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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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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Advancing research on compound weather and climate events via large ensemble model simulations

Societally relevant weather impacts typically result from compound events, which are rare combinations of weather and climate drivers. Focussing on four event types arising from different combinations of climate variables across space and time, here we illustrate that robust analyses of compound events — such as frequency and uncertainty analysis under present-day and future conditions, event attribution to climate change, and exploration of low-probability-high-impact events — require data with very large sample size. In particular, the required sample is much larger than that needed for analyses of univariate extremes. We demonstrate that Single Model Initial-condition Large Ensemble (SMILE) simulations from multiple climate models, which provide hundreds to thousands of years of weather conditions, are crucial for advancing our assessments of compound events and constructing robust model projections. Combining SMILEs with an improved physical understanding of compound events will ultimately provide practitioners and stakeholders with the best available information on climate risks.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Cryogenic Composite Tank Design for Next Generation Launch Technology

The structural performance of liquid hydrogen tanks made from composites is investigated. A computational method that judiciously combines structural analysis, composite mechanics, progressive fracture algorithm to evaluate damage tolerance, durability, and fatigue and fracture is described. A tank design concept is introduced and evaluated. The composite tank is internally stiffened by incorporating additional stacks of laminates along its length to alternate rows of finite elements. The robustness of the proposed design concept is assessed by damage progression analysis. Damage initiates i the composite at an internal pressure that is nearly two times the design pressure. From the point of damage initiation, the designed tank can tolerate an increase in internal pressure that is nearly three and a half times the design pressure. Low cycle fatigue analysis is also performed to determine the effect of pressurization and de-pressurization on the structural integrity of the tank. Results show that the tank can sustain at least a 100 cycles before any failure take place.

Abumen, Galib H.↗

NASA NTRS1983

Nonlinear truncation error analysis of finite difference schemes for the Euler equations

It is pointed out that, in general, dissipative finite difference integration schemes have been found to be quite robust when applied to the Euler equations of gas dynamics. The present investigation considers a modified equation analysis of both implicit and explicit finite difference techniques as applied to the Euler equations. The analysis is used to identify those error terms which contribute most to the observed solution errors. A technique for analytically removing the dominant error terms is demonstrated, resulting in a greatly improved solution for the explicit Lax-Wendroff schemes. It is shown that the nonlinear truncation errors are quite large and distributed quite differently for each of the three conservation equations as applied to a one-dimensional shock tube problem.

Klopfer, G. H.↗

DOE OSTI2023

A comparison of past and present computational methods for shape analysis of double-shell x-ray radiographs

Implosion symmetry is a key requirement in achieving a robust burning plasma in inertial confinement fusion experiments. In double-shell capsule implosions, we are interested in the shape of the inner shell as it pushes on the fuel. Shape analysis is a popular technique for studying said symmetry during implosion. Combinations of filtering and contour-finding algorithms are studied for their promise in reliably recovering Legendre shape coefficients from synthetic radiographs of double-shell capsules with applied levels of noise. A radial lineout max(slope) method when used on an image pre-filtered with non-local means and a variant of the marching squares algorithm are able to recover p 0 , p 2 , and p 4 maxslope Legendre shape coefficients with mean pixel discrepancy errors of 2.81 and 3.06, respectively, for the noisy synthetic radiographs we consider. Here, this improves upon prior radial lineout methods paired with Gaussian filtering, which we show to be unreliable and whose performance is dependent on input parameters that are difficult to estimate.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using row-resolution (i.e., 15 minutes) smart meter data. We first demonstrate that the electricity consumption profiles on mild-temperature days can be used to approximate the base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed from the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and verify the proposed methods. Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers.

Kim, Hyeonjin↗

NASA NTRSDate not supplied

Dragonfly Entry and Descent Flight Mechanics Modeling and Analysis

Dragonfly is a New Frontiers Program mission that will deliver a rotorcraft lander to Saturn’s moon, Titan [1]. The focus of this work is to analyze the trajectory from cruise stage separation until lander separation. This analysis is done by the NASA Langley (LaRC) EDL team using Program to Optimize Trajectories II (POST2)[2]. This poster provides an overview of the current design and the robustness of the overall entry sequence as assessed using a Monte Carlo uncertainty analysis. This mission is led by Johns Hopkins Applied Physics Laboratory (APL), presented here is the design and analysis as of the Dragonfly EDL Assembly Preliminary Design Review (PDR).

Modeling↗

NASA NTRS2017

Linear Covariance Analysis for a Lunar Lander

A next-generation lunar lander Guidance, Navigation, and Control (GNC) system, which includes a state-of-the-art optical sensor suite, is proposed in a concept design cycle. The design goal is to allow the lander to softly land within the prescribed landing precision. The achievement of this precision landing requirement depends on proper selection of the sensor suite. In this paper, a robust sensor selection procedure is demonstrated using a Linear Covariance (LinCov) analysis tool developed by Draper.

Jang, Jiann-Woei↗

DOE OSTI2016

A periodic freshwater patch detachment process from the Block Island Sound estuarine plume: BIS PERIODIC FRESHWATER PATCH DETACHMENT

Previous observations suggest periodic freshwater patches separating from the Block Island Sound (BIS) estuarine plume. In this study, the dynamics of the separation process is investigated through a series of numerical experiments using the Regional Ocean Modeling System (ROMS). In addition, we explore the seasonal variability of the freshwater patches and their response to river discharge and ambient current. The model results indicate that episodic freshwater patches are triggered by small changes in tidal currents over the spring-neap tidal cycle. The spring-neap variation in tidal currents causes significant, monthly fluctuations in turbulent mixing and vertical stratification in BIS, modulating the freshwater discharge thereby generating episodic freshwater patches that move both downstream along the southern shore of Long Island and toward Rhode Island Sound (RIS). The realistically configured model shows that the freshwater patches experience strong seasonal variability. They are largest in spring when the river discharge peaks, and smallest in summer due to the weak river discharge and a robust upstream ambient current from RIS. According to the analysis of the freshwater transport out of BIS, we conclude that such detachment occurs at tidal mixing fronts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Operando Tailoring of Defects and Strains in Corrugated β-Ni(OH) 2 Nanosheets for Stable and High-Rate Energy Storage

Nickel hydroxide represents a technologically important material for energy storage, such as hybrid supercapacitors. It has two different crystallographic polymorphs, α- and β-Ni(OH) 2 , showing advantages in either theoretical capacity or cycling/rate performance, manifesting a trade-off trend that needs to be optimized for practical applications. In this work, the synergistic superiorities in both activity and stability of corrugated β-Ni(OH) 2 nanosheets are demonstrated through an electrochemical abuse approach. With ≈91% capacity retention after 10 000 cycles, the corrugated β-Ni(OH) 2 nanosheets can deliver a gravimetric capacity of 457 C g -1 at a high current density of 30 A g -1 , which is nearly two and four times that of the regular α- and β-Ni(OH) 2 , respectively. Operando spectroscopy and finite element analysis reveal that greatly enhanced chemical activity and structural robustness can be attributed to the in situ tailored lattice defects and the strain-induced highly curved micromorphology. This work demonstrates a multi-scale defect-and-strain co-design strategy, which is helpful for rational design and tuned fabrication of next-generation electrode materials for stable and high-rate energy storage.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Laser machined plastic laminates. Towards portable diagnostic devices for use in low resource environments

Despite significant progress in development of bioanalytical devices cost, complexity, access to reagents and lack of infrastructure have prevented use of these technologies in resource-limited regions. To provide a sustainable tool in the global effort to combat infectious diseases the diagnostic device must be low cost, simple to operate and read, robust, and have sensitivity and specificity comparable to laboratory analysis. Thus, in this mini-review we describe recent work using laser machined plastic laminates to produce diagnostic devices that are capable of a wide variety of bioanalytical measurements and show great promise towards future use in low-resource environments.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Atikokan Digital Twin: Machine learning in a biomass energy system

The Atikokan Generating Station, operated by Ontario Power Generation, has a 200 MW, biomass-fired tower boiler that operates on a dispatch schedule with a five-minute cycle. The boiler is generally operated in the range of 40–100 MW using two of five burner levels. In order to optimize boiler performance, we propose the implementation of a unique digital twin. Our digital twin abstraction couples Bayesian inference from science-based models and from observations (machine learning) with decision theory to predict operating-variable set points that optimize the physical asset (the boiler) in the presence of uncertainty (artificial intelligence). We focus this paper on the continuous Bayesian machine learning part of the Atikokan Digital Twin; we discuss decision theory in a companion paper. We identify and learn about 12 operational, model, and measured-output parameters and their uncertainties from high-fidelity, science-based simulations of the Atikokan boiler and from the observed measurements at the power plant. Since the goal of the Atikokan Digital Twin is to implement it online in real time, we require fast function evaluations for the quantities of interest extracted from the simulations in the Bayesian analysis. We use Gaussian process regression/interpolation to create accurate, robust surrogate models. We define the Bayesian priors and likelihood function and solve for the posterior distributions of the 12 parameters. Here we then propagate these distributions (i.e., parameters with uncertainty) into the predicted distributions of 790 quantities of interest to learn about the relative importance of various sources of error including experimental, model, and operating-parameter errors.

09 BIOMASS FUELS↗

DOE OSTI2020

Multi-device study of temporal characteristics of magnetohydrodynamic modes initiating disruptions

Disruptions in tokamaks are often preceded by magnetohydrodynamic (MHD) instabilities that can rotate or become locked to the wall. Measurements from magnetic diagnostics in the presence of MHD mode precursors to disruptions can yield potentially valuable input to the plasma control system, with a view to disruption avoidance, prediction and mitigation. This report presents an exploratory analysis of the growth of MHD modes and corresponding time scales on the basis of magnetic measurements in multiple tokamaks. To this end, a database was compiled using disruptive discharges from COMPASS, ASDEX Upgrade, DIII-D and JET, manually classified according to disruption root cause, and characterized by a great diversity of operational conditions and mode dynamics. The typical time during which a mode can be detected using saddle coils and the duration of the locked mode phase in the database both extend over several orders of magnitude, but generally the time scales increase with plasma size. Several additional factors are discussed that can influence these durations, including the disruption root cause. A scaling law for the locked phase duration was estimated, yielding predictions toward ITER of the order of hundreds of milliseconds or even seconds. In addition, a scaling law for the mode amplitude at the disruption onset, proposed earlier by de Vries et al. (2016), is applied to the database, and its predictive capabilities are assessed. Despite significant uncertainty on the predictions from both scaling laws, encouraging trends are observed of the fraction of disruptions that may be detected with sufficient warning time to allow mitigation or even avoidance, based solely on observations of MHD mode dynamics. When combined with similar analysis of measurements from diagnostics that are sensitive to other disruption precursors, our analysis methods and results may contribute to the reliability, robustness and generalization of disruption warning schemes for ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids

Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Exploration of ICP platforms for measuring elemental impurities in uranium ore concentrates

Presented here is a look at different inductively coupled plasma (ICP) platforms including sector field, triple quadrupole mass spectrometric configurations, and optical emission spectroscopy. The goal of this paper was to convey the feasibility of trace elemental analysis of a uranium ore concentrate with varying ICP-based platforms. It was predicted that low mass elements would be better determined through optical means, or the mass collision/reaction technology of the triple quadrupole mass spectrometer, in comparison to high resolution measurements of magnetic sector-based configurations. Ultimately, it is difficult to achieve an “optimal” analysis of 20+ elements, for numerous samples, on a single platform, especially when time, measurement reproducibility, sensitivity, and robustness should be considered. The work presented here highlights the advantages and disadvantages of the respective trace elemental analysis platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

A panel analysis of groundwater use in California

We report groundwater is a relevant source of drinking and agricultural water in many regions of the world, but many aquifers have been unsustainably over-drafted and polluted. This has significant environmental, health, and economic implications. We rely on panel analysis, with small-sample corrections for cluster-robust variance estimation and hypothesis testing, to investigate the dynamics of groundwater extraction. We focus on California, yet our approach could be helpful to analyze the dynamics of groundwater extraction in other groundwater-reliant regions of the world. In California, over-reliance on groundwater has led to significant overdraft, affecting long-term water supply reliability and groundwater pumping costs. It further caused subsidence and infrastructure damage, harmed groundwater-dependent ecosystems, and threatened the sustainability of groundwater resources in the state. We use panel data of the 56 California Water Plan planning areas over the 1998–2015 period. We concentrate on agricultural and urban water use and the major water projects in the state, to provide a better understanding of the relationships between groundwater extraction and water use and supply. Results suggest that reducing agricultural water in Central California and urban water in Southern California could reduce groundwater extraction in these regions by approximately the same amount of the reduced water. Other opportunities to reduce the stress on the groundwater resources in the state are available for other regions, yet with lower benefits. Results also suggest that a decrease in deliveries from the Central Valley Project to the southern part of the Central Valley would increase groundwater extraction by approximately the same proportion. Changes in deliveries from the major water projects in the state, as well as from other sources of surface water, would also have some, yet lower impacts on groundwater extraction in the Central and Southern California.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Genome-scale phylogeny and comparative genomics of the fungal order Sordariales

The order Sordariales is taxonomically diverse, and harbours many species with different lifestyles and large economic importance. Despite its importance, a robust genome-scale phylogeny, and associated comparative genomic analysis of the order is lacking. In this study, we examined whole-genome data from 99 Sordariales, including 52 newly sequenced genomes, and seven outgroup taxa. We inferred a comprehensive phylogeny that resolved several contentious relationships amongst families in the order, and cleared-up intrafamily relationships within the Podosporaceae. Extensive comparative genomics showed that genomes from the three largest families in the dataset (Chaetomiaceae, Podosporaceae and Sordariaceae) differ greatly in GC content, genome size, gene number, repeat percentage, evolutionary rate, and genome content affected by repeat-induced point mutations (RIP). All genomic traits showed phylogenetic signal, and ancestral state reconstruction revealed that the variation of the properties stems primarily from within-family evolution. Together, the results provide a thorough framework for understanding genome evolution in this important group of fungi.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Quantifying Atomically Dispersed Catalysts Using Deep Learning Assisted Microscopy

The catalytic performance of atomically dispersed catalysts (ADCs) is greatly influenced by their atomic configurations, such as atom–atom distances, clustering of atoms into dimers and trimers, and their distributions. Scanning transmission electron microscopy (STEM) is a powerful technique for imaging ADCs at the atomic scale; however, most STEM analyses of ADCs thus far have relied on human labeling, making it difficult to analyze large data sets. Here, we introduce a convolutional neural network (CNN)-based algorithm capable of quantifying the spatial arrangement of different adatom configurations. The algorithm was tested on different ADCs with varying support crystallinity and homogeneity. Results show that our algorithm can accurately identify atom positions and effectively analyze large data sets. Here, this work provides a robust method to overcome a major bottleneck in STEM analysis for ADC catalyst research. We highlight the potential of this method to serve as an on-the-fly analysis tool for catalysts in future in situ microscopy experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Agricultural green revolution as a driver of increasing atmospheric CO2 seasonal amplitude

The atmospheric carbon dioxide (CO2) record displays a prominent seasonal cycle that arises mainly from changes in vegetation growth and the corresponding CO2 uptake during the boreal spring and summer growing seasons and CO2 release during the autumn and winter seasons. The CO2 seasonal amplitude has increased over the past five decades, suggesting an increase in Northern Hemisphere biospheric activity. It has been proposed that vegetation growth may have been stimulated by higher concentrations of CO2 as well as by warming in recent decades, but such mechanisms have been unable to explain the full range and magnitude of the observed increase in CO2 seasonal amplitude. Here we suggest that the intensification of agriculture (the Green Revolution, in which much greater crop yield per unit area was achieved by hybridization, irrigation and fertilization) during the past five decades is a driver of changes in the seasonal characteristics of the global carbon cycle. Our analysis of CO2 data and atmospheric inversions shows a robust 15 per cent long-term increase in CO2 seasonal amplitude from 1961 to 2010, punctuated by large decadal and interannual variations. Using a terrestrial carbon cycle model that takes into account high-yield cultivars, fertilizer use and irrigation, we find that the long-term increase in CO2 seasonal amplitude arises from two major regions: the mid-latitude cropland between 256N and 606N and the high-latitude natural vegetation between 506N and 706 N. The long-term trend of seasonal amplitude increase is 0.311 ± 0.027 percent per year, of which sensitivity experiments attribute 45, 29 and 26 per cent to land-use change, climate variability and change, and increased productivity due to CO2 fertilization, respectively. Vegetation growth was earlier by one to two weeks, as measured by the mid-point of vegetation carbon uptake, and took up 0.5 petagrams more carbon in July, the height of the growing season, during 2001–2010 than in 1961–1970, suggesting that human land use and management contribute to seasonal changes in the CO2 exchange between the biosphere and the atmosphere.

Zeng, Ning↗