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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evolution of AISI 304L stainless steel part properties due to powder recycling in laser powder-bed fusion

Selective laser melting (SLM) is a powder-bed fusion process in Additive Manufacturing (AM) that uses a laser beam to selectively fuse layers of powder into near net-shape components with little porosity. However, inconsistencies in the part properties due to the presence of defects in as-built components has hindered the widespread adoption of SLM for industrial applications forcing researchers to study the sources of variation for quality control purposes. A critical area suspected of creating variation in the part properties is the feedstock, where batch-to-batch differences as well as changes in the powder properties with reuse have the potential to affect performance. During processing, laser spatter and condensate eject from the melt pool and deposit into the powder-bed surrounding the parts. These particulates, more commonly known as ejecta, differ morphologically and chemically from the virgin powder compromising its reusability. In this study, 304L stainless steel powder was recycled for a total of 5 times through a systematic approach aimed at accelerating powder degradation to reveal the influence on both the tensile and impact toughness properties. Through analysis of variance (ANOVA), it was found that tensile properties did not change with reuse, while the impact toughness showed a steady decline illustrating the differences in static and dynamic part properties due to powder recycling.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Variation in the stratospheric aerosol associated with the North Cyclonic Polar Vortex as measured by the SAM II satellite sensor

Optical depth data gathered by the stratospheric aerosol measurement (SAM II) satellite during the 1979-80 winter season are analyzed to study mean atmospheric motions. The spacecraft photometer yielded extinction rates over the Northern Hemisphere in the 8-30 km altitude interval. Filtering was performed to remove the effects of high clouds and polar stratospheric clouds. Free horizontal mixing was prevalent below 14 km, as was a systematic difference across the polar jet stream above that altitude. The aerosol declined in altitude as the winter progressed. The polar vortex is concluded to have a base at the 14 km altitude and an outer boundary which coincides with the jet stream axis. The model accords with atmospheric tracer measurements made during the open-air nuclear testing programs in the 1950s.

Kent, G. S.↗
DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches

Abstract Wind power production is driven by, and varies with, the stochastic yet uncontrollable wind and environmental inputs. To compare a wind turbine's performance, a direct comparison on power outputs is always confounded by the stochastic effect of weather inputs. It is therefore crucial to control for the weather and environmental influence. Toward that objective, our study proposes an energy decomposition approach. We start with comparing the change in the total energy production and refer to the change in total energy as delta energy. On this delta energy, we apply our decomposition method, which is to separate the portion of energy change due to weather effects from that due to the turbine itself. We derive a set of mathematical relationships allowing us to perform this decomposition and examine the credibility and robustness of the proposed decomposition approach through extensive cross‐validation and case studies. We then apply the decomposition approach to Supervisory Control and Data Acquisition data associated with several wind turbines to which leading‐edge protection was carried out. Our study shows that the leading‐edge protection applied on blades may cause a small decline to the power production efficiency in the short term, although we expect the leading‐edge protection to benefit the blade's reliability in the long term.

17 WIND ENERGY↗
DOE OSTI2024

Polarization Type Potential Induced Degradation under Positive Bias in a Commercial PERC Module: Preprint

Potential induced degradation of the polarization type (PID-p) can reduce module performance in a relatively short period of time. PID-p can occur at both voltage polarities, but most studies are focused on degradation under a negative bias. This paper uses commercial bifacial passivated emitter and rear contact (PERC) cells within a monofacial glass-backsheet module construction to evaluate the impact of PID-p under a positive bias on the front side. Using the aluminum-foil (Al-foil) method, the module was stressed for PID in an environmental chamber. After the stress, the maximum power (Pmax) showed a decline of 3.1% at 1000 W/m2 and 6.2% at 200 W/m2. Recovery under light was also investigated. Complete recovery was observed at high irradiance, while a partial recovery was seen at lower irradiance. The outcomes of this study can help in understanding PID-p degradation under a positive bias and its recovery under the light.

PERC↗
DOE OSTI2021

Conducting thermal energy to the membrane/water interface for the enhanced desalination of hypersaline brines using membrane distillation

Membrane distillation (MD) is a membrane-based thermal desalination process capable of treating hypersaline brines. Standard MD systems rely on preheating the feed to drive the desalination process. However, relying on the feed to carry thermal energy is limited by a decline of the thermal driving force as the water moves across the membrane, and temperature polarization. In contrast, supplying heat directly into the feed channel, either through the membrane or other channel surfaces, has the potential of minimizing temperature polarization, increasing single-pass water recoveries, and decreasing the number of heat exchangers in the system. When solar thermal energy can be utilized, particularly if the solar heat is optimally delivered to enhance water evaporation and process performance, MD processes can potentially be improved in terms of energy efficiency, environmental sustainability, or operating costs. Here we describe an MD process using layered composite membranes that include a high-thermal-conductivity layer for supplying heat directly to the membrane-water interface and the flow channel. Here, the MD system showed stable performance with water flux up to 9 L/m 2 /hr, and salt rejection >99.9% over hours of desalinating hypersaline feed (100 g/L NaCl). In addition to bench-scale system, we developed a computational fluid dynamics model that successfully described the transport phenomena in the system.

42 ENGINEERING↗
DOE OSTI2024

Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses

Abstract Lateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Effect of surfactants and temperature on the hyperfiltration performance of poly(ether/urea) membranes

The individual and combined effects of pasteurization temperature (347 K) and surfactants (anionic, cationic, and neutral) on a poly(ether/urea) thin-film hyperfiltration membrane were studied. Performance of this positively charged membrane was measured in terms of sodium chloride rejection and water flux. The observed effect was mostly on water flux and minimal on salt rejection. Pasteurization temperature caused an irreversible flux decline (flux decline slope of 0.09). The gradual flux reduction caused by neutral and cationic surfactants was reversible, whereas the flux reduction caused by anionic surfactant was irreversible and of similar magnitude to flux reduction caused by pasteurization temperature. The effects of anionic surfactant and pasteurization temperature were additive. Because of flux decline at elevated temperatures the poly(ether/urea) membrane is not very attractive for long-term spaceflight use.

Leban, M. I.↗
NASA NTRS2004

The Star Formation History of Orion and its Environs

During this period of performance, we have obtained the following observations and carried out the analysis of the Orion associations itemized below. 1. Quest Optical Photometry: The photometric survey carries out with the Quest camera is finished. The strips at declinations +1 degree and -1 degree have already been processed. Photometry for a total of around 400,000 stars was obtained in these two strips with the Quest camera pipeline. Around 24,000 variables were picked out of this total by our variability software. Of these, around 2,500 stars fall above the main sequence and so were picked as candidates for spectroscopic follow-up. 2. Slit spectroscopy of bright candidates: Spectra for some 800 candidate PMS stars were obtained with the FAST spectrograph at the SAO 1.5m telescope in Mt. Hopkins. The spectra are being analyzed; 300 stars have been confirmed as young. 3. Multifiber spectroscopy: The first test of the multifiber spectrograph Hectoechelle were carried out in December 2003. One field of the Orion Nebula Cluster was observed with Hectochelle at three wavelength settings. A total of 157 spectra were obtained. Of these, 63 stars have been confirmed as Classical T Tauri stars, and 36 additional stars need further follow up. A paper is in preparation. 4. UBVRI photometry: We were granted time with the 4-shooter CCD Mosaic Camera at the SAO 1.2m telescope, to obtain UBVRI photometry of a subset of 53 newly identified T Tauri stars in the strips centered at DEC=-1 and +l. This sample is composed of strong Halpha emitting PMS stars (Classical T Tauri stars) located mostly in the Orion OB l b association, around the Orion Belt area. We have estimated mass accretion rates for 22 for these stars using the U photometry and the calibration of Gullbring et al. (1998), and found it to be similar to that of young stars in associations of similar age. 5. Near and mid-IR photometry: During the winter of 2003, we used the IR Camera on the SAO 1.2m telescope, to obtain L- band photometry of a set of the newly identified Orion OB l a and l b stars, in order to look for IR excess emission coming from the hotter inner parts of circumstellar disks. These data is being combined with the GEMINI/OSCIR 10 micron photometry obtained during 2002 and the mass accretion rates to determine the properties of disks in Ori lb. A paper is presently on preparation.

Calvet, Nuria↗
DOE OSTI2023

A multiscale recurrent neural network model for predicting energy production from geothermal reservoirs

Optimization of energy production from geothermal reservoirs requires reliable prediction of energy production performance under alternative operation and development scenarios. Traditionally, reservoir simulation models are used for the evaluation and screening of alternative production and development plans. However, simulation models require extensive data collection and modeling efforts and are time-consuming to build, run, and update. Data-driven predictive models, on the other hand, can serve as efficient prediction tools that can be used for decision support and management of daily operations and surveillance activities. Data-driven models become particularly attractive when a reservoir simulation model for a field does not exist and/or is difficult to build. Machine learning (ML)-based data-driven models that have recently become popular in several fields exploit statistical patterns and relations in training data to generate predictions. As such, they tend to perform better in interpolation problems (that is, prediction within the training data range) than when they are used to extrapolate beyond the training data. Production data from geothermal reservoirs tend to exhibit short-term variabilities as well as long-term trends, such as monotonically declining production temperatures. Capturing both short-term features and long-term trends with ML-based models is not trivial. We evaluate the use of recurrent neural networks (RNN) for the prediction of energy production from geothermal reservoirs. RNN is a class of ML architectures that are used to represent and predict sequential/dynamic data. Thus, it can be challenging to apply RNN to problems where long-term trends must be captured and extrapolation beyond the training data range is needed. We introduce the multiscale RNN architecture to extend the application of RNN to detect and predict both short-term variabilities and long-term trends in geothermal data. The developed architecture consists of a long-term component to only capture low-frequency data patterns, and a short-term component to detect features with higher frequency and more nonlinearity. The final prediction is obtained by combining the long-term and short-term predictions. Both synthetic and field data are used to evaluate the presented multiscale RNN model. The prediction performance of the multiscale RNN is compared against those obtained from the regular RNN and the autoregressive (AR) model. The results suggest that the multiscale architecture improves the long-term prediction performance of the regular RNN and enhances its robustness against noise.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Integrated Controls Package for High Performance Interior Retrofit [Slides]

For the last few years, networked lighting control (NLCs) have promised significant energy savings beyond what is achieved through a basic light-emitting diode (LED) lighting retrofit. At the same time, NLCs can substantially increase the cost and complexity of the lighting retrofit. And as lighting system wattage declines because of the increasing efficiency of LEDs, advanced controls have less lighting energy to save and the cost-effectiveness of the NLC investment decreases. But NLCs can be leveraged to achieve significant energy savings and value by enhancing control of other building systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Pharmacokinetics, Metabolite Measurement, and Biomarker Identification of Dermal Exposure to Permethrin Using Accelerator Mass Spectrometry

Impregnating military uniforms and outdoor clothing with the insecticide permethrin is an approach to reduce exposure to insect borne diseases and to repel pests and disease vectors such as mosquitos and sandflies, but the practice exposes wearers to prolonged dermal exposure to the pesticide. Key metabolite(s) from a low dose dermal exposure of permethrin were identified using accelerator mass spectrometry. Metabolite standards were synthesized and a high performance liquide chromatography (HPLC) elution protocol to separate individual metabolites in urine was developed. Six human subjects were exposed dermally on the forearm to 25 mg of permethrin containing 1.0 µCi of 14 C for 8 h. Blood, saliva and urine samples were taken for 7d. Absorption/elimination rates and metabolite concentrations varied by individual. Average absorption was 0.2% of the dose. Serum concentrations rose until 12–24 h postdermal application then rapidly declined reaching predose levels by 72 h. Maximum saliva excretion occurred 6 h postdosing. The maximum urinary excretion rate occurred during 12–24 h; average elimination half-life was 56 h. 3-Phenoxybenzyl alcohol glucuronide was the most abundant metabolite identified when analyzing elution fractions, but most of the radioactivity was in still more polar fractions suggesting extensive degradative metabolism and for which there were no standards. Finally, analyses of archived urine samples with the ultra performance liquid chromatography-accelerator mass spectrometry-mass spectrometry (UPLC-AMS-MS) system isolated a distinct polar metabolite but it was much diminished from the previous analyses a decade earlier.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Decarbonizing or illusion? How carbon emissions of commercial building operations change worldwide

To lead the low-carbon transition in global buildings, this study is the first to use the generalized Divisia index method (GDIM) to identify the factors driving carbon emissions and assess the decarbonization performance in commercial building operations (CBOs) of sixteen countries during 2000–2019. Results show that (1) while the global carbon emissions from CBOs have increased at a modest rate of 0.9%/yr, this trend runs counter to the declining emissions in the U.S. (-1.1%/yr) and the significant growth in China (14.4%/yr), which can be attributed to the impact of economy-related factors. (2) The U.S. and China, as the largest emitters, contributed 66.8% of the samples’ decarbonization of CBOs (919.1 million tons of carbon dioxide). (3) Most countries’ CBOs had a decarbonization efficiency level of less than 10%, except for Spain (27.8%). Spain excelled in both areas of per capita and per floor area with an average efficiency of nearly 30%. Moreover, ridge regression successfully confirms the stability of GDIM results and it should be noted GDIM has limitations in characterizing the end-use activity. Overall, this study tracks the historical decarbonization of global CBOs and offers benchmarks for different emitters to forecast the dynamic of building emissions along with economic booms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Development Support for NREL's System Advisor Model (SAM): Cooperative Research and Development, CRADA Number CRD-20-16998 (Final Report)

The variable nature of renewable generation, which depends on the sun shining and wind blowing for example, presents challenges for adequate and least-cost resource planning. The deployment of renewable generation assets is anticipated to increase due to various drivers, such as declining costs, favorable government policies, and increasing procurement by corporations and consumers. High levels of renewable penetration are anticipated to pose flexibility, reliability, and cost challenges to the electrical system. The development and implementation of new features into performance modeling software, such as the National Renewable Energy Laboratory's (NREL) System Advisor Model (SAM), is one way to help think through these challenges and develop appropriate strategies.

14 SOLAR ENERGY↗
NASA NTRS1999

Thin Film Ba(x) Sr(1-x)TiO3 Coupled Microstrip Ku- and K-band Phase Shifters

In this report authors found that the: (1) Best room temperature CMPS performance seen on 1% Mn-doped Ba(0.6)Sr(0.4)TiO3 annealed films on MgO: K = 74 C/dB. Phase Shift/coupled length: 1427 C/cm (2) Attempt to improve phase shifters through thicker as-deposited films stymied by declining film quality with film thickness. Annealing may alleviate this problem. (3) CMPS phase shift at Ku-band didn't experience the great rise in tunability seen in 1 MHz epsilon(sub r)(0) data. (4) While CMPS circuits may be well suited for arrays, simpler circuits like CPW would be more useful for characterizing epsilon(sub r) and tan(delta) at Ku-and K-band. (5) New substrates and designs are being tested.

VanKeuls, F. W.↗
NASA NTRS2003

Hindlimb unloading has a greater effect on cortical compared with cancellous bone in mature female rats

This study was designed to determine the effects of 28 days of hindlimb unloading (HU) on the mature female rat skeleton. In vivo proximal tibia bone mineral density and geometry of HU and cage control (CC) rats were measured with peripheral quantitative computed tomography (pQCT) on days 0 and 28. Postmortem pQCT, histomorphometry, and mechanical testing were performed on tibiae and femora. After 28 days, HU animals had significantly higher daily food consumption (+39%) and lower serum estradiol levels (-49%, P = 0.079) compared with CC. Proximal tibia bone mineral content and cortical bone area significantly declined over 28 days in HU animals (-4.0 and 4.8%, respectively), whereas total and cancellous bone mineral densities were unchanged. HU animals had lower cortical bone formation rates and mineralizing surface at tibial midshaft, whereas differences in similar properties were not detected in cancellous bone of the distal femur. These results suggest that cortical bone, rather than cancellous bone, is more prominently affected by unloading in skeletally mature retired breeder female rats.

NASA Discipline Musculoskeletal↗
DOE OSTI2025

Historic and modern nuclear graphite impurities: Pathways to improved waste strategies

Graphite has been used in large volumes as a structural material and neutron moderator since the earliest days of nuclear fission. However, no international consensus exists on the disposal of irradiated graphite, leaving much of the historic radioactive graphite inventory in interim vault or silo storage. With several new graphite-moderated reactors planned or under construction, the issue of graphite waste management is becoming increasingly urgent. This paper reviews and quantifies impurities in both historic and modern nuclear graphite, with emphasis on nitrogen—responsible for much of the 14 C inventory—and chlorine, which plays a critical role in repository performance and design. Modern graphites, benefitting from stringent quality-control measures developed for non-nuclear industries, meet or exceed the ASTM Ultra-High Purity nuclear standards, even without halide purification. Both chlorine and nitrogen concentrations have declined over time. For chlorine, identified as a key impurity influencing U.S. waste repository design, we propose a target of 0.1 appm in as-fabricated billets as a reasonable benchmark. Nitrogen sources are traced throughout the graphite production process, with surface and bulk concentrations characterized for all materials studied. Modern graphites commonly exhibit nitrogen levels below 5 appm, with values approaching 1 appm achievable. Using such reduced-nitrogen grades is critical to keeping graphite-induced radioactivity below the greater-than-Class-C waste threshold, thereby avoiding disposal cost penalties of nearly an order of magnitude.

Chlorine↗