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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 253 records · Page 14

Data-driven offshore CO 2 saline storage assessment methodology

The world produces approximately 50 billion tonnes of greenhouse gases annually. This is measured in CO 2 -equivalents, and geologic CO 2 storage has the potential to advance decarbonization and mitigate greenhouse gas emissions. New technologies to assess offshore carbon storage are needed to address resource, regulatory, and commercial needs. Although most efforts to assess storage resources focus on onshore criteria, offshore reservoirs offer significant storage potential and distinct development challenges. Potential advantages of offshore carbon storage include being further from human population centers and less potential to interact with groundwater. The U.S. Department of Energy's method for evaluating storage capacity in non-oil-bearing saline reservoirs has been enhanced to support assessments for offshore environments in the Offshore CO 2 Saline Storage methodology (OCSS). This methodology applies data-driven capabilities to estimate saline storage capacity while accounting for features specific to offshore reservoirs. Features include changes in CO 2 density and sedimentary differences that impact estimates of permanence and capacity. The Offshore CO 2 Saline Storage Calculator mechanizes OCSS to estimate storage capacity. This paper presents the methodology and estimates for 18 geologic domains in the Gulf of Mexico. Potential storage distributions, sensitivity analyses, and the incorporation of spatial data and tools to support safe site selection are also discussed.

58 GEOSCIENCES↗

IUS/TUG orbital operations and mission support study. Volume 5: Cost estimates

The costing approach, methodology, and rationale utilized for generating cost data for composite IUS and space tug orbital operations are discussed. Summary cost estimates are given along with cost data initially derived for the IUS program and space tug program individually, and cost estimates for each work breakdown structure element.

Source record↗

Source scaling comparison and validation in Central Italy: data intensive direct S waves versus the sparse data coda envelope methodology

SUMMARY Robustness of source parameter estimates is a fundamental issue in understanding the relationships between small and large events; however, it is difficult to assess how much of the variability of the source parameters can be attributed to the physical source characteristics or to the uncertainties of the methods and data used to estimate the values. In this study, we apply the coda method by Mayeda et al. using the coda calibration tool (CCT), a freely available Java-based code (https://github.com/LLNL/coda-calibration-tool) to obtain a regional calibration for Central Italy for estimating stable source parameters. We demonstrate the power of the coda technique in this region and show that it provides the same robustness in source parameter estimation as a data-driven methodology [generalized inversion technique (GIT)], but with much fewer calibration events and stations. The Central Italy region is ideal for both GIT and coda approaches as it is characterized by high-quality data, including recent well-recorded seismic sequences such as L'Aquila (2009) and Amatrice–Norcia–Visso (2016–2017). This allows us to apply data-driven methods such as GIT and coda-based methods that require few, but high-quality data. The data set for GIT analysis includes ∼5000 earthquakes and more than 600 stations, while for coda analysis we used a small subset of 39 events spanning 3.5 < Mw < 6.33 and 14 well-distributed broad-band stations. For the common calibration events, as well as an additional 247 events (∼1.7 < Mw < ∼5.0) not used in either calibration, we find excellent agreement between GIT-derived and CCT-derived source spectra. This confirms the ability of the coda approach to obtain stable source parameters even with few calibration events and stations. Even reducing the coda calibration data set by 75 per cent, we found no appreciable degradation in performance. This validation of the coda calibration approach over a broad range of event size demonstrates that this procedure, once extended to other regions, represents a powerful tool for future routine applications to homogeneously evaluate robust source parameters on a national scale. Furthermore, the coda calibration procedure can homogenize the Mw estimates for small and large events without the necessity of introducing any conversion scale between narrow-band measures such as local magnitude (ML) and Mw, which has been shown to introduce significant bias.

Morasca, Paola (ORCID:0000000265254867)↗

Planetary spacecraft cost modeling utilizing labor estimating relationships

A basic computerized technology is presented for estimating labor hours and cost of unmanned planetary and lunar programs. The user friendly methodology designated Labor Estimating Relationship/Cost Estimating Relationship (LERCER) organizes the forecasting process according to vehicle subsystem levels. The level of input variables required by the model in predicting cost is consistent with pre-Phase A type mission analysis. Twenty one program categories were used in the modeling. To develop the model, numerous LER and CER studies were surveyed and modified when required. The result of the research along with components of the LERCER program are reported.

Williams, Raymond↗

Cleaner Chips: Decarbonization in Semiconductor Manufacturing

The growth of the information and communication technology sector has vastly accelerated in recent decades because of advancements in digitalization and Artificial Intelligence (AI). Scope 1, 2, and 3 greenhouse gas emissions data of the top six semiconductor manufacturing companies (Samsung Electronics, Taiwan Semiconductor Manufacturing Corporation, Micron, SK Hynix, Kioxia, and Intel) were gathered from the publicly accessible Carbon Disclosure Project’s (CDP) website for 2020. Scope 3 emissions had the largest share in total annual emissions with an average share of 52%, followed by Scope 2 (32%) and Scope 1 (16%). Because of the absence of a standardized methodology for Scope 3 emissions estimation, each company used different methodologies that resulted in differences in emissions values. An analysis of the CDP reporting data did not reveal information on strategies implemented by companies to reduce Scope 3 emissions. The use of renewable energy certificates had the largest effect on decarbonization centered on reducing Scope 2 emissions, followed by the deployment of perfluorocarbon reduction technologies to help reduce Scope 1 fugitive emissions. Technology-specific marginal abatement costs of CO2 were also estimated and varied between −416 and 12,215 USD/t CO2 eq., which primarily varied depending on the technology deployed.

42 ENGINEERING↗

Re-evaluating probable maximum precipitation estimates: sensitivity to transposition domains and storm rotation using modern datasets

This study examines the sensitivity of Probable Maximum Precipitation (PMP) estimates to key methodological decisions embedded in the legacy approach adopted in the U.S. National Weather Service Hydrometeorological Reports No. 51 and No. 52. Although widely used for infrastructure design and risk regulation, fundamental aspects of PMP estimation—such as storm sample size, transposition domain, maximization procedures, and storm rotation—remain poorly constrained and lack formal guidance. Using the Red Rock watershed in Iowa as a case study, and leveraging the 2002–2023 NOAA Analysis of Record for Calibration (AORC) precipitation dataset, we systematically evaluate how each methodological choice, individually and in combination, influences PMP estimates. Our findings demonstrate that PMP is not a fixed physical upper bound but rather a modeling construct shaped heavily by user-defined assumptions. Notably, PMP values derived from modern gridded rainfall datasets can be substantially higher than the legacy estimate used in the original spillway design for Red Rock Dam. Decisions regarding storm sample size, domain extent, climatological window, and particularly storm rotation all contributed to higher PMP estimates. Storm rotation alone—a loosely constrained element in the current PMP practice—can amplify PMP by more than 25%. These results reveal the lack of standardized bounds in current PMP workflows and the need for systematic sensitivity and uncertainty analysis. As PMP estimation shifts toward probabilistic approaches, incorporating physically meaningful storm attributes will be key to developing more transparent, defensible methods for dam safety and climate-resilient infrastructure.

Probable maximum precipitation↗

Sitka Energy Inventory

The City and Borough of Sitka was chosen for an Energy Technology Innovation Partner Project award starting in Fall 2023, the third cohort of the program. The scope of the following work was driven by the city, as well as the city-appointed Sustainability Commission. The community asked for a method to track their reliance on outside fuel sources, as well as the emissions associated with those fuels and other processes in Sitka. The Pacific Northwest National Laboratory (PNNL) provided research and methodology in line with this community driven ask. This project is a community wide inventory, requiring methods to estimate the fuel usage and emissions from various industries. For each estimate, PNNL presents methodologies that can be repeated by the community in future years to understand how the city is changing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A selection function toolbox for subsets of astronomical catalogues

ABSTRACT Large catalogues are ubiquitous throughout astronomy, but most scientific analyses are carried out on smaller samples selected from these catalogues by chosen cuts on catalogued quantities. The selection function of that scientific sample – the probability that a star in the catalogue will satisfy these cuts and so make it into the sample – is thus unique to each scientific analysis. We have created a general framework that can flexibly estimate the selection function of a sample drawn from a catalogue in terms of position, magnitude and colour. Our method is unique in using the binomial likelihood and accounting for correlations in the selection function across position, magnitude, and colour using Gaussian processes and spherical harmonics. We have created a new open-source python package selectionfunctiontoolbox that implements this framework and used it to make three different estimates of the APOGEE DR16 red giant sample selection function, as a subset of 2MASS, with each estimate using an increasing amount of technical knowledge of the APOGEE targeting. In a companion paper, we applied our methodology to derive estimates of the astrometric and spectroscopic selection functions of Gaia EDR3. Our framework will make it trivial for astrophysicists to estimate the selection function that they should be using with the custom sample of stars that they have chosen to answer their scientific question.

79 ASTRONOMY AND ASTROPHYSICS↗

Improved Methodology for Surface and Atmospheric Soundings, Error Estimates, and Quality Control Procedures: the AIRS Science Team Version-6 Retrieval Algorithm

The AIRS Science Team Version-6 AIRS/AMSU retrieval algorithm is now operational at the Goddard DISC. AIRS Version-6 level-2 products are generated near real-time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. This paper describes some of the significant improvements in retrieval methodology contained in the Version-6 retrieval algorithm compared to that previously used in Version-5. In particular, the AIRS Science Team made major improvements with regard to the algorithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the cloud clearing and retrieval procedures; and 3) derive error estimates and use them for Quality Control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, Version-6 also operates in an AIRS Only (AO) mode which produces results almost as good as those of the full AIRS/AMSU mode. This paper also demonstrates the improvements of some AIRS Version-6 and Version-6 AO products compared to those obtained using Version-5.

Quality Control↗

Solar Photovoltaics and Land-Based Wind Technical Potential and Supply Curves for the Contiguous United States (2023 Edition)

Estimates of the potential of renewable energy are essential for understanding how we can decarbonize our electric grid and economy. They provide key data for policymakers, land managers, and energy modelers by defining the quantity, quality, and cost of renewable resources. However, estimating renewable energy potential is challenging and requires frequent updates because of rapid advances in technology, cost reductions, and uncertainty about developable land that are due to social, regulatory, and environmental factors. Additionally, the complex processes involved in renewable energy development require regular reviews of methods and assumptions, which can also impact our understanding of renewable potential. In this, the 2023 edition of this annual report, we present new estimates of the technical potential for land-based wind and solar photovoltaics (PV) for the contiguous United States (CONUS). We also provide cost estimates for the available resources, presenting representative supply curves that can be used in downstream modeling and analysis. Additionally, we introduce the new methodologies used to estimate wind capacity, wind energy losses, transmission cost and representation, updated technology cost and design, and scenarios of siting constraints designed to help bound the uncertainty of renewable potential.

14 SOLAR ENERGY↗

Comparison of Global Aboveground Biomass Estimates From Satellite Observations and Dynamic Global Vegetation Models

The global forest carbon stocks represent the amount of carbon stored in woody vegetation and are important for quantifying the ability of the global forests to sequester atmospheric CO 2 and to provide ecosystem services (e.g., timber) under climate change. The forest ecosystem carbon pool estimates are highly variable and poorly quantified in areas lacking forest inventory estimates. Here, we compare and analyze aboveground biomass (AGB) estimates from five satellite-based global data sets and nine dynamic global vegetation models (DVGMs). We find that across the data sets, mean AGB exhibits the largest variability around the tropical area. In addition, AGB shows a similar latitudinal trend but large variability among the data sets. Satellite-based AGB estimates are lower than those simulated by DVGMs. The divergence among the satellite-based AGB estimates can be driven by the methodology, input satellite products, and the forested areas used to estimate AGB. The modeled NPP, autotrophic respiration, and carbon allocation mostly drive the variability of AGB simulated by DGVMs. The future availability of a high-quality global forest area map is anticipated to improve AGB estimate accuracy and to reduce the discrepancies among different satellite- and model-based AGB estimates. Furthermore, we suggest the carbon-modeling community reexamine the methodology used to estimate AGB and forested areas for a more robust global forest carbon stock estimation.

54 ENVIRONMENTAL SCIENCES↗

Binomial Test Method for Determining Probability of Detection Capability for Fracture Critical Applications

The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that for a minimum flaw size and all greater flaw sizes, there is 0.90 probability of detection with 95% confidence (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields estimates of POD and confidence bounds for both Hit-Miss or signal amplitude testing, where signal amplitudes are reduced to Hit-Miss by using a signal threshold Directed DOEPOD uses a nonparametric approach for the analysis or inspection data that does require any assumptions about the particular functional form of a POD function. The DOEPOD procedure identifies, for a given sample set whether or not the minimum requirement of 0.90 probability of detection with 95% confidence is demonstrated for a minimum flaw size and for all greater flaw sizes (90/95 POD). The DOEPOD procedures are sequentially executed in order to minimize the number of samples needed to demonstrate that there is a 90/95 POD lower confidence bound at a given flaw size and that the POD is monotonic for flaw sizes exceeding that 90/95 POD flaw size. The conservativeness of the DOEPOD methodology results is discussed. Validated guidelines for binomial estimation of POD for fracture critical inspection are established.

Generazio, Edward R.↗

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Simon, Donald L.↗

Model estimation and identification of manual controller objectives in complex tracking tasks

A methodology is presented for estimating the parameters in an optimal control structural model of the manual controller from experimental data on complex, multiinput/multioutput tracking tasks. Special attention is devoted to estimating the appropriate objective function for the task, as this is considered key in understanding the objectives and strategy of the manual controller. The technique is applied to data from single input/single output as well as multi input/multi outpuut experiments, and results discussed.

Schmidt, D. K.↗

Statistically-informed deep learning for gravitational wave parameter estimation

We introduce deep learning models to estimate the masses of the binary components of black hole mergers, $(m_1,m_2)$, and three astrophysical properties of the post-merger compact remnant, namely, the final spin, $a_\mathrm f$, and the frequency and damping time of the ringdown oscillations of the fundamental $\ell = m = 2$ bar mode, $(\omega_\mathrm R, \omega_\mathrm I)$. Our neural networks combine a modified WaveNet architecture with contrastive learning and normalizing flow. We validate these models against a Gaussian conjugate prior family whose posterior distribution is described by a closed analytical expression. Upon confirming that our models produce statistically consistent results, we used them to estimate the astrophysical parameters $(m_1,m_2, a_\mathrm f, \omega_\mathrm R, \omega_\mathrm I)$ of five binary black holes: GW150914, GW170104, GW170814, GW190521 and GW190630. We use PyCBC Inference to directly compare traditional Bayesian methodologies for parameter estimation with our deep learning based posterior distributions. Our results show that our neural network models predict posterior distributions that encode physical correlations, and that our data-driven median results and 90% confidence intervals are similar to those produced with gravitational wave Bayesian analyses. This methodology requires a single V100 NVIDIA GPU to produce median values and posterior distributions within two milliseconds for each event. Furthermore, this neural network, and a tutorial for its use, are available at the Data and Learning Hub for Science.

79 ASTRONOMY AND ASTROPHYSICS↗

Aerosol Indirect Effect Studies at Southern Great Plains During the May 2003 Intensive Operations Period

During May 2003 the Department of Energy's Atmospheric Radiation Measurement Program conducted an Intensive Operations Period (IOP) to measure the radiative effects of aerosol and clouds. A suite of both in situ and remote sensing measurements were available to measure aerosol and cloud parameters. This paper has three main goals: First, it focuses on comparison between in situ retrievals of the radiatively important drop effective radius r(sub e) and various satellite, airborne, and surface remote sensing retrievals of the same parameter. On 17 May 2003, there was a fortuitous, near-simultaneous sampling of a stratus cloud by five different methods. The retrievals of r(sub e) agree with one another to within approx.20%, which is approximately the error estimate for most methods. Second, a methodology for deriving a best estimate of r(sub e) from these different instruments, with their different physical properties and sampling volumes, is proposed and applied to the 17 May event. Third, the paper examines the response of r(sub e) to changes in aerosol on 3 days during the experiment and examines the consistency of remote sensing and in situ measurements of the effect of aerosol on r(sub e). It is shown that in spite of the generally good agreement in derived r(sub e), the magnitude of the response of r(sub e), to changes in aerosol is quite sensitive to the method of retrieving r(sub e) and to the aerosol proxy for cloud condensation nuclei. Nonphysical responses are sometimes noted, and it is suggested that further work needs to be done to refine these techniques.

Feingold, Graham↗

Making the Case for Reusable Booster Systems: The Operations Perspective

Presentation to the Aeronautics Space Engineering Board National Research Council Reusable Booster System: Review and Assessment Committee. Addresses: the criteria and assumptions used in the formulation of current RBS plans; the methodologies used in the current cost estimates for RBS; the modeling methodology used to frame the business case for an RBS capability including: the data used in the analysis, the models' robustness if new data become available, and the impact of unclassified government data that was previously unavailable and which will be supplied by the USAF; the technical maturity of key elements critical to RBS implementation and the ability of current technology development plans to meet technical readiness milestones.

reusable launch vehicle↗

Neptunium transition probabilities estimated through laser induced breakdown spectroscopy (LIBS) measurements

in tis report calibration free–laser induced breakdown spectroscopy (CF-LIBS) approaches are promising for the analysis of radioactive materials; however, a lack of reported fundamental properties for these materials is an obstacle to implementation. Spectra of laser induced plasmas containing Np and Sr, along with Saha–Boltzmann methods, were used to estimate the first reported transition probabilities (TPs) of Np. These TPs enabled the first attempt at CF-LIBS analysis of radioactive samples to predict Np/Sr ratios with a mean error of 3.86%. The presented methodology of TP estimation will be applied to the study of other actinides and allow broader applications of CF-15 LIBS in the nuclear field.

74 ATOMIC AND MOLECULAR PHYSICS↗