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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

The Linear Point Standard Ruler with DESI DR1 and DR2 Data

The linear point, a purely geometric feature in the monopole of the two-point correlation function, has been proposed as an alternative standard ruler. Compared to the peak in the correlation function, it is more robust to late-time nonlinear effects at the percent level. In light of improved simulations and high quality data, we revisit the robustness of the linear point and use it as an alternative to template-based fitting approaches typically used in BAO analyses. We present the linear point measurements on galaxy samples from the first and second data releases (DR1 and DR2) of the DESI survey. We convert the linear point into a dimensionless parameter $α_{iso,LP}$, defined as the ratio of the linear point in the fiducial cosmology and the observed value, analogous to the isotropic BAO scaling parameter $α_{iso}$ used in previous BAO measurements. Using the 2nd generation of AbacusSummit mock catalogs, we find that linear point measurements are more precise when calculated in the post-reconstruction regime with 15-60% smaller uncertainties than those pre-reconstruction. We find a systematic shift in the linear point measurements compared against the isotropic BAO measurements in mocks; we attribute this to the isotropic damping parameter responsible for smearing the linear point in the nonlinear regime. We propose a sample-dependent correction that mitigates the impact of late-time nonlinear effects. While this introduces a cosmology dependence in an otherwise model-independent measurement, this is necessary given the sub-percent precision dictated by current cosmological surveys. Comparing $α_{iso,LP}$ with isotropic BAO measurements made on the DESI DR1 and DR2 galaxy samples, we find excellent agreement after applying this correction, particularly post-reconstruction. We discuss future scope regarding cosmological inference with linear point measurements.

Uberoi, N. [Yale U.] (ORCID:0000000275179629)↗
DOE OSTI2023

2D Seismic Surveys as an Alternative for CO 2 Monitoring in the North Dakota CarbonSAFE Project

Conference presentation for International Meeting for Applied Geoscience & Energy (IMAGE), Houston, TX, August 28 – September 1, 2023. As part of the North Dakota CarbonSAFE project, seismic, controlled-source electromagnetic, and microgravity baseline monitoring surveys were collected to assess the safe, permanent, commercial-scale geologic storage of CO 2 generated by the Milton R. Young coal-fired power plant. Data from five 2D seismic lines were assessed as an alternative to 3D seismic for CO 2 monitoring. 2D and 3D surveys were compared using wave equation-based (WEB)-AVO inversion. The encouraging WEB-AVO results demonstrated that 2D surveys could be included in CO 2 monitoring programs as a cost-effective method.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2014

Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to obtain a more accurate network. All described workflows are implemented as part of the DOE Systems Biology Knowledgebase (KBase) and are publicly available via API or command-line web interface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Exploratory Efforts to Constrain Geologic Material Properties from Remote Sensing Data: Joint Study (FY2020 Final Report)

Identification and characterization of underground events from surface or remote data requires a thorough understanding of the rock material properties. However, material properties usually come from borehole data, which is expensive and not always available. A potential alternative is to use topographic characteristics to approximate the strength, but this has never been done before quantitatively. Here we present the results from the first steps towards this goal. We have found that there are strong correlations between compressive and tensile strengths and slopes, but these correlations vary depending on data analysis details. Rugosity may be better correlated to strength than slope values. More comprehensive analyses are needed to fully understand the best method of predicting strength from topography for this area. We also found that misalignment of multiple GIS datasets can have a large influence on the ability to make interpretations. Lastly, these results will require further study in a variety of climatic conditions before being applicable to other sites.

58 GEOSCIENCES↗
DOE OSTI2021

Exploratory Efforts to Constrain Geologic Material Properties from Remote Sensing Data: A Joint Study

Identification and characterization of underground events from surface or remote data requires a thorough understanding of the rock material properties. However, material properties usually come from borehole data, which is expensive and not always available. A potential alternative is to use topographic characteristics to approximate the strength, but this has never been done before quantitatively. Here we present the results from the first steps towards this goal. We have found that there are strong correlations between compressive and tensile strengths and slopes, but these correlations vary depending on data analysis details. Rugosity may be better correlated to strength than slope values. More comprehensive analyses are needed to fully understand the best method of predicting strength from topography for this area. We also found that misalignment of multiple GIS datasets can have a large influence on the ability to make interpretations. Lastly, these results will require further study in a variety of climatic conditions before being applicable to other sites.

42 ENGINEERING↗
NASA NTRS1997

Foreshock Langmuir Waves for Unusually Constant Solar Wind Conditions: Data and Implications for Foreshock Structure

Plasma wave data are compared with ISEE 1's position in the electron foreshock for an interval with unusually constant (but otherwise typical) solar wind magnetic field and plasma characteristics. For this period, temporal variations in the wave characteristics can be confidently separated from sweeping of the spatially varying foreshock back and forth across the spacecraft. The spacecraft's location, particularly the coordinate D(sub f) downstream from the foreshock boundary (often termed DIFF), is calculated by using three shock models and the observed solar wind magnetometer and plasma data. Scatterplots of the wave field versus D(sub f) are used to constrain viable shock models, to investigate the observed scatter in the wave fields at constant D(sub f), and to test the theoretical predictions of linear instability theory. The scatterplots confirm the abrupt onset of the foreshock waves near the upstream boundary, the narrow width in D(sub f) of the region with high fields, and the relatively slow falloff of the fields at large D(sub f), as seen in earlier studies, but with much smaller statistical scatter. The plots also show an offset of the high-field region from the foreshock boundary. It is shown that an adaptive, time-varying shock model with no free parameters, determined by the observed solar wind data and published shock crossings, is viable but that two alternative models are not. Foreshock wave studies can therefore remotely constrain the bow shock's location. The observed scatter in wave field at constant D(sub f) is shown to be real and to correspond to real temporal variations, not to unresolved changes in D(sub f). By comparing the wave data with a linear instability theory based on a published model for the electron beam it is found that the theory can account qualitatively and semiquantitatively for the abrupt onset of the waves near D(sub f) = 0, for the narrow width and offset of the high-field region, and for the decrease in wave intensity with increasing D(sub f). Quantitative differences between observations and theory remain, including large overprediction of the wave fields and the slower than predicted falloff at large D(sub f) of the wave fields. These differences, as well as the unresolved issue of the electron beam speed in the high-field region of the foreshock, are discussed. The intrinsic temporal variability of the wave fields, as well as their overprediction based on homogeneous plasma theory, are indicative of stochastic growth physics, which causes wave growth to be random and varying in sign, rather than secular.

Cairns, Iver H.↗
NASA NTRS2010

Display Sharing: An Alternative Paradigm

The current Johnson Space Center (JSC) Mission Control Center (MCC) Video Transport System (VTS) provides flight controllers and management the ability to meld raw video from various sources with telemetry to improve situational awareness. However, maintaining a separate infrastructure for video delivery and integration of video content with data adds significant complexity and cost to the system. When considering alternative architectures for a VTS, the current system's ability to share specific computer displays in their entirety to other locations, such as large projector systems, flight control rooms, and back supporting rooms throughout the facilities and centers must be incorporated into any new architecture. Internet Protocol (IP)-based systems also support video delivery and integration. IP-based systems generally have an advantage in terms of cost and maintainability. Although IP-based systems are versatile, the task of sharing a computer display from one workstation to another can be time consuming for an end-user and inconvenient to administer at a system level. The objective of this paper is to present a prototype display sharing enterprise solution. Display sharing is a system which delivers image sharing across the LAN while simultaneously managing bandwidth, supporting encryption, enabling recovery and resynchronization following a loss of signal, and, minimizing latency. Additional critical elements will include image scaling support, multi -sharing, ease of initial integration and configuration, integration with desktop window managers, collaboration tools, host and recipient controls. This goal of this paper is to summarize the various elements of an IP-based display sharing system that can be used in today's control center environment.

Brown, Michael A.↗
DOE OSTI2015

Transportation Deployment; NREL (National Renewable Energy Laboratory)

Automakers, commercial fleet operators, component manufacturers, and government agencies all turn to the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) to help put more green vehicles on the road. The lab’s independent analysis and evaluation pinpoint fuel-efficient and low-emission strategies to support economic and operational goals, while breaking down barriers to widespread adoption. Customized assessment of existing equipment and practices, energy-saving alternatives, operational considerations, and marketplace realities factor in the multitude of variables needed to ensure meaningful performance, financial, and environmental benefits. NREL provides integrated, unbiased, 360-degree sustainable transportation deployment expertise encompassing alternative fuels, advanced vehicles, and related infrastructure. Hands-on support comes from technical experts experienced in advanced vehicle technologies, fleet operations, and field data collection coupled with extensive modeling and analysis capabilities. The lab’s research team works closely with automakers and vehicle equipment manufacturers to test, analyze, develop, and evaluate high-performance fuel-efficient technologies that meet marketplace needs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Alternating current conduction mechanisms of RbMgPO4 compound

Highlights: • Two displacive reversible phase transitions located at T{sub 1} = 442/432 K and T{sub 2} = 460/445 K (heating/cooling). • The temperature dependence of conductivity was described in terms of Arrhenius relation. • The ac conductivity of this compound is proportional to ω{sup s} where the s values are between 0 and 2. • The (CBH) model was found to be the appropriate transport mechanism in RbMgPO{sub 4} compound. - Abstract: Rubidium magnesium monophosphate (RbMgPO{sub 4}) compound was prepared from highly pure constituents by solid state reaction. It was characterized by X-ray powder diffraction, IR, Raman, differential scanning calorimetry (DSC) and impedance spectroscopy. The infrared and Raman spectra were interpreted on the basis of PO{sub 4}{sup 3−} vibrations. DSC revealed two displacive and reversible phase transitions at T{sub 1} = 442/432 K and T{sub 2} = 460/445 K (heating/cooling). The electrical conductivity was measured in the frequency and temperature range 200 Hz-5 MHz and 423 K–523 K, respectively. The obtained results were analysed by fitting the experimental data to an equivalent circuit model. The temperature dependence of alternating and direct current conductivities (σ{sub ac}, σ{sub dc}) confirms the observed transitions in the calorimetric study; they were described in terms of Arrhenius relation. The activation energy’s values were determined in each phase. The AC conductivity behavior is ensured by a single process defined as a hopping transport mechanism. The conductivity frequency dependence was interpreted using the correlated barrier-hopping model (CBH) in all phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems

This study explores data-driven prognostics for nuclear power plant (NPP) condensers, focusing on tube fouling. We utilized the Asherah nuclear power plant simulator (ANS) to compare four methods: Random Forest (RF), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory Neural Network (LSTM). By simulating various fouling scenarios in the ANS, we generated data with different degradation rates under transient operations. The models were trained and tested on these data, with performance evaluated visually and numerically including uncertainty assessment. The LSTM model excelled, exhibiting minimal prediction noise and the most accurate remaining useful life estimates across all degradation levels. Its ability to capture long-term dependencies and produce cleaner outputs makes it a strong candidate, although accurate training data across the entire component lifespan are crucial. The RF model emerged as a robust alternative, providing reliable predictions with high confidence. The FCNN and SVR models, while less effective overall, showed potential under specific conditions. FCNN offers a less complex alternative to LSTM and might benefit from larger datasets. SVR excels in precision when the quality of the training data is high. Furthermore, this study highlights the operational benefits of advanced prognostics in the energy sector and emphasizes the need for further research in NPP condenser health management through real-life experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2000

Gravitational Physics Research

Gravitational physics research at ISPAE is connected with NASA's Relativity Mission (Gravity Probe B (GP-B)) which will perform a test of Einstein's General Relativity Theory. GP-B will measure the geodetic and motional effect predicted by General Relativity Theory with extremely stable and sensitive gyroscopes in an earth orbiting satellite. Both effects cause a very small precession of the gyroscope spin axis. The goal of the GP-B experiment is the measurement of the gyroscope precession with very high precision. GP-B is being developed by a team at Stanford University and is scheduled for launch in the year 2001. The related UAH research is a collaboration with Stanford University and MSFC. This research is focussed primarily on the error analysis and data reduction methods of the experiment but includes other topics concerned with experiment systems and their performance affecting the science measurements. The hydrogen maser is the most accurate and stable clock available. It will be used in future gravitational physics missions to measure relativistic effects such as the second order Doppler effect. The HMC experiment, currently under development at the Smithsonian Astrophysical Observatory (SAO), will test the performance and capability of the hydrogen maser clock for gravitational physics measurements. UAH in collaboration with the SAO science team will study methods to evaluate the behavior and performance of the HMC. The GP-B data analysis developed by the Stanford group involves complicated mathematical operations. This situation led to the idea to investigate alternate and possibly simpler mathematical procedures to extract the GP-B measurements form the data stream. Comparison of different methods would increase the confidence in the selected scheme.

Wu, S. T.↗
NASA NTRS1976

Energy Conversion Alternatives Study (ECAS), General Electric Phase 1. Volume 1: Executive summary

A data base for the comparison of advanced energy conversion systems for utility applications using coal or coal-derived fuels was developed. Estimates of power plant performance (efficiency), capital cost, cost of electricity, natural resource requirements, and environmental intrusion characteristics were made for ten advanced conversion systems. Emphasis was on the energy conversion system in the context of a base loaded utility power plant. All power plant concepts were premised on meeting emission standard requirements. A steam power plant (3500 psig, 1000 F) with a conventional coal-burning furnace-boiler was analyzed as a basis for comparison. Combined cycle gas/steam turbine system results indicated competitive efficiency and a lower cost of electricity compared to the reference steam plant. The Open-Cycle MHD system results indicated the potential for significantly higher efficiency than the reference steam plant but with a higher cost of electricity.

Corman, J. C.↗
NASA NTRS1980

Alternate symbol inversion for improved symbol synchronization in convolutionally coded systems

Inverting alternate symbols of the encoder output of a convolutionally coded system provides sufficient density of symbol transitions to guarantee adequate symbol synchronizer performance, a guarantee otherwise lacking. Although alternate symbol inversion may increase or decrease the average transition density, depending on the data source model, it produces a maximum number of contiguous symbols without transition for a particular class of convolutional codes, independent of the data source model. Further, this maximum is sufficiently small to guarantee acceptable symbol synchronizer performance for typical applications. Subsequent inversion of alternate detected symbols permits proper decoding.

Simon, M. K.↗
DOE OSTI2024

Life-cycle analysis of lithium chemical production in the United States

To achieve its ambitious national decarbonization goals, the United States has incentivized the domestic production of materials critical to decarbonization technologies, including lithium-ion batteries (LIBs). These materials include battery-grade lithium chemicals (Li-chemicals), for which the U.S. is encouraging domestic production from resources (sedimentary clays and low Li-content brines (LLCBs)) that differ substantially from conventional sources (Salar brines and spodumene ores). Here, we conduct the first-ever comparative life-cycle analysis of Li-chemical production from all alternative resources (in the U.S.) and conventional sources based on data from company literature for U.S.-related production efforts. Two energy sources (electricity and natural gas), four material inputs (HCl, NaOH, Na 2 CO 3 , and CaO), and process carbon emissions dominate the life-cycle impacts (≥90% share) of U.S.-based Li-chemical production. Comparatively, the life-cycle impacts of alternative sources-based Li-chemicals lie between those for Li-chemical production from Salar brines and from spodumene ores. At the battery level, the shift in Li-chemical sourcing causes a notable change in LIB's life-cycle impacts (by ~5–15%), independent of the cathode chemistry employed. Our study highlights the relevance of a decarbonized electric grid and the capture and sequestration of process carbon emissions generated during Li-chemical and upstream material production in decarbonizing Li-chemical production from alternative sources. Further decarbonization would necessitate using decarbonized material inputs and a shift away from natural gas towards renewable energy for alternative resource-based Li-chemical production processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-F-18C-13: Low-Dose X-Ray CT Reconstruction Using a Hybrid First-Order Method

Purpose: To develop a novel reconstruction method for X-ray CT that can lead to accurate reconstruction at significantly reduced dose levels combining low X-ray incident intensity and few views of projection data. Methods: The noise nature of the projection data at low X-ray incident intensity was modeled and accounted by the weighted least-squares (WLS) criterion. The total variation (TV) penalty was used to mitigate artifacts caused by few views of data. The first order primal-dual (FOPD) algorithm was used to minimize TV in image domain, which avoided the difficulty of the non-smooth objective function. The TV penalized WLS reconstruction was achieved by alternated FOPD TV minimization and projection onto convex sets (POCS) for data fidelity constraints. The proposed FOPD-POCS method was evaluated using the FORBILD jaw phantom and the real cadaver head CT data. Results: The quantitative measures, root mean square error (RMSE) and contrast-to-noise ratio (CNR), demonstrate the superior denoising capability of WLS over LS-based TV iterative reconstruction. The improvement of RMSE (WLS vs. LS) is 15%∼21% and that of CNR is 17%∼72% when the incident counts per ray are ranged from 1×10{sup 5} to 1×10{sup 3}. In addition, the TV regularization can accurately reconstruct images from about 50 views of the jaw phantom. The FOPD-POCS reconstruction reveals more structural details and suffers fewer artifacts in both the phantom and real head images. The FOPD-POCS method also shows fast convergence at low X-ray incident intensity. Conclusion: The new hybrid FOPD-POCS method, based on TV penalized WLS, yields excellent image quality when the incident X-ray intensity is low and the projection views are limited. The reconstruction is computationally efficient since the FOPD minimization of TV is applied only in the image domain. The characteristics of FOPD-POCS can be exploited to significantly reduce radiation dose of X-ray CT without compromising accuracy for diagnosis or treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades

Zebrafish have become a key alternative model for studying health effects of environmental stressors, partly due to their genetic similarity to humans, fast generation time, and the efficiency of generating high-dimensional systematic data. Studies aiming to characterize adverse health effects in zebrafish typically include several phenotypic measurements (endpoints). While there is a solid biomedical basis for capturing a comprehensive set of endpoints, making summary judgments regarding health effects requires thoughtful integration across endpoints. Here, we introduce a Bayesian method to quantify the informativeness of 17 distinct zebrafish endpoints as a data-driven weighting scheme for a multi-endpoint summary measure, called weighted Aggregate Entropy (wAggE). We implement wAggE using high-throughput screening (HTS) data from zebrafish exposed to five concentrations of all 1060 ToxCast chemicals. Our results show that our empirical weighting scheme provides better performance in terms of the Receiver Operating Characteristic (ROC) curve for identifying significant morphological effects and improves robustness over traditional curve-fitting approaches. From a biological perspective, our results suggest that developmental cascade effects triggered by chemical exposure can be recapitulated by analyzing the relationships among endpoints. Thus, wAggE offers a powerful approach for analysis of multivariate phenotypes that can reveal underlying etiological processes. - Highlights: • Introduced a data-driven weighting scheme for multiple phenotypic endpoints. • Weighted Aggregate Entropy (wAggE) implies differential importance of endpoints. • Endpoint relationships reveal developmental cascade effects triggered by exposure. • wAggE is generalizable to multi-endpoint data of different shapes and scales.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1993

Implementation and operation of three fractal measurement algorithms for analysis of remote-sensing data

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomena. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. The purpose of this paper is to introduce and implement three algorithms in C code for deriving fractal measurement from remotely sensed data. These three methods are: the line-divider method, the variogram method, and the triangular prism method. Remote-sensing data acquired by NASA's Calibrated Airborne Multispectral Scanner (CAMS) are used to compute the fractal dimension using each of the three methods. These data were obtained as a 30 m pixel spatial resolution over a portion of western Puerto Rico in January 1990. A description of the three methods, their implementation in PC-compatible environment, and some results of applying these algorithms to remotely sensed image data are presented.

Jaggi, S.↗