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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Biomass yield potential, feedstock quality, and nutrient removal of perennial buffer strips under continuous zero fertilizer application

Perennial-based buffer strips have been promoted as having the potential for improving ecosystem services from riparian areas while producing biomass as livestock feed or as a bioenergy feedstock. Both biomass production and nutrient removal of buffer strips are substantially influenced by the vegetation types for the multipurpose perennial buffers. In this 2016–2019 study in western Illinois, two perennial cropping systems, including forage crops composed of cool-season grass mixtures (forage system) and bioenergy crops made up of warm-season grass mixtures (bioenergy system), were used to establish buffer strips for assessing biomass production, feedstock quality, nutrient removal, and buffer longevity. Treatments for this study reflecting agronomic practices included (1) two harvests occurring in summer (at anthesis) and fall (after complete senescence) and (2) one harvest in fall for the forage system (two-cut vs. one-cut forage) and (3) one fall harvest for the bioenergy system (one-cut bioenergy). Successively harvesting without any fertilizer input resulted in a yield decline in forage biomass over 3 years by approximately 30 % (6.3 to 4.4 Mg DM ha –1 (dry matter) with a rate of 1.0 Mg ha –1 yr –1 ) in the two-cut forage and by 35 % (4.9 to 3.2 Mg DM ha –1 with a rate of 0.9 Mg ha –1 yr –1 ) in the one-cut forage systems. The feed quality also decreased over the years by showing declined rates of 12.9 (crucial protein), 0.9 (calcium), 0.7 (copper), and 1.3 g kg –1 DM yr –1 (zinc). Empirical models predicted enteric CH 4 emissions from cattle ranged from 225.7 to 242.6 g per cow per day based on the feed nutritive values. In contrast, bioenergy biomass yield increased by 27 % from 4.9 to 6.7 Mg DM ha –1 with a consistent quality (cellulose of ~ 397.9 g kg –1 ; hemicellulose of ~ 299.4 g kg –1 ), corresponding to the increased total theoretical ethanol yield from 1.8 × 10 3 to 2.4 × 10 3 L ha –1 (~ 33 % increase). Annual nutrient removals of N, P, K, Ca, and Mg were significantly higher in the forage systems (e.g., two-cut: 52.6–106.9 kg N ha –1 ; one-cut: 44.5–84.1 kg N ha –1 ) than those in the bioenergy system (e.g., 25.9–34.4 kg N ha –1 ); however, the removal rate declined rapidly over 3 years (e.g., ~ 49 % reduction) as the annual biomass yield declined in the forage systems. This on-farm field study demonstrated the potential of the perennial crop used as buffer strip options for biomass production and buffer sustainability at the edge of the field.

09 BIOMASS FUELS↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme

As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.

Molthan, Andrew L.↗
NASA NTRSDate not supplied

The Emphasis of Design Patterns in Expressing Expert Knowledge From A Technical Solution – A Framework for Continued Research

Digital Engineering is a transformative strategy that leverages an integrated model-based approach to improve communication, decision making, design understanding, and acquisition efficiency of system development. As modern systems are derived from pre-existing systems, harvesting expert knowledge from proven systems in a useful, model-based way will reduce the experiential learning and cognition required for new system development, contributing to a Digital Engineering transformation. Motivated by performance gains observed during a multi-year, sequential development activity, this survey reviews knowledge, architecture, and pattern literature to establish a framework for research of architectural methods for expert knowledge identification and description using Model Based System Engineering. The multi-year sequential development activity is offered as the experimental system of interest for this research. This work aims to enable a digital engineering strategy that improves concept phase decision making, accelerates knowledge acquisition from lessons learned repositories, and eases the burden of generational knowledge loss.

Lithium Ion↗
DOE OSTI2025

Ensemble‐Based Spatially Distributed CLM5 Hydrological Parameter Estimation for the Continental United States

Abstract One of the major challenges in large‐domain hydrological modeling efforts lies in the estimation of spatially distributed hydrological parameters while simultaneously accounting for their associated uncertainties. Addressing this challenge is particularly difficult in ungauged locations. With growing societal demands for large‐scale streamflow projections to inform water resource management and long‐term planning, evaluating and constraining hydrological parameter uncertainty is increasingly vital. This study introduces a hybrid regionalization approach to enhance hydrological predictions of the Community Land Model version 5 (CLM5) across the Continental United States (CONUS), with a total of 50,629 1/8° grid cells. This hybrid method combines the strengths of two existing techniques: parameter regionalization and streamflow signature regionalization. It identifies ensemble behavioral parameters for each 1/8° grid cell across the CONUS domain, tailored to three distinct streamflow signatures focused on low flows, high flows, and annual water balance. Evaluating this hybrid method for 464 CAMELS (Catchment Attributes and Meteorology for Large‐sample Studies) basins demonstrates a significant improvement in CLM5 hydrological predictions, even in challenging arid regions. In CONUS applications, the derived spatially distributed parameter sets capture both spatial continuity and variation of parameters, highlighting their heterogeneous nature within specific regions. Overall, this hybrid regionalization approach offers a promising solution to the complex task of improving hydrological modeling over large domains for important hydrological applications.

CLM5↗
NASA NTRSDate not supplied

Fostering Better Collaboration in Software Development Cycles Between Scientists and Programmers to Ensure the Integrity of and Promote the Development of New Scientific Data Products.

Misaligned incentives lead to reduced interaction between scientists and programmers on modern NASA science data-product development teams. Typically, situations arise where the scientist is not incentivized to learn modern coding practices and the programmer does not understand the science algorithms in the code. A programmer is responsible for the deliverable code thus setting a tradeoff between the desire for code improvement versus fear of compromising the integrity of data-product while the scientist continues to rely on their legacy codebases owing to the complexity of using the delivered code outside the processing environment and lack of validation modules. The NASA/CERES-TISA project has adopted a collaborative approach, with scientists and programmers both utilizing the same software repository with multiple branches, some optimized for delivery to a processing datacenter and others for scientific product development and validation. A team of scientists and programmers jointly review any new science code updates for integration into the codebase and strive to improve practices through promoting algorithm understanding, better institutional knowledge exchange and documentation, modularization, and developing data processing flow-dictated validation and debugging methods. This leads to a reduction in the personnel single point failures and reduced development time for creation of new science data-products.

CERES↗
DOE OSTI2023

Cost‐benefit assessment framework for robotics‐driven inspection of floating offshore wind farms

Abstract Operations and maintenance (O&M) of floating offshore wind farms (FOWFs) poses various challenges in terms of greater distances from the shore, harsher weather conditions, and restricted mobility options. Robotic systems have the potential to automate some parts of the O&M leading to continuous feature‐rich data acquisition, operational efficiency, along with health and safety improvements. There remains a gap in assessing the techno‐economic feasibility of robotics in the FOWF sector. This paper investigates the costs and benefits of incorporating robotics into the O&M of a FOWF. A bottom‐up cost model is used to estimate the costs for a proposed multi‐robot platform (MRP). The MRP houses unmanned aerial vehicle (UAV) and remotely operated vehicle (ROV) to conduct the inspection of specific FOWF components. Emphasis is laid on the most conducive O&M activities for robotization and the associated technical and cost aspects. The simulation is conducted in Windfarm Operations and Maintenance cost‐Benefit Analysis Tool (WOMBAT), where the metrics of incurred operational expenditure (OPEX) and the inspection time are calculated and compared with those of a baseline case consisting of crew transfer vessels, rope‐access technicians, and divers. Results show that the MRP can reduce the inspection time incurred, but this reduction has dependency on the efficacy of the robotic system and the associated parameterization e.g., cost elements and the inspection rates. Conversely, the increased MRP day rate results in a higher annualized OPEX. Residual risk is calculated to assess the net benefit of incorporating the MRP. Furthermore, sensitivity analysis is conducted to find the key parameters influencing the OPEX and the inspection time variation. A key output of this work is a robust and realistic framework which can be used for the cost‐benefit assessment of future MRP systems for specific FOWF activities.

17 WIND ENERGY↗
DOE OSTI2020

Enhanced carbon-transfer and -utilization efficiencies achieved using membrane carbonation with gas sources having a range of CO 2 concentrations

The economic viability of microalgal biofuels relies on increasing productivity in a cost-effective manner. As microalgal biomass contains > 50% carbon, a high rate of CO 2 delivery is required for high productivity, and inefficient CO 2 delivery amplifies operating costs. Membrane carbonation using non-porous hollow fiber membranes can ideally deliver CO 2 without bubble formation and high carbon transfer efficiency. Because CO 2 streams from industrial resources are not 100% CO 2 , the buildup of inert gasses can significantly lower the CO 2 delivery rate when the distal end of the membrane is closed. To overcome the buildup of inert gases, we managed the distal end of the membranes with three different approaches: fully open end, restricted bleed valve, and restricted bleed valve with pH-actuated venting. For all approaches, CO 2 was delivered to membranes ondemand based on a pH set point. Evaluating a wide range of CO 2 concentrations (10% to 100%), we found that all approaches eliminated the buildup of inert gases, could maintain target pH values and gave the same biomass productivities and carbon distributions. However, carbon transfer efficiency depended on the operation of the distal end. Fully open-end operation gave a poor carbon transfer efficiency because of excessive loss of CO 2 from the distal end. However, restricting the exit flow rate to ≤4 cm 3 /min mitigated the problems of excessive CO 2 loss, but without incurring a large loss of CO 2 -delivery flux. For the continuous cultivation, combining a restricted bleed valve with pH-actuated venting improved the carbon-transfer efficiency and -utilization efficiencies up to 85% and 67%, respectively, with a sufficient CO 2 delivery flux.

42 ENGINEERING↗
DOE OSTI2024

Surrogate construction via weight parameterization of residual neural networks

Surrogate model development is a critical step for uncertainty quantification or other sample-intensive tasks for complex computational models. Here, in this work, we develop a multi-output surrogate form using a class of neural networks (NNs) that employ shortcut connections, namely Residual NNs (ResNets). ResNets are known to regularize the surrogate learning problem and improve the efficiency and accuracy of the resulting surrogate. Inspired by the continuous, Neural ODE analogy, we augment ResNets with weight parameterization strategy with respect to ResNet depth. Weight-parameterized ResNets regularize the NN surrogate learning problem and allow better generalization with a drastically reduced number of learnable parameters. We demonstrate that weight-parameterized ResNets are more accurate and efficient than conventional feed-forward multi-layer perceptron networks. We also compare various options for parameterization of the weights as functions of ResNet depth. We demonstrate the results on both synthetic examples and a large scale earth system model of interest.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Advances and challenges in KSTAR plasma control toward long-pulse, high-performance experiments

An overview of advances and progress on the KSTAR plasma control improvement is given. The enhancement of the KSTAR plasma control system (PCS) continues in order to enable implementations of more sophisticated control algorithms and capabilities of integrated controls on magnets, gas, heating and off-normal event handling. Features and functionalities on the generic magnetic controls, kinetic controls and new fault scheme design are added for the operation space expansion, mainly regarding recent achievements of higher plasma current up to 1.0–1.2MA, high-performance long pulse up to 90s, and discharges relevant to ITER. Technical challenges and prospective upgrades in the near future are described.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Rapid grain refinement and compositional homogenization in a cast binary Cu50Ni alloy achieved by friction stir processing

Friction stir processing (FSP) has been increasingly adopted for joining and processing materials in automotive, aerospace and industrial construction. During FSP a dynamic competition between high-speed shear deformation and deformation-induced heating brings about a complex competition between multiple dynamic microstructural evolution mechanisms making it difficult to predict the microstructural evolution pathway. Hence, improved understanding of microstructural evolution mechanisms during FSP can be beneficial for continued growth in the adoption of FSP for demanding applications of future. Towards this goal, this study uses a model binary Cu – 50 at.% Ni alloy to clarify the effect of single and double pass FSP on the microstructural evolution of a coarse grained and compositionally heterogeneous cast microstructure. High energy synchrotron X-ray diffraction, electron backscatter diffraction, and nanoindentation are used to clarify the microstructural evolution due to FSP. The process of compositional homogenization of as-cast segregations is studied by energy dispersive spectroscopy and atom probe tomography. Our results show that a single fast FSP pass at 30 mm.s -1 produces a 100 µm deep layer of submicrometric and hall-petch hardened CuNi grains. The initial cast compositional heterogeneities in a micrometric scale is rapidly transformed to nano-sized domains, mainly confined at grain boundaries. Double pass FSP increases the penetration depth of the processed layer and leads to a 2.9 times grain growth relative to single pass FSP. Grain fragmentation, discontinuous dynamic recrystallization, grain growth, and twinning mechanisms are discussed. In conclusion, these results highlight the value of FSP for ultrafast grain refinement and compositional homogenization of cast alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Conversion of High-Solids Hydrothermally Pretreated Bioenergy Sorghum to Lipids and Ethanol Using Yeast Cultures

Glucose and xylose are the major sugars in cellulosic hydrolysates. The cellulosic sugars can be used for the production of biofuels and value-added bioproducts. In this study, lipid and ethanol were produced from bioenergy sorghum syrups using engineered yeasts. Here, bioenergy sorghum was hydrothermally pretreated at 50% solids loading in a continuous reactor system and mechanically refined sequentially using a burr mill to improve biomass accessibility for hydrolysis. Fed-batch enzymatic hydrolysis was conducted with 50% w/v solids loading to achieve 230 g/L sugar concentration. Different strains of Rhodosporidium toruloides were used to ferment sugars into lipids, and the highest lipid yield of 9.2 g/L was observed. The lipid yield was improved to 19.0 g/l by implementing a two-stage culture where once the sugars were exhausted in the first stage, the yeast was introduced into fresh hydrolysate without adding nitrogen. For ethanol production, the engineered Saccharomyces cerevisiae SR8ΔADH6 was utilized to coferment glucose and xylose. Additionally, the effects of nutrient media (YP, YNB/urea, and urea), cellulosic sugar concentration, and sulfite addition were investigated to optimize the ethanol yield from sorghum syrups. The optimal ethanol yield at 73.3% was obtained from the YNB/urea culture consisting of 34 g glucose/L and 17 g xylose/L.

09 BIOMASS FUELS↗
DOE OSTI2022

Limitations of Separate Cloud and Rain Categories in Parameterizing Collision-Coalescence for Bulk Microphysics Schemes

Warm rain collision-coalescence has been persistently difficult to parameterize in bulk microphysics schemes. We use a flexible bulk microphysics scheme with bin scheme process parameterizations, called AMP, to investigate reasons for the difficulty. AMP is configured in a variety of ways to mimic bulk schemes and is compared to simulations with the bin scheme upon which AMP is built. We find that an important limitation in traditional bulk schemes is the use of separate cloud and rain categories. When the drop size distribution is instead represented by a continuous distribution, the simulation of cloud-to-rain conversion is substantially improved. We also find large sensitivity to the threshold size to distinguish cloud and rain in traditional schemes; substantial improvement is found by decreasing the threshold from 40 to 25 μm. Neither the use of an assumed functional form for the size distribution nor the choice of predicted distribution moments has a large impact on the ability of AMP to simulate rain production. When predicting four total moments of the liquid drop size distribution, either with a traditional two-category, two-moment scheme with a reduced size threshold, or a four-moment single-category scheme, errors in the evolution of mass and the cloud size distribution are similar, but the single-category scheme has a substantially better representation of the rain size distribution. Optimal moment combinations for the single-category approach are investigated and appear to be linked more to the information content they provide for constraining the size distributions than to their correlation with collision-coalescence rates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Constraining hydrodynamic models of inertial confinement fusion implosions using capsule surrogate experiments

We conduct capsule surrogate experiments at the National Ignition Facility to calibrate radiation hydrodynamic simulations to infer hydrodynamic conditions that are not observable in indirect drive ignition implosions. We tune the simulations by applying laser power and cross beam energy transfer (CBET) saturation multipliers to match the observables from capsule surrogate experiments. Shock timing, velocity, and symmetry are measured in liquid D 2 filled Keyhole capsule surrogate experiments and implosion trajectory, stagnation time, and shape time history are measured in in-flight 2D backlit x-ray radiography experiments (“2DConA”) of D 2 gas filled capsule implosions. Calibrated simulations suggest that the N210808 ignition implosion (fusion target gain = 0.7) had a shell mass remaining at stagnation of less than the nominal %5 (3.8%) and resulted in less confinement. For N221204, the shell was made 5.75 μm thicker to trade implosion velocity for increased confinement and resulted in a target gain = 1.5 with a shell mass remaining of 5.7%. Furthermore, a single adjusted model can reproduce all shock timing data as changes are made to shell thickness (79–85 μm) and laser wavelength separation (1.8–4.0 Å). However, for the 2DConA implosions, a 5% variation in the peak power laser multipliers and a 30% variation in late-time CBET between experiments are needed to match the observed stagnation times, in-flight $P_2$ shape, and hot-spot $P_2$ shape. While progress is being made to improve the models in simulations using focused experiments, capsule surrogate experiments will continue to be needed to optimize future ignition designs.

Lasers↗
DOE OSTI2021

Data for Conversion of High-Solids Hydrothermally Pretreated Bioenergy Sorghum to Lipids and Ethanol Using Yeast Cultures

Glucose and xylose are the major sugars present in cellulosic hydrolysates. The cellulosic sugars can be used for the production of platform chemicals. In this study, productions of lipid and ethanol by yeasts were compared for concentrated bioenergy sorghum syrup. Bioenergy sorghum was hydrothermally pretreated at 50% w/w solids in a continuous industrial reactor and sequentially mechanically refined using a burr mill to improve biomass accessibility for hydrolysis. Fed-batch enzymatic hydrolysis was conducted with 50% w/v solids loading and cellulase cocktail (50 FPU/g biomass) to achieve 230 g/L sugar concentration. Various strains of Rhodosporidium toruloides were evaluated for converting sugars into lipids, and strain Y-6987 had the highest lipid titer (9.2 g/L). The lipid titer was improved to 19.0 g/L by implementing a two-stage culture scheme, where the first stage was optimized for yeast growth and the second for lipid production. For ethanol production, the engineered Saccharomyces cerevisiae SR8ΔADH6 was used to coferment glucose and xylose. Ethanol fermentation was optimized for media nutrients (YP, YNB/urea, and urea), cellulosic sugar concentration, and sulfite conditioning to maximize the ethanol concentration from sorghum syrups. Fermentation of 70% v/v concentrated hydrolysate conditioned with sulfite produces 50.1 g/L ethanol from 141 g/L of sugars.

Conversion↗
DOE OSTI2021

Assessment of Electrode Contamination Mitigation at 0.5 MA Scale

The Z Machine at Sandia National Laboratories uses current pulses with peaks up to 27 MA to drive target implosions and generate high energy density conditions of interest for stockpile stewardship programs pertinent to the NNSA program portfolio . Physical processes in the region near the Z Machine target create electrode plasmas which seed parasitic current loss that reduce the performance and output of a Z experiment. Electrode surface contaminants (hydrogen, water, hydrocarbons) are thought to be the primary constituent of electrode plasmas which contribute to loss mechanisms. The Sandia team explore d in situ heating and plasma discharge techniques by integrating requisite infrastructure into Sandia's Mykonos LTD accelerator, addressing potential impacts to accelerator operation, and reporting on the impact of these techniques on electrode plasma formation and shot performance. The in situ discharge cleaning utilizes the electrodes of the accelerator to excite an argon-oxygen plasma to sputter and chemically react contaminants from electrode surfaces. Insulating breaks are required to isolate the plasma in electrode regions where loss processes are most likely to occur. The shots on Mykonos validate that these breaks do not perturb experiment performance, reducing the uncertainty on the largest unknown about the in situ cleaning system. Preliminary observations with electrical and optical diagnostics suggest that electrode plasma formation is delayed, and overall inventory has been substantively reduced. In situ heating embeds cartridge heaters into accelerator electrodes and employs a thermal bakeout to rapidly desorb contaminants from electrode surfaces. For the first time, additively manufactured (AM) electrode assemblies were used on a low impedance accelerator to integrate cooling channels and manage thermal gradients. Challenges with poor supplier fabrication to specifications, load alignment, thermal expansion and hardware movement and warpage appears to have introduced large variability in observed loss, though, preventing strong assertions of loss reduction via in situ heating. At this time, an in situ discharge cleaning process offers the lowest risk path to reduce electrode contaminant inventories on Z, though we recommend continuing to develop both approaches. Additional engineering and testing are required to improve the implementation of both systems. .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Towards a New Supply Chain Cybersecurity Risk Analysis Technique

Supply chain cyber-attacks, such as the SolarWinds Orion attack, are occurring with greater frequency. These attacks compromise a digital device before it is sent to customers, bypassing traditional security controls to remain persistent and undetected in operational environments. While supply chain attacks are prevalent, methods for analyzing the risk of these attacks are currently unavailable. This paper proposes new supply chain cyber-attack difficulty and risk metrics to evaluate the relative risk of an attack throughout the supply chain lifecycle. Difficulty metrics for each stakeholder in a digital device’s supply chain (e.g., hardware manufacturing, firmware development, software development, storage, and distribution entities) are calculated using scores from cybersecurity maturity questionnaires in a Bayesian Network leaky Noisy-MAX model. These difficulty metrics are then used to calculate an overall supply chain cyber-attack risk. Vulnerability and recoverability metrics are also proposed to evaluate the relative stakeholder influence in the attack risk. These proposed relative risk metrics enable continuous supply chain monitoring, provide decision-makers with information necessary for improved supplier selection, and help drive improvements in the cybersecurity posture of the stakeholders in their supply chain.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1966

Vibrator improves spark erosion cutting process

Variable frequency mechanical vibrator improves spark erosion cutting process. The vibration of the cutting tip permits continual flushing away of residue around the cut area with nondestructive electric transformer oil during the cutting process.

Thrall, L. R.↗