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Results for “Realizability Analysis”

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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Quantifying and Reducing Uncertainty in Correlated Multi-Area Short-Term Load Forecasting

In this study, we represent and reduce the uncertainties in short-term electric load forecasting by integrating time series analysis tools including ARIMA modeling, sequential Gaussian simulation, and principal component analysis. The approaches are mainly focusing on maintaining the inter-dependency between multiple geographically related areas. These approaches are applied onto cross-correlated load time series as well as their forecast errors. Multiple short-term prediction realizations are then generated from the reduced uncertainty ranges, which are useful for power system risk analyses.

load forecast↗
DOE OSTI2021

Functional Principal Component Analysis of Radio–Optical Reference Frame Tie

The Gaia optical reference frame is intrinsically undefined with respect to global orientation and spin, so it needs to be anchored in the radio-based International Celestial Reference Frame (ICRF) to provide a referenced and quasi-inertial celestial coordinate system. The link between the two fundamental frames is realized through two samples of distant extragalactic sources, mostly active galactic nuclei and quasars, but only the smaller sample of radio-loud ICRF sources with optical counterparts is available to determine the mutual orientation. The robustness of this link can be mathematically formulated in the framework of functional principal component analysis using a set of vector spherical harmonics to represent the differences in celestial positions of the common objects. The weakest eigenvectors are computed, which describe the greatest deficiency of the link. The deficient or poorly determined terms are specific vector fields on the sphere that carry the largest errors of absolute astrometry using Gaia in reference to the ICRF. This analysis provides guidelines for the future development of the ICRF maximizing the accuracy of the link over the entire celestial sphere. A measure of the robustness of a least-squares solution, which can be applied to any linear model fitting problem, is introduced to help discriminate between reference frame tie models of different degrees.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

ONRAMP, ORNL Nuclear Resources Analysis and Modeling Portfolio

Many teams from US and international organizations, government, industry, research organizations, and academic institutions have established near-term technical exchanges and long-term partnerships with ORNL, realizing previously unforeseen innovations and efficiencies. Through ONRAMP, we invite you to learn more about the rich resources available at ORNL that can enhance your current approaches. Learn what is possible using customized, advanced techniques.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1973

A simplified signal analysis technique for obtaining optimal estimates of system dynamics

A procedure is presented which provides an algorithm for the special case where the unknown system has n inputs, and n finite length realizations for each of the n input signals are available. Given an n input system and n experimental records for each input, it is shown that the optimum Wiener filter is easily computed using only the experimental data. No assumptions concerning the analytical structure of the spectral matrix are necessary.

Whitbeck, R. F.↗
DOE OSTI2020

The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support

Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of researchers and practitioners revisit the current status of SA, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems. Six areas are discussed that warrant further attention, including (1) structuring and standardizing SA as a discipline, (2) realizing the untapped potential of SA for systems modeling, (3) addressing the computational burden of SA, (4) progressing SA in the context of machine learning, (5) clarifying the relationship and role of SA to uncertainty quantification, and (6) evolving the use of SA in support of decision making. An outlook for the future of SA is provided that underlines how SA must underpin a wide variety of activities to better serve science and society.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network↗
DOE OSTI2021

Advanced mass balance characterization and fractionation of algal biomass composition

Abstract Opportunities associated with biomass production and bioproduct isolation from algae-derived feedstocks are plentiful and promising; however, there are challenges associated with realizing these applications. One of the most important, and often overlooked, challenges is the lack of availability of a strong foundation of compositional analysis methods validated on microalgal biomass. Currently, compositional analysis in algae is dominated by the use of interference-prone methods, a lack of full mass balance accounting, and the use of top-down approaches that bin all unaccounted-for mass into a single category, such as carbohydrates. We present here an approach based on a bottom-up algal biomass characterization aimed at moving towards, and highlighting the importance of, full and accurate mass closure to achieve the maximum economic potential from a sustainable and renewable feedstock. Algal biomass representing three genera, Nannochloropsis , Scenedesmus , and Monoraphidium , was subjected to a cell rupture and fractionation process, followed by detailed characterization of each fraction to determine the partitioning of measured and unknown components. The goal of this work is to identify where the missing components partition, and develop a strategy to close the mass balance or identify the unknowns, while utilizing a rigorous characterization approach for characterizing algal biomass. Although only 75–80% of the biomass was accounted for, the fractionation approach utilized here provides key insight into possible chemical components for future investigations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

An (adjustable RN)-based multi-OLT PON and the dynamic programming algorithm for downstream channel

In this paper, a multiple optical line terminal (OLT) passive optical network (PON) and the dynamic programming algorithm for downstream channel is proposed. By wavelength-selectable module, the adjustable remote node (RN) is constructed. By this adjustable RN, a simple and efficient multi-OLT PON is designed. By the way of first-plan and then-load, optical network unit (ONU) groups are established in order to realize the fast loading of ONUs. Specially, by introducing dynamic programming algorithm, the wavelength bandwidth utilization is maximized. Finally, by the simulation and analysis, the effectiveness of the proposed scheme is demonstrated.

42 ENGINEERING↗
DOE OSTI2019

Canonical scalar field inflation with a Woods–Saxon potential

This paper focuses on the realization of an inflationary model from a canonical scalar field theory with a Woods–Saxon potential, in the slow-roll approximation. Our analysis indicates that the observable quantities derived theoretically from our model, namely the spectral index of the primordial scalar curvature perturbations and the tensor-to-scalar ratio, are compatible with the latest Planck collaboration data. We also discuss the qualitative features of the potential, and we show that the value of the scalar field for which the graceful exit occurs, coincides with the inflection point of the scalar potential. We also attempt to study the post-inflation reheating phase of the model, in order to further examine the viability of the Woods–Saxon scalar field model, and as we demonstrate the results indicate viability of the model for this era too, however the instantaneous reheating is not allowed for the model at hand.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Bicontinuous substrates with reduced pore restriction for CO 2 -selective composite membranes

A substrate with bicontinuous structure is attractive for thin-film composite (TFC) membrane synthesis due to its high surface porosity and well-interconnected bulk morphology. In this study, the vapor-induced phase separation (VIPS) of the casting solution comprising water, 2-pyrrolidone, and polyethersulfone (PES) was studied. By tuning the water addition in the casting solution and water vapor exposure time, the optimized substrate exhibited a bicontinuous surface with a high porosity of 24.2% (or 216/µm 2 pore density), thereby mitigating pore restriction and showing a high CO 2 permeance of 2.94×10 5 GPU. Compared to the benchmark PES substrate with cellular surface pores and lower gas permeance, the use of the bicontinuous substrate led to a 12% increase in the CO 2 permeance of the TFC membrane. The mitigated pore restriction was further rationalized by a resistance-in-series model. The analysis of the lateral diffusion and substrate resistances indicates that an even higher surface pore density of the substrate is required to fully realize the potential of ultra-permeable, CO 2 -selective polymers in the TFC configuration. As a result, the scalability of the VIPS process was demonstrated by the roll-to-roll fabrication of the optimized bicontinuous substrate with a width of 21" and a length of >100'.

42 ENGINEERING↗
DOE OSTI2019

High temperature singlet-based magnetism from Hund’s rule correlations

Uranium compounds can manifest a wide range of fascinating many-body phenomena, and are often thought to be poised at a crossover between localized and itinerant regimes for 5f electrons. The antiferromagnetic dipnictide USb 2 has been of recent interest due to the discovery of rich proximate phase diagrams and unusual quantum coherence phenomena. Here, linear-dichroic X-ray absorption and elastic neutron scattering are used to characterize electronic symmetries on uranium in USb 2 and isostructural UBi 2 . Of these two materials, only USb 2 is found to enable strong Hund’s rule alignment of local magnetic degrees of freedom, and to undergo distinctive changes in local atomic multiplet symmetry across the magnetic phase transition. Theoretical analysis reveals that these and other anomalous properties of the material may be understood by attributing it as the first known high temperature realization of a singlet ground state magnet, in which magnetism occurs through a process that resembles exciton condensation.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Atomic structure of defects and interfaces in TiO 2 -B and Ca:TiO 2 -B (CaTi 5 O 11 ) films grown on SrTiO 3

The bronze polymorph of titanium dioxide, TiO 2 -B, characterized by a crystal structure with a relatively open layered geometry, is a material of interest for various energy applications, including photovoltaics, catalysts, and high-rate energy storage devices. The related phase, CaTi 5 O 11 , which serves as an effective template layer, when deposited on (100) SrTiO 3 , for the growth of high quality single crystalline films of TiO 2 -B, is also of interest for such applications. For both materials, a detailed understanding of the film growth and defect structure is deemed critical to the successful realization of these applications in thin film devices. Thus, using results obtained with aberration-corrected transmission electron microscopy, we present here an analysis of the defects and interfacial structure in CaTi 5 O 11 films grown on (100) and (110) SrTiO 3 substrates, as well as in the TiO 2 -B film grown on (001) CaTi 5 O 11 .

36 MATERIALS SCIENCE↗
DOE OSTI2015

Broadband nanophotonic waveguides and resonators based on epitaxial GaN thin films

We demonstrate broadband, low loss optical waveguiding in single crystalline GaN grown epitaxially on c-plane sapphire wafers through a buffered metal-organic chemical vapor phase deposition process. High Q optical microring resonators are realized in near infrared, infrared, and near visible regimes with intrinsic quality factors exceeding 50 000 at all the wavelengths we studied. TEM analysis of etched waveguide reveals growth and etch-induced defects. Reduction of these defects through improved material and device processing could lead to even lower optical losses and enable a wideband photonic platform based on GaN-on-sapphire material system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Perspective: Reproducible Coherence Characterization of Superconducting Quantum Devices

As the field of superconducting quantum computing approaches maturity, optimization of single-device performance is proving to be a promising avenue towards large-scale quantum computers. However, this optimization is possible only if performance metrics can be accurately compared among measurements, devices, and laboratories. Currently such comparisons are inaccurate or impossible due to understudied errors from a plethora of sources. In this Perspective, we outline the current state of error analysis for qubits and resonators in superconducting quantum circuits, and discuss what future investigations are required before superconducting quantum device optimization can be realized.

McRae, Corey H.↗
DOE OSTI2017

Optimized clustering estimators for BAO measurements accounting for significant redshift uncertainty

Here, we determine an optimized clustering statistic to be used for galaxy samples with significant redshift uncertainty, such as those that rely on photometric redshifts. To do so, we study the baryon acoustic oscillation (BAO) information content as a function of the orientation of galaxy clustering modes with respect to their angle to the line-of-sight (LOS). The clustering along the LOS, as observed in a redshift-space with significant redshift uncertainty, has contributions from clustering modes with a range of orientations with respect to the true LOS. For redshift uncertainty $\sigma_z \geq 0.02(1+z)$ we find that while the BAO information is confined to transverse clustering modes in the true space, it is spread nearly evenly in the observed space. Thus, measuring clustering in terms of the projected separation (regardless of the LOS) is an efficient and nearly lossless compression of the signal for $\sigma_z \geq 0.02(1+z)$. For reduced redshift uncertainty, a more careful consideration is required. We then use more than 1700 realizations (combining two separate sets) of galaxy simulations mimicking the Dark Energy Survey Year 1 sample to validate our analytic results and optimized analysis procedure. We find that using the correlation function binned in projected separation, we can achieve uncertainties that are within 10 per cent of those predicted by Fisher matrix forecasts. We predict that DES Y1 should achieve a 5 per cent distance measurement using our optimized methods. We expect the results presented here to be important for any future BAO measurements made using photometric redshift data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Kingdom-Wide Analysis of Fungal Protein-Coding and tRNA Genes Reveals Conserved Patterns of Adaptive Evolution

Protein-coding genes evolved codon usage bias due to the combined but uneven effects of adaptive and nonadaptive influences. Studies in model fungi agree on codon usage bias as an adaptation for fine-tuning gene expression levels; however, such knowledge is lacking for most other fungi. Our comparative genomics analysis of over 450 species supports codon usage and transfer RNAs (tRNAs) as coadapted for translation speed and this is most likely a realization of convergent evolution. Rather than drift, phylogenetic reconstruction inferred adaptive radiation as the best explanation for the variation of interspecific codon usage bias. Although the phylogenetic signals for individual codon and tRNAs frequencies are lower than expected by genetic drift, we found remarkable conservation of highly expressed genes being codon optimized for translation by the most abundant tRNAs, especially by inosine-modified tRNAs. As an application, we present a sequence-to-expression neural network that uses codons to reliably predict highly expressed transcripts. The kingdom Fungi, with over a million species, includes many key players in various ecosystems and good targets for biotechnology. Collectively, our results have implications for better understanding the evolutionary success of fungi, as well as informing the biosynthetic manipulation of fungal genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Entangled phase of simultaneous fermion and exciton condensations realized

Fermion-exciton condensates (FECs)—computationally and theoretically predicted states that simultaneously exhibit the character of superconducting states and exciton condensates—are novel quantum states whose properties may involve a hybridization of superconductivity and the dissipationless flow of energy. Here, we exploit prior investigations of superconducting states and exciton condensates on quantum devices to identify a tuneable quantum state preparation entangling the wave functions of the individual condensate states. Utilizing this state preparation, we prepare a variety of FEC states on quantum computers—realizing strongly correlated FEC states on current, noisy intermediate-scale quantum devices—and verify the presence of the dual condensate via postmeasurement analysis. This confirmation of the previously predicted condensate state on quantum devices as well as the form of its wave function motivates further theoretical and experimental exploration of the properties, applications, and stability of FECs.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Orbital selective directional conductor in the two-orbital Hubbard model

Recently, we employed a developed many-body technique that allows for the incorporation of thermal effects, the rich phase diagram of a two-dimensional two-orbital (degenerate d xz and d yz ) Hubbard model is presented varying temperature and the repulsion U. The main result is the finding at intermediate U of an antiferromagnetic orbital selective state where an effective dimensional reduction renders one direction insulating and the other metallic. Possible realizations of this state are discussed. Additionally, we also study nematicity above the N eel temperature. After a careful finite-size scaling analysis, the nematicity temperature window appears to survive in the bulk limit, although it is very narrow.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗