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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Three-point energy correlators in hadronic Higgs boson decays

We present the analytic calculation of the leading-order three-point energy correlator (EEEC) in hadronic Higgs decays, including both the gluon-initiated channel H → g g + X and quark-initiated channel H → q q ¯ + X . The phase-space integration is evaluated directly using Mandelstam variables s i j = ( p i + p j ) 2 , and the appearing square roots can be rationalized by either conformal ratios or celestial coordinate variables. Throughout the calculation, we observe the same transcendental function space as in N = 4 super–Yang-Mills theory and e + e − → hadrons . Different infrared limits are also explored using the full analytic result, offering the fixed-order data for EEEC factorization and resummation. Given its nontrivial shape dependence, the EEEC presents an excellent opportunity to explore the dynamics of gluon jets originating from the H → g g decay channel at future lepton colliders. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2016

Off-shell hydrodynamics from holography

In this article, we outline a program for obtaining an action principle for dissipative fluid dynamics by considering the holographic Wilsonian renormalization group applied to systems with a gravity dual. As a first step, in this paper we restrict to systems with a non-dissipative horizon. By integrating out gapped degrees of freedom in the bulk gravitational system between an asymptotic boundary and a horizon, we are led to a formulation of hydrodynamics where the dynamical variables are not standard velocity and temperature fields, but the relative embedding of the boundary and horizon hypersurfaces. At zeroth order, this action reduces to that proposed by Dubovsky et al. as an off-shell formulation of ideal fluid dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Statistical Optimization of Polyhydroxybutyrate Production by Bacillus Pumilus H9 Using Cow Dung as a Cheap Carbon Source by Response Surface Methodology

A gram positive bacterium (designated strain H9) found to be a potential polyhydroxybutyrate (biodegradable polymer) producer was isolated from the soil samples of a stress prone environment (municipal waste areas). This bacterium was identified as Bacillus pumilus H9 from its morphological, physiological and 16S rRNA gene sequence analysis. A four-factor central composite rotary design was employed to optimize the medium and to find out the interactive effects of four variables, viz. concentrations of cow dung, sucrose, peptone and pH on PHB production. Using response surface methodology, a second-order polynomial equation was obtained by multiple regression analysis and a yield of 2.47 g/L of PHB dry weight was achieved from the optimized medium at pH 7. Here, we report cow dung as a cheap carbon source for the production of PHB. Further, phbA, phbB and phbC genes were amplified by polymerase chain reaction which confirms the bacterium to be able to produce polyhydroxybutyrate.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Prym Differentials on Variable Tori

We consider multiplicative functions and Prym differentials on variable tori. We prove counterparts of the theorem on the total sum of residues for Prym differentials of any integer order on tori. As a consequence, reciprocity laws are proved. We construct elementary Prym differentials of all kinds with any integer order which holomorphically depend on the moduli of tori and characters. We derive an analogue of the Appell decomposition formula for functions with characters. We also study vector bundles of Prym differentials of any integer order over the product of Teichmueller spaces for a torus and a group of characters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A behavioral choice model of the use of car-sharing and ride-sourcing services

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing and car-sharing services, this paper presents a bivariate ordered probit model estimated on a survey data set derived from the 2014-2015 Puget Sound Regional Travel Study. Model estimation results show that users of these services tend to be young, well-educated, higher-income, working individuals residing in higher-density areas. There are significant interaction effects reflecting the influence of children and the built environment on disruptive mobility service usage. The model developed in this paper provides key insights into factors affecting market penetration of these services, and can be integrated in larger travel forecasting model systems to better predict the adoption and use of mobility-on-demand services.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Derivative-based SINDy (DSINDy): Addressing the challenge of discovering governing equations from noisy data

Recent advances in the field of data-driven dynamics allow for the discovery of ODE systems using state measurements. One approach, known as Sparse Identification of Nonlinear Dynamics (SINDy), assumes the dynamics are sparse within a predetermined basis in the states and finds the expansion coefficients through linear regression with sparsity constraints. This approach requires an accurate estimation of the state time derivatives, which is not necessarily possible in the high-noise regime without additional constraints. We present an approach called Derivative-based SINDy (DSINDy) that combines two novel methods to improve ODE recovery at high-noise levels. First, we denoise the state variables by applying a projection operator that leverages the assumed basis for the system dynamics. Second, we use a second order cone program (SOCP) to find the derivative and governing equations simultaneously. We derive theoretical results for the projection-based denoising step, which allow us to estimate the values of hyperparameters used in the SOCP formulation. This underlying theory helps limit the number of required user-specified parameters. Finally, we present results demonstrating that our approach leads to improved system recovery for the Van der Pol oscillator, the Duffing oscillator, the Rössler attractor, and the Lorenz 96 model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Isolation and characterization of a virus infecting the freshwater algae Chrysochromulina parva

Water samples from Lake Ontario, Canada were tested for lytic activity against the freshwater haptophyte algae Chrysochromulina parva. A filterable lytic agent was isolated and identified as a virus via transmission electron microscopy and molecular methods. The virus, CpV-BQ1, is icosahedral, ca. 145 nm in diameter, assembled within the cytoplasm, and has a genome size of ca. 485 kb. Sequences obtained through PCR-amplification of DNA polymerase (polB) genes clustered among sequences from the family Phycodnaviridae, whereas major capsid protein (MCP) sequences clustered among sequences from either the Phycodnaviridae or Mimiviridae. Based on quantitative molecular assays, C. parva's abundance in Lake Ontario was relatively stable, yet CpV-BQ1's abundance was variable suggesting complex virus-host dynamics. This study demonstrates that CpV-BQ1 is a member of the proposed order Megavirales with characteristics of both phycodnaviruses and mimiviruses indicating that, in addition to its complex ecological dynamics, it also has a complex evolutionary history. - Highlights: • A virus infecting the algae C. parva was isolated from Lake Ontario. • Virus characteristics demonstrated that this novel virus is an NCLDV. • The virus's polB sequence suggests taxonomic affiliation with the Phycodnaviridae. • The virus's capsid protein sequences also suggest Mimiviridae ancestry. • Surveys of host and virus natural abundances revealed complex host–virus dynamics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Transformation of Structure, Electrical Conductivity, and Magnetism in AA'Fe 2 O 6-δ , A = Sr, Ca and A' = Sr

The ability to control electrical properties and magnetism by varying the crystal structure using the effect of the A-site cation in oxygen-deficient perovskites has been studied in AA’Fe 2 O 6-δ , where A=Sr, Ca and A’= Sr. The structure of Sr 2 Fe 2 O 6-δ , synthesized at 1250 °C in air, contains dimeric units of FeO 5 square-pyramids separated by FeO 6 octahedra. Here we show that this ordering scheme can be transformed by changing the A-site cations from Sr to Ca. This leads to a structure where layers of corner-sharing FeO 6 octahedra are separated by chains of FeO 4 tetrahedra. Through systematic variation of the A-site cations, we have determined the average ionic radius required for this conversion to be ~1.41 Å. We have demonstrated that the magnetic structure is also transformed. The Sr 2 compound has an incommensurate magnetic structure, where magnetic moments are in spin-density wave state, aligning perpendicular to the body diagonal of the unit cell. With the aid of neutron diffraction experiments at 10 K and 300 K, we have shown that the magnetic structure is converted into a long-range G-type antiferromagnetic system when one Sr is replaced by Ca. In this G-type ordering scheme, the magnetic moments align in the 001 direction, antiparallel to their nearest neighbors. We have also performed variable-temperature electrical conductivity studies on these materials in the temperature range 298 – 1073 K. These studies have revealed the transformation of charge transport properties, where the metallic behavior of the Sr 2 -compound is converted into semiconductivity in the CaSr-material. The trend of conductivity as a function of temperature is reversed upon changing the A-site cation. The conductivity of the Sr 2 compound shows a downturn, while the conductivity of the CaSr material increases as a function of temperature. We have also shown that the CaSr-compound exhibits temperature-dependent behavior typical of a mixed ionic-electronic conducting system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A coherent discrete variable representation method on a sphere

Here, the coherent discrete variable representation (ZDVR) has been extended for construct- ing a multidimensional potential-optimized DVR basis on a sphere. In order to deal with the non-constant Jacobian in spherical angles, two direct product primitive basis methods are proposed so that the original ZDVR technique can be properly implemented. The method has been demonstrated by computing the lowest states of a two dimensional (2D) vibrational model. Results show that the extended ZDVR method gives accurate eigenval- ues and exponential convergence with increasing ZDVR basis size.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Influence of nuclear quantum effects on the electronic properties of amorphous carbon

We carry out quantum simulations to study the physical properties of diamond-like amorphous carbon by coupling first-principles molecular dynamics with a quantum thermostat, and we analyze multiple samples representative of different defective sites present in the disordered network. We show that quantum vibronic coupling is critical in determining the electronic properties of the system, in particular its electronic and mobility gaps, while it has a moderate influence on the structural properties. We find that despite localized electronic states near the Fermi level, the quantum nature of the nuclear motion leads to a renormalization of the electronic gap surprisingly similar to that found in crystalline diamond. We also discuss the notable influence of nuclear quantum effects on band-like and variable-hopping mechanisms contributing to electrical conduction. Our calculations indicate that methods often used to evaluate electron–phonon coupling in ordered solids are inaccurate to study the electronic and transport properties of amorphous semiconductors composed of light atoms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Instability in interacting dark sector: an appropriate holographic Ricci dark energy model

In this paper we investigate the consequences of phantom crossing considering the perturbative dynamics in models with interaction in their dark sector. By mean of a general study of gauge-invariant variables in comoving gauge, we relate the sources of instabilities in the structure formation process with the phantom crossing. In order to illustrate these relations and its consequences in more detail, we consider a specific case of an holographic dark energy interacting with dark matter. We find that in spite of the model is in excellent agreement with observational data at background level, however it is plagued of instabilities in its perturbative dynamics. We reconstruct the model in order to avoid these undesirable instabilities, and we show that this implies a modification of the concordance model at background. Also we find drastic changes on the parameters space in our model when instabilities are avoided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms

The emergent practical applicability of the Quantum Approximate Optimization Algorithm (QAOA) for approximate combinatorial optimization is a subject of considerable interest. One of the primary limitations of QAOA is the task of finding a set of good parameters, which is usually done using a variational optimization loop. Parameter transfer, or parameter concentration, is a phenomenon where QAOA angles trained on problem instances that are self-similar tend to perform well for other problem instances from that similar class. This suggests a potentially highly efficient and scalable non-variational learning method for QAOA angle finding. In this work, we systematically study QAOA parameter transferability from small problem sizes (16 and 27 decision variables) onto large problem instances (up to 156 qubits) for heavy-hex graph Ising models with geometrically local higher order terms using the Julia based QAOA simulation tool \texttt{JuliQAOA} to perform classical angle finding for up to $49$ QAOA layers ($p$). Parameter transfer of the fixed angles is validated using a combination of full statevector, Projected Entangled Pair States (PEPS), Matrix Product State (MPS), and LOWESA numerical simulations. We find that the QAOA parameter transfer from single instances applied to other (unseen) problem instances does not in general provide monotonically improving performance as a function of $p$ - there are many cases where the performance temporarily decreases as a function of $p$ - but despite this the transferred angles have a general trend of improved expectation value as the QAOA depth increases, in many cases converging close to the true ground-state energy of the $100+$ qubit instances. We also sample the hardware-compatible Ising models using the ensemble of transfer-learned QAOA parameters on several superconducting qubit IBM Quantum processors with 127, 133, and 156 qubits. We find continuous solution quality improvement of the hardware-compatible QAOA circuits run on the IBM NISQ processors up to $p=5$ on \texttt{ibm\_fez}, up to $p=9$ on \texttt{ibm\_torino}, and up to $p=10$ on \texttt{ibm\_pittsburgh}.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Estimating the Contributions to Human Error Probability from the Convolution of the Distribution of Time Available and Time Required

As part of their duties, Human Reliability Analysis must often evaluate if crews in nuclear power plants (NPPs) can complete tasks associated with a human-failure event within time limits. For example, the time required in NPP scenarios is determined by systematic and structured walkthroughs, feasibility studies, recorded times from training exercises, and interviews with experienced operators and experts. Typically, a point estimate is derived for the estimate (mean, maximum, or 95th percentile of time required). Using point-estimate values can mask the risk associated with variability among crews, plant conditions and set-up, environmental conditions, and other impact factors under which these actions are executed. While point estimates for time required and time available have served the industry well, without considering the uncertainty they could lead to biased understanding about the risk. The Integrated Human Event Analysis System - General Methodology (IDHEAS-G) model (developed by the US Nuclear Regulatory Commission, NRC) for human error probability calculates human error probability by summing two probabilities: insufficient time and cognitive error. As such, the model takes a more holistic approach by considering the full distributions for time required and time available to calculate the human error probability because the time available to complete the task is insufficient. In this study, we expand on the work of the NRC and discuss methods for estimating these time considerations. For example, for the time required, the impact of Performance Influencing Factors (PIFs) on the distribution was divided into impacts that are aleatory in nature, such as crew-to-crew variability, and those that are epistemic (i.e., the PIFs). Starting with the factors that introduce aleatory uncertainty, a first-order distribution was developed from a large set of time required (i.e., NPP task completion times) data for the range of operator actions that occur in the NPP control room under simulated accident conditions. The first-order distribution can then be adjusted to account for epistemic uncertainty using research associated with the impact of applicable PIFs on the time required. We also develop guidance for analysts to address the probability distributions for the time available. The guidance we developed on how to estimate time required and time available distributions is based on the identification of pertinent research and data, data analyses, and expert knowledge elicitation.

human error probability, human performance, time e↗
DOE OSTI2024

Scale-Bridging Optimization Framework for Desalination Integrated Produced Water Networks

In this work, we develop a Pyomo-based non-linear optimization strategy that includes rigorous MVR models. The detailed desalination unit is integrated into the multiperiod produced water network problem using the trust region filter (TRF) method. TRF decomposes the integrated problem into a master problem consisting of the network variables and a simplified surrogate model for the detailed desalination unit. The surrogate is updated using zero and first-order corrections from the optimal solution of the detailed models at every iteration. This framework allows us to co-optimize the design of the desalination units and operating policy for the multiperiod network. A common design is ensured across all periods using global capacity constraints. We validate the solution obtained using the TRF method by solving the full integrated problem for small network instances and show our results on real case studies on produced water networks from the Permian and Appalachian basins. In this work, we describe our TRF formulation, give details on our implementation in Pyomo, and analyze the results obtained by solving the optimization problem using IPOPT. We also present a discussion on the computational efficiency and scaling using the TRF approach against a full-scale integration of the rigorous models within the water network.

Naik, Sakshi↗
DOE OSTI2018

Heat Transfer Analysis of Solar Air Heating System for Different Tilt Angles

Solar Air Heater is a simple, cheap and most widely used for various applications such as textile industries, agricultural, desalination and space heating. Generally collectors are tilted so as to absorb maximum radiation, so it is necessary to calculate the optimum tilt angle to maximize the solar radiation falling on the collector area to gain maximum useful energy. The maximum solar radiation can be collected by using a tracking mechanism. Tracking systems are expensive and complicated in construction. The working operation of solar integrated tracking system is difficult. This paper presents the mechanism of evaluating the overall heat transfer coefficient of the solar air-heater at variable intensities and inlet velocities. The experimental setup is integrated with blower at inlet to the solar air heater in order to pump air at different velocities. The work focus on comparative study of solar air heating system for different tilt angles ranging from 250 to 600 and determines the overall heat transfer coefficient so as to find the optimum tilt angle of a solar flat plate collector.

14 SOLAR ENERGY↗
DOE OSTI2024

Probabilistic Assessment of Structural Integrity

A probability-based approach, combining deterministic and probabilistic methods, was developed for analyzing building and component failures, which are especially crucial for complex structures like nuclear power plants. This method links finite element and probabilistic software to assess structural integrity under static and dynamic loads. This study uses NEPTUNE software, which is validated, for a deterministic transient analysis and ProFES software for probabilistic models. In a case study, deterministic analyses with varied random variables were transferred to ProFES for probabilistic analyses of piping failure and wall damage. A Monte Carlo Simulation, First-Order Reliability Method, and combined methods were employed for probabilistic analyses under severe transient loading, focusing on a postulated accident at the Ignalina Nuclear Power Plant. The study considered uncertainties in material properties, component geometry, and loads. The results showed the Monte Carlo Simulation method to be conservative for high failure probabilities but less so for low probabilities. The Response Surface/Monte Carlo Simulation method explored the impact load–failure probability relationship. Given the uncertainties in material properties and loads in complex structures, a deterministic analysis alone is insufficient. Probabilistic analysis is imperative for extreme loading events and credible structural safety evaluations.

Mathematics↗