, a gap exists in NNSA methodology relating component level reliabilities and uncertainties to system level reliability and uncertainty. This paper shows how component level reliability data can be combined via a bootstrap analysis to estimate system level reliabilities and uncertainties. The performance of the bootstrap for this problem is validated through simulation studies. This paper extends the original work of Crowder by including sensitivity analyses related to changes in samples sizes and component failure probabilities. The use of the bootstrap as a decision-making tool is thus developed by quantifying the effect of such changes on system reliability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Optimal Energy Storage System and Smart Switch Placement in Dynamic Microgrids With Applications to Marine Energy Integration

Here this paper studies a dynamic microgrid (DMG) planning problem that places energy storage systems (ESSs) and smart switches (SSWs) optimally in the system. We apply the proposed methodology to applications concerning marine renewable energy (MRE). MRE is an emerging clean energy resource with enormous capacity but volatile and intermittent energy output profiles. Innovative grid-integration technologies designed to enhance the reliability of an MRE-integrated system are needed. However, there are still limited studies in this regard. Existing works have shown the promising prospect of using a dynamic microgrid (DMG) operational concept to accommodate renewable resources in distribution systems, but they usually assume fixed ESS and SSW installations. To further improve the operational flexibility of DMGs, we propose a DMG planning methodology that optimally places ESSs and SSWs so that a DMG with MRE is warranted with proper resource adequacy and topological flexibility in both the contingency and normal operations. We use realistic case studies based on a real-world distribution network and the U.S. Department of Energy's MRE dataset to verify the value and validity of the proposed work.

25 ENERGY STORAGE↗

NASA NTRS2017

Full-Coverage High-Resolution Daily PM(sub 2.5) Estimation using MAIAC AOD in the Yangtze River Delta of China

Satellite aerosol optical depth (AOD) has been used to assess population exposure to fine particulate matter (PM (sub 2.5)). The emerging high-resolution satellite aerosol product, Multi-Angle Implementation of Atmospheric Correction(MAIAC), provides a valuable opportunity to characterize local-scale PM(sub 2.5) at 1-km resolution. However, non-random missing AOD due to cloud snow cover or high surface reflectance makes this task challenging. Previous studies filled the data gap by spatially interpolating neighboring PM(sub 2.5) measurements or predictions. This strategy ignored the effect of cloud cover on aerosol loadings and has been shown to exhibit poor performance when monitoring stations are sparse or when there is seasonal large-scale missngness. Using the Yangtze River Delta of China as an example, we present a Multiple Imputation (MI) method that combines the MAIAC high-resolution satellite retrievals with chemical transport model (CTM) simulations to fill missing AOD. A two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM(sub 2.5) concentrations in 2013 and 2014 at 1 km resolution with complete coverage in space and time. The daily MI models have an average R(exp 2) of 0.77, with an inter-quartile range of 0.71 to 0.82 across days. The overall Ml model 10-fold cross-validation R(exp 2) (root mean square error) were 0.81 (25 gm(exp 3)) and 0.73 (18 gm(exp 3)) for year 2013 and 2014, respectively. Predictions with only observational AOD or only imputed AOD showed similar accuracy.Comparing with previous gap-filling methods, our MI method presented in this study performed bette rwith higher coverage, higher accuracy, and the ability to fill missing PM(sub 2.5) predictions without ground PM(sub 2.5) measurements. This method can provide reliable PM(sub 2.5)predictions with complete coverage that can reduce biasin exposure assessment in air pollution and health studies.

PM2.5↗

NASA NTRS1985

The impact of the FGGE observing systems in the Southern Hemisphere

Results of studies carried out at the Australian Numerical Meteorology Research Centre (ANMRC) and the Australian Bureau of Meteorology to assess the impact of FGGE on numerical weather prediction in the Southern Hemisphere are presented. These studies inducate that the FGGE data base had a significant impact on analysis and numerical weather prediction. From the operational standpoint, the most outstanding contribution was made by the drifting buoy data that enabled reliable routine surface pressure analyses to be made over the entire hemisphere. The results of a limited study using the MNMRC data assimilation scheme show that the quality of prediction to 48 hours hinges crucially on both the buoy pressure data and satellite temperature soundings with single level satellite winds having a small impact.

Puri, K.↗

NASA NTRS1991

Rendezvous strategy impacts on CTV avionics design, system reliability requirements, and available collision avoidance maneuvers

Rockwell International is conducting an ongoing program to develop avionics architectures that provide high intrinsic value while meeting all mission objectives. Studies are being conducted to determine alternative configurations that have low life-cycle cost and minimum development risk, and that minimize launch delays while providing the reliability level to assure a successful mission. This effort is based on four decades of providing ballistic missile avionics to the United States Air Force and has focused on the requirements of the NASA Cargo Transfer Vehicle (CTV) program in 1991. During the development of architectural concepts it became apparent that rendezvous strategy issues have an impact on the architecture of the avionics system. This is in addition to the expected impact on propulsion and electrical power duration, flight profiles, and trajectory during approach.

Donovan, William J.↗

NASA NTRS1998

High-Performance Monitoring Architecture for Large-Scale Distributed Systems Using Event Filtering

Monitoring is an essential process to observe and improve the reliability and the performance of large-scale distributed (LSD) systems. In an LSD environment, a large number of events is generated by the system components during its execution or interaction with external objects (e.g. users or processes). Monitoring such events is necessary for observing the run-time behavior of LSD systems and providing status information required for debugging, tuning and managing such applications. However, correlated events are generated concurrently and could be distributed in various locations in the applications environment which complicates the management decisions process and thereby makes monitoring LSD systems an intricate task. We propose a scalable high-performance monitoring architecture for LSD systems to detect and classify interesting local and global events and disseminate the monitoring information to the corresponding end- points management applications such as debugging and reactive control tools to improve the application performance and reliability. A large volume of events may be generated due to the extensive demands of the monitoring applications and the high interaction of LSD systems. The monitoring architecture employs a high-performance event filtering mechanism to efficiently process the large volume of event traffic generated by LSD systems and minimize the intrusiveness of the monitoring process by reducing the event traffic flow in the system and distributing the monitoring computation. Our architecture also supports dynamic and flexible reconfiguration of the monitoring mechanism via its Instrumentation and subscription components. As a case study, we show how our monitoring architecture can be utilized to improve the reliability and the performance of the Interactive Remote Instruction (IRI) system which is a large-scale distributed system for collaborative distance learning. The filtering mechanism represents an Intrinsic component integrated with the monitoring architecture to reduce the volume of event traffic flow in the system, and thereby reduce the intrusiveness of the monitoring process. We are developing an event filtering architecture to efficiently process the large volume of event traffic generated by LSD systems (such as distributed interactive applications). This filtering architecture is used to monitor collaborative distance learning application for obtaining debugging and feedback information. Our architecture supports the dynamic (re)configuration and optimization of event filters in large-scale distributed systems. Our work represents a major contribution by (1) survey and evaluating existing event filtering mechanisms In supporting monitoring LSD systems and (2) devising an integrated scalable high- performance architecture of event filtering that spans several kev application domains, presenting techniques to improve the functionality, performance and scalability. This paper describes the primary characteristics and challenges of developing high-performance event filtering for monitoring LSD systems. We survey existing event filtering mechanisms and explain key characteristics for each technique. In addition, we discuss limitations with existing event filtering mechanisms and outline how our architecture will improve key aspects of event filtering.

Maly, K.↗

DOE OSTI2024

Graph neural networks for CO 2 solubility predictions in Deep Eutectic Solvents

Deep Eutectic Solvents (DESs) are a promising class of solvents for CO 2 capture. DESs are complex mixtures that can be designed to optimize CO solubility and overall capture process efficiency. However, the vast design landscape of DES mixtures makes experimental investigation prohibitive; as such, there is a need for computational models that can quickly and efficiently navigate the design space and inform data collection efforts. In this work, we propose Graph Neural Network (GNN) models for predicting CO 2 solubility for DESs; the GNN leverages a mixture graph representation that captures the molecular structure of the DES components as well as their intermolecular interactions. Here, we compare the GNN framework against alternative architectures (neural networks, graph convolution networks, and random forests) and data representations (molecular fingerprints, sigma profiles, and graphs). We show that the proposed approach offers superior predictive performance; specifically, we show that solubility can be predicted reliably directly from molecular structure (without the need of using sigma profiles as proposed in previous studies). This result is important, as obtaining sigma profiles requires expensive density functional theory computations. We also explored the ability of GNNs to predict solubility for new DES mixtures and operating conditions. We found that the model extrapolates across temperature reliably. However, we also found deficiencies in the ability of the model to predict solubility for DES mixtures, pressures, and molar ratio not included in the training sets; we show that this is due to an inherent lack of chemical diversity in datasets available in the literature. The proposed computational capabilities can thus help navigate the design space of DES and inform data collection efforts. Our models, data, and benchmarks are shared as Python code implemented in Jupyter notebooks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Reliability and Resiliency in South Asia's Power Sector - Pathways for Research, Modeling, and Implementation

Reliability and resilience are the core principles of power system planning and operations around the world. Power systems in South Asia are transforming with increasing penetration of clean energy generation resources, emerging technologies, increasing electricity demand and electrification. At the same time, these power systems are facing challenges posed by extreme weather events and climate change. All these factors would add furthermore importance to the reliability and resilience of future power systems in South Asia. This has motivated us to better understand the country specific challenges and chalk out the pathways for research, modelling and implementation in South Asia. Our research, experience in the region and feedback from key stakeholders indicate following as the key areas where more work is needed to improve reliability and resilience of power systems in the region: Renewable energy Data for power system studies, New Tools and Studies, Resilience Planning, Resource Adequacy, Advanced RE Forecasting, Cybersecurity, Load Forecasting, and Coordinated Planning and Operations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗