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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 19 records

Detectability of Varied Hybridization Scenarios Using Genome-Scale Hybrid Detection Methods

Hybridization events complicate the accurate reconstruction of phylogenies, as they lead to patterns of genetic heritability that are unexpected under traditional, bifurcating models of species trees. This phenomenon has led to the development of methods to infer these varied hybridization events, both methods that reconstruct networks directly, as well as summary methods that predict individual hybridization events from a subset of taxa. However, a lack of empirical comparisons between methods – especially those pertaining to large networks with varied hybridization scenarios – hinders their practical use. Here, we provide a comprehensive review of popular summary methods: TICR, MSCquartets, HyDe, Patterson’s D-Statistic (ABBA-BABA), D3, and Dp. TICR and MSCquartets are based on quartet concordance factors gathered from gene tree topologies and HyDe, Patterson’s D-Statistic, D3, and Dp use site pattern frequencies to identify hybridization events between sets of three taxa. We then use simulated data to address questions of method accuracy and ideal use scenarios by testing methods against complex networks which depict gene flow events that differ in depth (timing), quantity (single vs. multiple, overlapping hybridizations), and rate of gene flow (γ). We find that deeper or multiple hybridization events may introduce noise and weaken the signal of hybridization, leading to higher relative false negative rates across all methods. Despite some forms of hybridization eluding quartet-based detection methods, MSCquartets displays high precision in most scenarios. While HyDe results in high false negative rates when tested on hybridizations involving extinct or unsampled ghost lineages, HyDe is the only method able to identify the direction of hybridization, distinguishing the source parental lineages from recipient hybrid lineages. Lastly, we test the methods on a dataset of ultraconserved elements from the bee subfamily Nomiinae, finding possible hybridization events between clades which correspond to regions of poor support in the species tree estimated in a previous study.

Bjorner, Marianne B.

Reassessing Hybrid Vigor or Hybrid Dysfunction Using Physiological Trade-Offs in an Endangered Salamander System

Fitness of interspecific hybrids can be higher or lower than that of their parental genotypes, with major ramifications for evolution and conservation. A recent study found that hybrid tiger salamanders had higher metabolic rates than their parental forms. Specifically, the ratio of resting metabolic rate to water loss, which was used as a measure of performance, was greater in hybrids. Recent genetic research showed that over half of the experimental subjects in that study were genetically pure California tiger salamanders (Ambystoma californiense) misclassified as hybrids. We reanalyzed the data using the corrected identification of hybrids and parentals. As expected, updating the classification revealed even stronger evidence for differences between hybrids and parentals. Hybrids had higher resting metabolic rates and greater water loss than parentals. The ratio of resting metabolic rate to water loss was also higher in hybrids. However, we suggest that this ratio might not be a positive measure of salamander performance. Higher metabolic rate means higher energy expenditure, and higher water loss suggests increased risk of desiccation. Both are major challenges for terrestrial amphibians, especially salamanders, which are hypothesized to be low-energy, low-water-loss specialists. Under this hypothesis, the ratio of energy expenditure to water loss is a ratio of two costs rather than a ratio of benefit to cost. While our analyses corroborate and strengthen the previous statistical results, we suggest that high resting metabolic rate is better interpreted as hybrid dysfunction, not vigor. Here, both hypotheses are speculative, and specific research on the fitness effects of these physiological differences is needed to resolve this important ecological question.

Ambystoma californiense

Insight and Evidence Motivating the Simplification of Dual-Analysis Hybrid Systems into Single-Analysis Hybrid Systems

Many hybrid data assimilation systems currently used for NWP employ some form of dual-analysis system approach. Typically a hybrid variational analysis is responsible for creating initial conditions for high-resolution forecasts, and an ensemble analysis system is responsible for creating sample perturbations used to form the flow-dependent part of the background error covariance required in the hybrid analysis component. In many of these, the two analysis components employ different methodologies, e.g., variational and ensemble Kalman filter. In such cases, it is not uncommon to have observations treated rather differently between the two analyses components; recentering of the ensemble analysis around the hybrid analysis is used to compensated for such differences. Furthermore, in many cases, the hybrid variational high-resolution system implements some type of four-dimensional approach, whereas the underlying ensemble system relies on a three-dimensional approach, which again introduces discrepancies in the overall system. Connected to these is the expectation that one can reliably estimate observation impact on forecasts issued from hybrid analyses by using an ensemble approach based on the underlying ensemble strategy of dual-analysis systems. Just the realization that the ensemble analysis makes substantially different use of observations as compared to their hybrid counterpart should serve as enough evidence of the implausibility of such expectation. This presentation assembles numerous anecdotal evidence to illustrate the fact that hybrid dual-analysis systems must, at the very minimum, strive for consistent use of the observations in both analysis sub-components. Simpler than that, this work suggests that hybrid systems can reliably be constructed without the need to employ a dual-analysis approach. In practice, the idea of relying on a single analysis system is appealing from a cost-maintenance perspective. More generally, single-analysis systems avoid contradictions such as having to choose one sub-component to generate performance diagnostics to another, possibly not fully consistent, component.

Todling, Ricardo

EMT-TS Hybrid Simulation for Large Power Grids Considering IBR-Driven Dynamics

The escalating integration of inverter-based resources (IBRs) poses new challenges to power systems by introducing fast dynamics with higher frequencies, which may need to be simulated by an electromagnetic transient (EMT) program. As an alternative to conducting EMT simulations for the entire system, which is typically time consuming, hybrid simulation between EMT and phasor-domain transient stability (TS) can greatly reduce the computational burden while preserving the detailed fast dynamics in the EMT zone. This paper establishes an EMT-TS hybrid simulation platform using open-source tools, specifically ParaEMT, GridPACK, and HELICS, which are the EMT simulator, TS simulator, and interface framework, respectively. Case studies on the 240-bus Western Electricity Coordinating Council (WECC) system demonstrate that the developed ParaEMT-HELICS-GridPACK hybrid simulator can accurately capture both slow electromechanical and fast IBR-driven dynamics with a 2.4x speedup.

electromagnetic transient

Existing Hydropower Assets (EHA) Annual Gross Generation Plant Database, 2003-2024

Existing Hydropower Asset (EHA) Annual Gross Generation is a geospatial point-level dataset containing annual gross generation over time (2003-2024) and key characteristics of operational U.S. pumped storage and hybrid plants with 1 megawatt or greater of nameplate capacity. EIA 923 and EHA are the primary sources of the derived data. Hydropower units are excluded.

Johnson, Megan [ORNL] (ORCID:0000000290141741)

Existing Hydropower Assets (EHA) Annual Net Generation Plant Database, 2003-2024

Existing Hydropower Asset (EHA) Annual Net Generation is a geospatial point-level dataset containing annual net generation over time (2003-2024) and key characteristics of operational U.S. hydropower plants with 1 megawatt or greater of nameplate capacity. EIA 923 and EHA are the primary sources of the derived data. Pumped storage and hybrid plants are excluded.

Johnson, Megan [ORNL] (ORCID:0000000290141741)

Hybrid Propulsion Demonstration Program 250K Hybrid Motor

The Hybrid Propulsion Demonstration Program (HPDP) program was formed to mature hybrid propulsion technology to a readiness level sufficient to enable commercialization for various space launch applications. The goal of the HPDP was to develop and test a 250,000 pound vacuum thrust hybrid booster in order to demonstrate hybrid propulsion technology and enable manufacturing of large hybrid boosters for current and future space launch vehicles. The HPDP has successfully conducted four tests of the 250,000 pound thrust hybrid rocket motor at NASA's Stennis Space Center. This paper documents the test series.

Story, George

Upcycling Polyethylene Waste into Hybrid Graphitic Porous Carbon Materials Used in High‐Performance Zinc‐Ion Hybrid Capacitors

Polyethylene (PE) waste is a challenge to upcycle into useful materials because this plastic tends to decompose into volatile compounds when heated at relatively low temperatures. In this work, mixtures of PE wastes into a hybrid graphitic porous carbon (HGPC) by a thermal oxidation pretreatment step, with assistance of an inert solid additive (KCl), to functionalize, crosslink, and stabilize the PE waste followed by carbonization and catalytic graphitization steps with a potassium carbonate catalyst, are upcycled. The PE waste‐derived HGPC (PW‐HGPC) has a hybrid structure composed of graphene‐like carbon nanosheets grown on the surface of carbon particles, high porosity with specific surface area, up to 1,763 m 2 g −1 , and good graphitic degree with average Raman I 2D / I G ratios of 0.53. When used as cathode material for zinc‐ion hybrid capacitors, this PW‐HGPC exhibits an excellent specific capacity, up to 126.7 mAh g −1 , at high mass loading of 10 mg cm −2 . Moreover, PW‐HGPC exhibits remarkable cycling stability with capacity retention of >94% after 10 000 cycles. Additionally, the KCl is recycled and reused over five times. This method provides a new solution for upcycling PE wastes into high value‐added carbon materials, not only for zinc‐ion hybrid capacitors but also for other electrochemical energy storage device applications.

hybrid graphitic porous carbon

Upcycling Polyethylene Waste Into Hybrid Graphitic Porous Carbon Materials Used in High-Performance Zinc-Ion Hybrid Capacitors

Polyethylene (PE) waste is a challenge to upcycle into useful materials because this plastic tends to decompose into volatile compounds when heated at relatively low temperatures. In this work, we report a chemical process that addresses this challenge by converting mixtures of linear low-density polyethylene (LLDPE), low-density polyethylene (LDPE), and high-density polyethylene (HDPE) waste into a hybrid graphitic porous carbon (HGPC) that can be used as a zinc-ion hybrid capacitor cathode. The process uses a low temperature thermal oxidation pre-treatment step, with assistance of an inert solid additive (KCl) to increase the effective surface area of the PE melt, to functionalize, cross-link, and stabilize the PE waste followed by carbonization and catalytic graphitization steps at higher temperatures with a potassium carbonate (K2CO3) catalyst. The PE waste derived HPGC (PW-HPGC) has a hybrid structure composed of graphene-like carbon nanosheets grown on the surface of carbon particles, high porosity with the Brunauer–Emmett–Teller (BET) specific surface area up to 1,763 m2g-1, and good graphitic degree with average Raman I2D/IG ratios of 0.53. When used as a cathode material for zinc-ion hybrid capacitors, this PW-HGPC exhibits an excellent specific capacity up to 126.7 mAhg-1 at high mass loading of 10 mgcm-2. Moreover, PW-HGPC exhibits remarkable cycling stability with capacity retention of >94% after 10,000 cycles at a current density of 2.0 A g-1.

hybrid graphitic porous carbon

Development of a Continuum Damage Mechanics Material Model of a Graphite-Kevlar(Registered Trademark) Hybrid Fabric for Simulating the Impact Response of Energy Absorbing Kevlar(Registered Trademark) Hybrid Fabric for Simulating the Impact Response of Energy Absorbing

This paper describes the development of input properties for a continuum damage mechanics based material model, Mat 58, within LS-DYNA(Registered Trademark) to simulate the response of a graphite-Kevlar(Registered Trademark) hybrid plain weave fabric. A limited set of material characterization tests were performed on the hybrid graphite-Kevlar(Registered Trademark) fabric. Simple finite element models were executed in LS-DYNA(Registered Trademark) to simulate the material characterization tests and to verify the Mat 58 material model. Once verified, the Mat 58 model was used in finite element models of two composite energy absorbers: a conical-shaped design, designated the "conusoid," fabricated of four layers of hybrid graphite-Kevlar(Registered Trademark) fabric; and, a sinusoidal-shaped foam sandwich design, designated the "sinusoid," fabricated of the same hybrid fabric face sheets with a foam core. Dynamic crush tests were performed on components of the two energy absorbers, which were designed to limit average vertical accelerations to 25- to 40-g, to minimize peak crush loads, and to generate relatively long crush stroke values under dynamic loading conditions. Finite element models of the two energy absorbers utilized the Mat 58 model that had been verified through material characterization testing. Excellent predictions of the dynamic crushing response were obtained.

Jackson, Karen E.

Self-regulating behavior of hybrid membrane systems as demonstrated in an element-scale forward osmosis-reverse osmosis hybrid system

Hybrid membrane systems can be difficult to design due to the requisite flow rate matching between up- and downstream unit operations. In this work, we use a forward osmosis-reverse osmosis (FO-RO) hybrid system to demonstrate how some membrane systems can exhibit self-regulating behavior due to osmotic coupling. This can reduce the need for complex control systems for flow balancing. We show this behavior using a module-scale test bed that can mimic the behavior of larger scale operations. The system shows permeate flow rate near-convergence between the FO and RO modules after startup or when perturbed by a change in RO module pressure. The behavior of this hybrid system demonstrates that some membrane operations can exploit osmotic interdependence, rather than expensive control systems, to achieve steady state operation.

Debottlenecking

Hybrid rocket propulsion <la propulsion par fusees hybrides<

The aim of the first part of this article is to demonstrate the potentialities of hybrids in the space program. These potentialities are applicable to all three main classes of chemical rockets currently in use, namely: (1) storable -propellant rockets, (2) cryogenic-propellant rockets, and (3) semistorable-propellant rockets, where the non-storable element is introduced at the time of firing. On the basis of these three categories, the properties of hybrid systems are discussed in relation to the specific impulse. The hybrid method of propulsion is compared with standard solid- and liquid-propellant propulsion systems. The second part of the article is concerned with the fundamental problems of combustion, the emphasis being placed on the rate of regression of the solid phase, which determines the performance of the system. Different theories of the regression rate are described and compared with various experimental results.

Cryogenic propellant

Development and Lab-Scale Testing of a Gas Generator Hybrid Fuel in Support of the Hydrogen Peroxide Hybrid Upper Stage Program

As part of a NASA funded contract to develop and demonstrate a gas generator cycle hybrid rocket motor for upper stage space motor applications, the development and demonstration of a low sensitivity, high performance fuel composition was undertaken. The ultimate goal of the development program was to demonstrate successful hybrid operation (start, stop, throttling) of the fuel with high concentration (90+%) hydrogen peroxide. The formulation development and lab-scale testing of a simple DOT Class 1.4c gas generator propellant is described. Both forward injected center perforated and aft injected end burner hybrid combustion behavior were evaluated with gaseous oxygen and catalytically decomposed 90% hydrogen peroxide. Cross flow and static environments were found to yield profoundly different combustion behaviors, which were further governed by binder type, oxidizer level and, significantly, oxidizer particle size. Primary extinguishment was accomplished via manipulation of PDL behavior and oxidizer turndown, which is enhanced with the hydrogen peroxide system. Laboratory scale combustor results compared very well with 11-inch and 24-inch sub-scale test results with 90% hydrogen peroxide.

Lund, Gary K.

Comparison of Real-Time Pressure Rail Selection Algorithms for the Hybrid Hydraulic Electric Architecture: Case Study on a Track Loader

Abstract The hybrid hydraulic electric architecture (HHEA) seeks to combine the high power/torque/force density of hydraulics with the efficiency of electric machines. A set of common pressure rails is used to provide a majority of the power and this power is modulated by small electric machines to provide precise control for the operator. The HHEA has been studied in previous work using off-line dynamic programming optimization to determine energy efficient pressure rail selections, but this approach requires drive cycle information apriori. A Lagrange multiplier method has also been investigated where a set of gains (Lagrange multipliers) are optimized off-line with the idea the these gains, once determined, could be used for real-time operation. In this work, three new real-time pressure rail selection algorithms that do not require future drive cycle information are investigated; greedy, torque minimizing, and thresholding. The greedy control is found to only use 1% more energy than the globally optimal dynamic programming solution; but a model of energy loss is required.

24 POWER TRANSMISSION AND DISTRIBUTION

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML