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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Hydrophobins in the Life Cycle of the Ectomycorrhizal Basidiomycete Tricholoma vaccinum

Hydrophobins—secreted small cysteine-rich, amphipathic proteins—foster interactions of fungal hyphae with hydrophobic surfaces, and are involved in the formation of aerial hyphae. Phylogenetic analyses of Tricholoma vaccinum hydrophobins showed a grouping with hydrophobins of other ectomycorrhizal fungi, which might be a result of co-evolution. Further analyses indicate angiosperms as likely host trees for the last common ancestor of the genus Tricholoma. The nine hydrophobin genes in the T. vaccinum genome were investigated to infer their individual roles in different stages of the life cycle, host interaction, asexual and sexual development, and with respect to different stresses. In aerial mycelium, hyd8 was up-regulated. In silico analysis predicted three packing arrangements, i.e., ring-like, plus-like and sheet-like structure for Hyd8; the first two may assemble to rodlets of hydrophobin covering aerial hyphae, whereas the third is expected to be involved in forming a two-dimensional network of hydrophobins. Metal stress induced hydrophobin gene hyd5. In early steps of mycorrhization, induction of hyd4 and hyd5 by plant root exudates and root volatiles could be shown, followed by hyd5 up-regulation during formation of mantle, Hartig’ net, and rhizomorphs with concomitant repression of hyd8 and hyd9. During fruiting body formation, mainly hyd3, but also hyd8 were induced. Host preference between the compatible host Picea abies and the low compatibility host Pinus sylvestris could be linked to a stronger induction of hyd4 and hyd5 by the preferred host and a stronger repression of hyd8, whereas the repression of hyd9 was comparable between the two hosts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures

Although water temperature is important to stream biota, it is difficult to collect in a spatially and temporally continuous fashion. We used remotely-sensed Land Surface Temperature (LST) data to estimate mean daily stream temperature for every confluence-to-confluence reach in the John Day River, OR, USA for a ten year period. Models were built at three spatial scales: site-specific, subwatershed, and basin-wide. Model quality was assessed using jackknife and cross-validation. Model metrics for linear regressions of the predicted vs. observed data across all sites and years: site-specific r2 = 0.95, Root Mean Squared Error (RMSE) = 1.25 °C; subwatershed r2 = 0.88, RMSE = 2.02 °C; and basin-wide r2 = 0.87, RMSE = 2.12 °C. Similar analyses were conducted using 2012 eight-day composite LST and eight-day mean stream temperature in five watersheds in the interior Columbia River basin. Mean model metrics across all basins: r2 = 0.91, RMSE = 1.29 °C. Sensitivity analyses indicated accurate basin-wide models can be parameterized using data from as few as four temperature logger sites. This approach generates robust estimates of stream temperature through time for broad spatial regions for which there is only spatially and temporally patchy observational data, and may be useful for managers and researchers interested in stream biota.

McNyset, Kristina↗
DOE OSTI2020

Air compressor load forecasting using artificial neural network

Air compressor systems are responsible for approximately 10% of the electricity consumed in United States and European Union industry. As many researches have proven the effectiveness of using Artificial Neural Network inair compressor performance prediction, there is still a need to forecast the air compressor electrical load profile. The objective of this study is to predict compressed air systems’ electrical load profile, which is valuable to industry practitioners as well as software providers in developing better practice and tools for load managementand look-ahead scheduling programs. Two artificial neural networks, Two-Layer Feed-Forward Neural Networkand Long Short-Term Memory were used to predict an air compressors electrical load. Compressors with three different control mechanisms are evaluated with a total number of 11,874 observations. Here, the forecasts were validated using out-of-sample datasets with 5-fold cross-validation. Models produced average coefficient ofdetermination values from 0.24 to 0.94, average root-mean-square errors from 0.05 kW - 5.83 kW, and meanabsolute scaled errors from 0.20 to 1.33. The results indicate that both artificial neural networks yield goodresults for compressors using variable speed drive (average R 2 = 0.8 and no naïve forecasting), only the longshort-term memory model gives acceptable results for compressors using on/off control (average R 2 = 0.82 and no naïve forecasting), and no satisfactory results are obtained for load/unload type air compressors (models constituting active forecasting).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Coupled Induction Machine and HVAC Models for Simulating HVAC Performance Considering Grid Dynamics in Buildings

This paper presents the development of novel models that integrate induction machines with HVAC equipment, such as pumps, heat pumps, and chillers, to analyze the impact of electrical parameters on the operational performance of thermo-fluid systems. The proposed model employs a coupling technique that captures the dynamic interactions between induction machines and HVAC systems. By integrating electrical, thermal, and mechanical dynamics, the models provide a comprehensive framework for simulating real-world scenarios, including interactions with the electrical grid. This achievement was made possible through the development of a Computationally Efficient and Accurate Induction Machine (CEAIM) model. Implemented using the equation-based Modelica language, the CEAIM model has been validated against experimental results, manufacturer data sheets, and various operating conditions. Its performance has been compared with existing induction machine models in the Modelica Standard Library (MSL), demonstrating superior accuracy and computational efficiency. The CEAIM model predicts torque, speed, and power consumption with a coefficient of determination (R 2 ) ranging from 0.98 to 1 and a coefficient of variation of root mean square error (CVRMSE) between 0.27% and 6.67%. Additionally, CEAIM scales more efficiently than conventional MSL models, with a slower computational growth rate in large-scale simulations. After thorough validation of the CEAIM model, it was coupled with HVAC equipment as this approach provides a detailed multi-dimensional view of capturing electrical transients and mechanical performance. To support this, a case study was conducted to showcase its capabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A 32-Channel Cryo-CMOS ASIC for SNSPD Biasing and Readout with Picosecond

Superconducting nanowire single-photon detectors (SNSPD) are a promising technology for particle detection. Although SNSPDs have demonstrated picosecond timing accuracy, scaling up large arrays has proved challenging. In this work, we introduce a 32-channel cryo-CMOS application-specific integrated circuit (ASIC) that can be tightly integrated with SNSPD arrays. The ASIC is designed to operate at a temperature of 4K and can perform up to 32 simultaneous timing measurements with a root-mean-square (RMS) accuracy of 8.0ps. The ASIC includes on-chip circuitry for externally biasing superconducting devices, low-noise amplifiers for reading superconducting devices, high-resolution time-to-digital converters (TDC) for time-tagging events, and serializers for transmitting data to room-temperature electronics. The ASIC is manufactured in a 22nm FDSOI process and occupies an area of 4.0mm x 1.0mm. The performance of the ASIC was verified using custom cryogenic device models internally developed for the 22nm SOI process. Measurement results will be presented at the conference.

Fredenburg, Jeff↗
DOE OSTI2016

Nitrogen Fertilization Effects on Productivity and Nitrogen Loss in Three Grass-Based Perennial Bioenergy Cropping Systems

Nitrogen (N) fertilization can greatly improve plant productivity but needs to be carefully managed to avoid harmful environmental impacts. Nutrient management guidelines aimed at reducing harmful forms of N loss such as nitrous oxide (N 2 O) emissions and nitrate (NO 3 - ) leaching have been tailored for many cropping systems. The developing bioenergy industry is likely to make use of novel cropping systems, such as polycultures of perennial species, for which we have limited nutrient management experience. We studied how a switchgrass (Panicum virgatum) monoculture, a 5-species native grass mixture and an 18- species restored prairie responded to annual fertilizer applications of 56 kg N ha -1 in a fieldscale agronomic trial in south-central Wisconsin over a 2-year period.We observed greater fertilizer-induced N 2 O emissions and sub-rooting zone NO 3 - concentrations in the switchgrass monoculture than in either polyculture. Fertilization increased aboveground net primary productivity in the polycultures, but not in the switchgrass monoculture. Switchgrass was generally more productive, while the two polycultures did not differ from each other in productivity or N loss. In conclusion, our results highlight differences between polycultures and a switchgrass monoculture in responding to N fertilization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Magnetron R&Ds for High Efficiency CW RF Sources of Particle Accelerators

A proof of principle experiment carried out at JLab's magnetron R&D test stand has demonstrated a -25dB injection signal to phase lock a 2.45GHz 1.2kW CW magnetron within 2.1 Hz of root mean square deviation (RMSD) value with the optimization of magnetic field trimming of ±25% in order to overcome the frequency pushing of more than 4MHz in the RF power output range of 45-100%. In addition, a test stand for a newly built 1497 MHz, 13kW, CW magnetron prototype is ready for the high power injection test with outcome aimed for the CEBAF klystron replacement. Based on these R&D results, a 915MHz, 2?75kW CW commercial heating type magnetron system is being developed as high efficiency (>80%) RF source to drive an electron linac for industrial applications.

Wang, H.↗
DOE OSTI2016

Flow and Heat Transfer Tests in New Loop at 2757 kPa (400 psi)

A helium flow and heat transfer experiment has been designed for the new helium flow loop facility at LANL. This new facility is centered on an Aerzen GM 12.4 Root’s blower, selected for operation at higher pressure, up to 2757 kPa, and mass flow rate, up to 400 g/s. This replaces the previous Tuthill PD plus 3206 blower and loop limited to 2067 kPa (300 psi) and 100 g/s. The resistively heated test piece is comprised of 7 electric heaters with embedded thermocouples. The plant design for the Mo100 to Mo99 targets requires sharp bends and geometry changes in the helium flow tube immediately before and after the target. An idealized fully developed flow configuration with straight entry and exit will be tested and compared with an option that employs rectangular tubing to make the bend at a radius consistent with and practical for the actual plant design. The current plant design, with circular tubing and a sudden contraction to rectangular just prior to target entrance, will also be tested. This requires some modification of the test piece, as described in the report.

42 ENGINEERING↗
DOE OSTI2018

Causal Analysis Report for NA-SS-SNL-8000-2018-0002 Electrical shock: Wind Turbine Nacelle Lubbock TX

A Sandia National Laboratories Member of the Workforce (MOW) experienced contact with electrical energy while performing work on an oil filter pump electrical system in the al wind turbine nacelle at Sandia National Laboratories Scaled Wind Turbine Facility (SWiFT). The Department of Energy (DOE) Sandia National Laboratories (SNL) Scaled Wind Farm Technology (SWiFT) facility does research and development (R&D) work in collaboration with Texas Tech University. The SWiFT facility includes three turbines for performing wind plant and turbine technology research in support of DOE's Wind Energy Technology Office. The current work ongoing at the site is primarily related to commissioning the three turbines to support ongoing DOE customer needs and requests. It was during the performance of commissioning tests of the hydraulic systems in the a1 turbine that a Sandia MOW experienced contact with electrical energy. There were multiple root and contributing causes that ultimately resulted in the electrical energy contact. These causes are summarized and aligned to their corrective actions in the corrective action plan table provided in Section 7(c). The purpose of this narrative section is to provide additional information and context

17 WIND ENERGY↗
DOE OSTI2024

A 32-Channel Cryo-CMOS ASIC for SNSPD Biasing and Readout with Picosecond Timing

Superconducting nanowire single-photon detectors (SNSPD) are a promising technology for particle detection. Although SNSPDs have demonstrated picosecond timing accuracy, scaling up large arrays has proved challenging. In this work, we introduce a 32-channel cryo-CMOS application-specifc integrated circuit (ASIC) that can be tightly integrated with SNSPD arrays. The ASIC is designed to operate at a temperature of 4K and can perform up to 32 simultaneous timing measurements with a root-mean-square (RMS) accuracy of 8.0ps. The ASIC includes on-chip circuitry for externally biasing superconducting devices, low-noise amplifers for reading superconducting devices, high-resolution time-to-digital converters (TDC) for time-tagging events, and serializers for transmitting data to room-temperature electronics. The ASIC is manufactured in a 22nm FDSOI process and occupies an area of 4.0mm x 1.0mm. The performance of the ASIC was verifed using custom cryogenic device models internally developed for the 22nm SOI process. Measurement results will be presented at the conference.

Fredenburg, Jeff↗
DOE OSTI2025

Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Genomics in a changing arctic: critical questions await the molecular ecologist

Molecular ecology is poised to tackle a host of interesting questions in the coming years. Of particular importance to the molecular ecologist are new technologies and analytical approaches that provide opportunities to address questions previously unapproachable.The Arctic provides a unique and rapidly changing environment with a suite of emerging research needs that can be addressed through genetics and genomics. Here we highlight recent research on boreal and tundra ecosystems and put forth a series of questions related to plant and microbial responses to climate change that can benefit from technologies and analytical approaches contained within the molecular ecologist's toolbox. These questions include understanding (i) the mechanisms of plant acquisition and uptake of N in cold soils, (ii) how these processes are mediated by root traits, (iii) the role played by the plant microbiome in cycling C and nutrients within high-latitude ecosystems and (iv) plant adaptation to extreme Arctic climates. We highlight how contributions can be made in these areas through studies that target model and nonmodel organisms and emphasize that the sequencing of the Populus and Salix genomes provides a valuable resource for scientific discoveries related to the plant microbiome and plant adaptation in the Arctic. Moreover, there exists an exciting role to play in model development, including incorporating genetic and evolutionary knowledge into ecosystem and Earth System Models. In this regard, the molecular ecologist provides a valuable perspective on plant genetics as a driver for community biodiversity, and how ecological and evolutionary forces govern community dynamics in a rapidly changing climate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Development of Metal Boride/Carbide Precursors for MOCVD Applications (Office of Naval Research Research Performance Progress Report)

Annual Report for Office of Naval Research (ONR) program office. Highlights the synthetic and corresponding computational efforts surrounding the synthesis and processing of chemical precursors and their subsequent processing for formation of metal carbide products. Focus of this annual report is largely directed toward the computational effort as that manuscript is being finalized for submission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Characterization of resistance to a potent D -peptide HIV entry inhibitor

Background: PIE12-trimer is a highly potent D-peptide HIV-1 entry inhibitor that broadly targets group M isolates. It specifically binds the three identical conserved hydrophobic pockets at the base of the gp41 N-trimer with sub-femtomolar affinity. This extremely high affinity for the transiently exposed gp41 trimer provides a reserve of binding energy (resistance capacitor) to prevent the viral resistance pathway of stepwise accumulation of modest affinity-disrupting mutations. Such modest mutations would not affect PIE12-trimer potency and therefore not confer a selective advantage. Viral passaging in the presence of escalating PIE12-trimer concentrations ultimately selected for PIE12-trimer resistant populations, but required an extremely extended timeframe (> 1 year) in comparison to other entry inhibitors. Eventually, HIV developed resistance to PIE12-trimer by mutating Q577 in the gp41 pocket. Results: Using deep sequence analysis, we identified three mutations at Q577 (R, N and K) in our two PIE12-trimer resistant pools. Each point mutant is capable of conferring the majority of PIE12-trimer resistance seen in the polyclonal pools. Surface plasmon resonance studies demonstrated substantial affinity loss between PIE12-trimer and the Q577R-mutated gp41 pocket. A high-resolution X-ray crystal structure of PIE12 bound to the Q577R pocket revealed the loss of two hydrogen bonds, the repositioning of neighboring residues, and a small decrease in buried surface area. The Q577 mutations in an NL4-3 backbone decreased viral growth rates. Fitness was ultimately rescued in resistant viral pools by a suite of compensatory mutations in gp120 and gp41, of which we identified seven candidates from our sequencing data. Conclusions: These data show that PIE12-trimer exhibits a high barrier to resistance, as extended passaging was required to develop resistant virus with normal growth rates. The primary resistance mutation, Q577R/N/K, found in the conserved gp41 pocket, substantially decreases inhibitor affinity but also damages viral fitness, and candidate compensatory mutations in gp160 have been identified.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Root cause analysis of a molten salt pump in FLUSTFA

The primary salt pump installed in the high-temperature FLUoride Salt Test Facility (FLUSTFA) was successfully operated for some time, but later ceased operation. To understand what occurred, a Root Cause Analysis (RCA) was performed. Steps taken to try to get the pump operational include adjusting the shaft position, increasing the heating power of the tape heaters on the pump volute, and manually rotating the pump shaft. While removing the insulation, corrosion was noted on the outside of the pump volute, and decolorization of the insulation and tape heaters was observed. Significant corrosion products were also observed in the pump itself and the piping connected to the pump. The nitrogen cover gas was maintained from before salt was introduced into the loop until the pump was dismounted and continues to be maintained even after the pump was removed. After considering probable scenarios, causes were assigned and corrective actions were developed to prevent those causes. Then, the RCA was presented to an advisory committee for review, the “Review Committee,” consisting of experts in large molten salt systems: Brandon Haugh, David Holcomb, Kevin Robb, and Vicente Rojas. As a result, the advisory committee provided comprehensive feedback, which have been incorporated into a revised RCA. Findings have then been summarized and reported in this publication.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Numerical simulation of vortex-induced vibration response of a single IEA 10-MW wind turbine blade

Three-dimensional simulation of vortex-induced vibration (VIV) of a single International Energy Agency (IEA) 10-MW reference wind turbine blade with a length of 97.325 m is performed using the ExaWind stack, an open-source suite of codes. This study aims to illustrate the spanwise VIV response characteristics and cross-validate the results with an existing commercial framework. Five near-body meshes and three time steps are selected for the convergence study. To improve computational efficiency, several VIV triggering methods are also compared to shorten the VIV development period. The ExaWind-based VIV simulation strategy for a single IEA 10-MW blade is determined. First, the modal shape is validated against published results. Then, spanwise VIV responses of four blade configurations under a fixed and varied incoming flow velocity are analyzed. Results show that the VIV response is dominated by the first edgewise (second overall) mode. Little first-mode contributions appear near the second-mode node, producing a pi phase jump, and a higher harmonics response occurs near the blade root. Rotational degrees of freedom are minor compared with translational motion. The response versus reduced velocity is analyzed, showing a two-branch behavior similar to that of VIV for a bluff cylinder. Across all tested cases, the dominant frequency remains locked to the natural frequency of the second mode with no observed desynchronization. A mild deviation is observed for the case of 90-degree pitch and 310-degree azimuth rotation near a reduced velocity of 6, which will be examined with additional cases in future work. These findings indicate that severe VIV responses can arise under specific configurations and flow conditions, thereby increasing the potential for VIV fatigue damage and requiring greater attention during operation.

17 WIND ENERGY↗
DOE OSTI2025

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗
DOE OSTI2020

Global biogeography of fungal and bacterial biomass carbon in topsoil

Bacteria and fungi, representing two major soil microorganism groups, play an important role in global nutrient biogeochemistry. Biogeographic patterns of bacterial and fungal biomass are of fundamental importance for mechanistically understanding nutrient cycling. We synthesized 1323 data points of phospholipid fatty acid-derived fungal biomass C (FBC), bacterial biomass C (BBC), and fungi:bacteria (F:B) ratio in topsoil, spanning 11 major biomes. The FBC, BBC, and F:B ratio display clear biogeographic patterns along latitude and environmental gradients including mean annual temperature, mean annual precipitation, net primary productivity, root C density, soil temperature, soil moisture, and edaphic factors. At the biome level, tundra has the highest FBC and BBC densities at 3684 (95% confidence interval: 1678–8084) mg kg -1 and 428 (237–774) mg kg -1 , respectively; desert has the lowest FBC and BBC densities at 16.92 (14.4–19.89) mg kg -1 and 6.83 (6.1–7.65) mg kg -1 , respectively. The F:B ratio varies dramatically, ranging from 1.8 (1.6–2.1) in savanna to 8.6 (6.7–11.0) in tundra. An empirical model was developed for the F:B ratio and it is combined with a global dataset of soil microbial biomass C to produce global maps for FBC and BBC in 0–30 cm topsoil. Across the globe, the highest FBC is found in boreal forest and tundra while the highest BBC is in boreal forest and tropical/subtropical forest, the lowest FBC and BBC are in shrub and desert. Global stocks of living microbial biomass C were estimated to be 12.6 (6.6–16.4) Pg C for FBC and 4.3 (0.5–10.3) Pg C for BBC in topsoil. These findings advance our understanding of the global distribution of fungal and bacterial biomass, which facilitates the incorporation of fungi and bacteria into Earth system models. The global maps of bacterial and fungal biomass serve as a benchmark for validating microbial models in simulating the global C cycle under a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗