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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Stakeholder Engaged Structured Decision Making to Improve Performance and Reduce Costs While Protecting Human Health and the Environment - 18645

The objective of the Best Practice is to facilitate a paradigm shift when it comes to approaches to the decision making process for nuclear waste management, disposal, and remediation decisions. The stakeholder-engaged structured decision making (SDM) paradigm shift provides a transparent framework for developing optimal solutions to complex problems (Keeney, 1992, Gregory et al, 2012). This is a deliberative-analytical process. The deliberative side centers on understanding stakeholder concerns and values, and developing objectives while identifying options that may achieve those objectives. SDM is implemented with the aid of computer tools that are aimed specifically at capturing these deliberative aspects of a decision analysis. SDM captures this information in a structured format that allows access to the values, objectives, and options that have been identified to help. Through this approach we achieve transparency, traceability, and reproducibility. The goal of SDM at this stage is to provide a formal structure for capturing and processing deliberative information. The deliberative part sets the stage for the analytical part of SDM. A variety of Subject matter experts (SMEs) are engaged in how to evaluate the options through the objectives. Objectives often include minimizing human health risk and minimizing cost, but in the full scope of a sustainability-based approach to decision making, it can include objectives related to economic, environmental and social issues. Subject matter experts might provide other options for achieving the objectives, but their primary role is to evaluate/model the options to the endpoint defined by the objectives or in other words perform a consequence analysis. The structure of SDM makes it clear exactly what is needed from the SMEs, because the options are identified, and the endpoint (objectives) are defined - evaluations and/or models are needed to connect options to objectives. This consequence analysis completes the evaluation, and directly addresses which of the options is the best option. The same SDM approach to finding the best options can also be used for prioritization and resource allocation. Because all of the information is captured in a formal system with the help of computer tools (a software framework for implementing SDM), the decision models that are developed for an application can be fully evaluated numerically and for the insights gained from using a formal process for managing the multiple factors that need to be considered for complex decisions. This includes uncertainty and sensitivity analysis that can be used to guide the need for further data/information collection if the optimal decision is not adequately supported - that is, if there is insufficient confidence in the decision. Also, this feeds directly into adaptive management therefore if more data/information are collected then the efficacy of the current decision can be evaluated, potentially leading to a change in decisions if warranted. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

The Role of Chemistry in Fracture Pattern Development and Opportunities to Advance Interpretations of Geological Materials

Abstract Fracture pattern development has been a challenging area of research in the Earth sciences for more than 100 years. Much has been learned about the spatial and temporal complexity inherent to these systems, but severe challenges remain. Future advances will require new approaches. Chemical processes play a larger role in opening‐mode fracture pattern development than has hitherto been appreciated. This review examines relationships between mechanical and geochemical processes that influence the fracture patterns recorded in natural settings. For fractures formed in diagenetic settings (~50 to 200 °C), we review evidence of chemical reactions in fractures and show how a chemical perspective helps solve problems in fracture analysis. We also outline impediments to subsurface pattern measurement and interpretation, assess implications of discoveries in fracture history reconstruction for process‐based models, review models of fracture cementation and chemically assisted fracture growth, and discuss promising paths for future work. To accurately predict the mechanical and fluid flow properties of fracture systems, a processes‐based approach is needed. Progress is possible using observational, experimental, and modeling approaches that view fracture patterns and properties as the result of coupled mechanical and chemical processes. A critical area is reconstructing patterns through time. Such data sets are essential for developing and testing predictive models. Other topics that need work include models of crystal growth and dissolution rates under geological conditions, cement mechanical effects, and subcritical crack propagation. Advances in machine learning and 3‐D imaging present opportunities for a mechanistic understanding of fracture formation and development, enabling prediction of spatial and temporal complexity over geologic timescales. Geophysical research with a chemical perspective is needed to correctly identify and interpret fractures from geophysical measurements during site characterization and monitoring of subsurface engineering activities.

58 GEOSCIENCES↗
DOE OSTI2025

Laboratory Demonstration of Collisionless Blob Formation via Laser-Produced Plasma Self-Focusing

Strongly localized, propagating plasma density structures that are capable of crossing magnetic field lines are known as “blobs.” Here we demonstrate a novel mechanism for the formation and propagation of an ion gyroradius-scale blob-cavity structure at the interface between a super-Alfvénic laser-produced plasma (LPP) and an ambient magnetized plasma. The LPP self-focuses along the edge of the diamagnetic cavity which results in a dense, jetlike structure as compared to ballistic motion. This collimated flow couples momentum to the ambient plasma through a collisionless process known as Larmor coupling. The Larmor electric fields locally displace the ambient ions forming a blob above the LPP flow. In the region between a gyrating blob and collimated LPP flow, a secondary cavity of expelled magnetic field forms. In conclusion, these findings are supported by particle-in-cell simulations that replicate the blob formation mechanism and provide insight to similar processes in space, astrophysical, and laboratory settings characterized by ion kinetic scales.

Fluorescence spectroscopy↗
DOE OSTI2021

Poly(ether‐block‐amide) membrane with deformability and adjustable surface hydrophilicity for water purification

Abstract Freshwater resources are currently insufficient, and another form of freshwater resources, namely, ice, is very interesting except for the issue of how to use new materials for effective purification during the processing procedure. In this article, a new membrane material with multisize pore structure in the cross‐section and intact thin skin layer on the upper and lower surfaces was successfully prepared by adding porogen, filler and setting heating environment during the phase separation process. The membrane exhibits excellent axial deformability, and its elongation at break can reach to 160% strain. Meanwhile, they all show elastic deformation behavior in the range from −60 to 100°C. Even if high content of hydrophobic filler is compounded into these membranes, that is, 5.7 wt% carbon tube content, water contact angle of membrane's surface is only 72.5°, demonstrating obvious hydrophilicity. In addition, in the water purification process, the adsorption rate constant reached ideal value of 0.26 s −1 , and the equilibrium adsorption capacity was about 2.8 g/g, showing fast and efficient water purification ability. In the mode of external heating source or the membrane's heat dissipation, these prepared membranes can melt the ice to obtain purified water and exhibit a controllable purification ability in this process.

Ge, Chengbiao↗
DOE OSTI2019

ERAP1 enzyme-mediated trimming and structural analyses of MHC I–bound precursor peptides yield novel insights into antigen processing and presentation

Endoplasmic reticulum aminopeptidase 1 (ERAP1) and ERAP2 critically shape the major histocompatibility complex I (MHC I) immunopeptidome. The ERAPs remove N-terminal residues from antigenic precursor peptides and generate optimal-length peptides (i.e. 8–10-mers) to fit into the MHC class I groove. It is therefore intriguing that MHC class I molecules can present N-terminally extended peptides on the cell surface that can elicit CD8+ T-cell responses. This observation likely reflects gaps in our understanding of how antigens are processed by the ERAP enzymes. To better understand ERAPs' function in antigen processing, here we generated a nested set of N-terminally extended 10–20-mer peptides (RA)nAAKKKYCL covalently bound to the human leukocyte antigen (HLA)-B*0801. We used X-ray crystallography, thermostability assessments, and an ERAP1-trimming assay to characterize these complexes. The X-ray structures determined at 1.40–1.65 Å resolutions revealed that the residue extensions (RA)n unexpectedly protrude out of the A pocket of HLA-B*0801, whereas the AAKKKYCL core of all peptides adopts similar, bound conformations. HLA-B*0801 residue 62 was critical to open the A pocket. We also show that HLA-B*0801 and antigenic precursor peptides form stable complexes. Finally, ERAP1-mediated trimming of the MHC I–bound peptides required a minimal length of 14 amino acids. We propose a mechanistic model explaining how ERAP1-mediated trimming of MHC I–bound peptides in cells can generate peptides of canonical as well as noncanonical lengths that still serve as stable MHC I ligands. Our results provide a framework to better understand how the ERAP enzymes influence the MHC I immunopeptidome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Panorama 360 (Final Report)

This is the final technical report for the DOE-funded Panorama 360 project. Panorama 360 provided a resource for the collection, analysis, and sharing of performance data about end-to-end scientific workflows executing on DOE facilities. The work focused on workflows that include experimental data generation at DOE facilities. The main activities of Panorama 360 include the development of: 1. A distributed repository that stores different types of workflow execution data (e.g., point and time series performance traces at fine- and coarse-grained levels); 2. A set of open-source data capture, curation, and publishing tools fully integrated with a state-of-the-art workflow management system that automates data ingestion to the repository and enables users to discover, query, and process data from the repository; 3. A set of analysis algorithms and machine learning based tools to perform analysis and characterization of the gathered data, which can be used to detect anomalous performance or system faults; and 4. Best practices and recommendations for workflow evaluation, analysis, execution, and architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Panorama 360 (Final Report)

This final technical report from the lead institution, USC grant #DE-SC0012636, serves as the final technical report for collaborative institution UNC-CH grant #DE-SC0012390. The goal was to develop a repository and associated capabilities for data collection, ingestion, and analysis for a broad class of DOE applications that span experimental and simulation science workflows. In particular, this work focuses on workflows that include experimental data generation at DOE facilities. The main activities of Panorama 360 include the development of: (1) A distributed repository that stores different types of workflow execution data (e.g., point and time series performance traces at fine- and coarse-grained levels); (2) A set of open-source data capture, curation, and publishing tools fully integrated with a state-of-the-art workflow management system that automates data ingestion to the repository and enables users to discover, query, and process data from the repository; (3) A set of analysis algorithms and machine learning based tools to perform analysis and characterization of the gathered data, which can be used to detect anomalous performance or system faults; and (4) Best practices and recommendations for workflow evaluation, analysis, execution, and architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Timelike Compton Scattering from a longitudinally polarised target with CLAS12 at Jefferson Lab

Explorations into the internal dynamics of hadrons are constantly evolving, and the requirement for experimental results to verify theoretical models of hadron structure is paramount. A key area in this field is the study of Generalised Parton Distributions (GPDs), which are functions used to model the momenta of quarks and gluons within hadrons, and the methods to access GPDs experimentally. One such scattering process that allows access to these is Timelike Compton Scattering. TCS complements existing Deeply Virtual Compton Scattering experiments and allows investigation into the universality of GPDs through access to the real and imaginary parts of the parton helicity independent GPD Hq via beam spin asymmetries (BSA), and it provides novel access to the real and imaginary parts of the parton helicity dependent GPD ˜Hq through target polarisation asymmetries (TSA). This thesis work presents a comparative study with the first published BSA for TCS at the Thomas Jefferson National Accelerator Facility (JLab), alongside a first time extraction of a Target Spin Asymmetry with the Summer 2022 data taking run. JLab hosts the Continuous Electron Beam Accelerator Facility (CEBAF) which provides a 12 GeV electron beam to four experimental halls. Hall-B contains the CEBAF Large Acceptance Spectrometer, which took data across three run periods on a longitudinally polarised NH3 and ND3 fixed target from 2022-2023, to extract measurements of electron-proton scattering, from which a TCS signal could be extracted. The thesis discusses work done to understand and eliminate contributions from the non-/low-polarised nuclear background, testing pre-established cuts to eliminate pion background from a dilepton (e+e-) final state and modifying them as needed for the new experimental run, and attempts to hone in on a clean TCS signal from which to extract the two asymmetry observables. A comparison with existing BSA results was performed; however, the statistical errors are too large to draw a significant conclusion as to whether there is agreement across each bin. More data is needed for a multidimensionally binned extraction. A proof of principle was achieved in the TSA measurements, with two out of four kinematic bins showing preliminary agreement in shape with theoretical values. Again, the errors are significant due to the contributions from the nuclear background. To support these conclusions, a further study was done, which takes into account an estimate of the asymmetries with the full available dataset (this thesis is based only on data taken in the summer set; at the time of writing processing was still being conducted for the final two datasets), as well as an estimate including additional future experiment days that were awarded in July 2024. Additional work was done on a secondary project exploring the feasibility of measuring TCS at the upcoming Electron Ion Collider, supporting the design proposal for the detector for the first interaction region and giving a positive outlook for the future of these types of measurements beyond JLab.

Gates, Kayleigh [Univ. of Glasgow, Scotland (Unite↗
DOE OSTI2019

Surrogate Models for Estimating Failure in Brittle and Quasi-Brittle Materials

In brittle fracture applications, failure paths, regions where the failure occurs and damage statistics, are some of the key quantities of interest (QoI). High-fidelity models for brittle failure that accurately predict these QoI exist but are highly computationally intensive, making them infeasible to incorporate in upscaling and uncertainty quantification frameworks. The goal of this paper is to provide a fast heuristic to reasonably estimate quantities such as failure path and damage in the process of brittle failure. Towards this goal, we first present a method to predict failure paths under tensile loading conditions and low-strain rates. The method uses a k-nearest neighbors algorithm built on fracture process zone theory, and identifies the set of all possible pre-existing cracks that are likely to join early to form a large crack. The method then identifies zone of failure and failure paths using weighted graphs algorithms. We compare these failure paths to those computed with a high-fidelity fracture mechanics model called the Hybrid Optimization Software Simulation Suite (HOSS). A probabilistic evolution model for average damage in a system is also developed that is trained using 150 HOSS simulations and tested on 40 simulations. A non-parametric approach based on confidence intervals is used to determine the damage evolution over time along the dominant failure path. For upscaling, damage is the key QoI needed as an input by the continuum models. This needs to be informed accurately by the surrogate models for calculating effective moduli at continuum-scale. We show that for the proposed average damage evolution model, the prediction accuracy on the test data is more than 90%. In terms of the computational time, the proposed models are ≈ O ( 10 6 ) times faster compared to high-fidelity fracture simulations by HOSS. These aspects make the proposed surrogate model attractive for upscaling damage from micro-scale models to continuum models. We would like to emphasize that the surrogate models are not a replacement of physical understanding of fracture propagation. The proposed method in this paper is limited to tensile loading conditions at low-strain rates. This loading condition corresponds to a dominant fracture perpendicular to tensile direction. The proposed method is not applicable for in-plane shear, out-of-plane shear, and higher strain rate loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Fluid‐Driven Cohesive Strengthening: Critical Role of Reaction Kinetics as the Determinant for Frictional Stability

After an earthquake, faults in the Earth's crust lock up and slowly regain strength. This process, called fault healing, plays a key role in determining how often earthquakes happen and how large they can be. While scientists know that healing involves both mechanical friction and chemical changes in rocks, it has been unclear how these processes work together, especially over shorter timescales in laboratory settings. In our study, we ran controlled experiments on the mineral anhydrite under different fluid conditions. We found that the presence and pressure of water speeds up fault healing by triggering a chemical reaction that strengthens the fault over time. This strengthening makes the fault more resistant to sliding, which could delay future earthquakes—but also sets the stage for larger ones when they do occur. We propose a model that combines frictional and chemical processes to explain this water‐activated, time‐dependent healing. Importantly, our results show that even faults typically considered stable could still produce earthquakes if they undergo sufficient chemical healing. This has broad implications for understanding where and when earthquakes might strike, especially in fluid‐rich environments such as subduction zones and geoenergy settings.

Affinito, R [Pennsylvania State Univ., University ↗
DOE OSTI2020

Renormalization scale setting for heavy quark pair production in $e^+e^–$ annihilation near the threshold region

Heavy fermion pair production in e + e – annihilation is a fundamental process in hadron physics and is of considerable interest for various phenomena. In this paper, we will apply the principle of maximum conformality (PMC) to provide a comprehensive analysis of these processes. The PMC provides a systematic, unambiguous method for determining the renormalization scales of the QCD coupling constant for single-scale and multiple-scale applications. The resulting predictions eliminate any renormalization scheme-and-scale ambiguities, eliminate the factorial renormalon divergences, and are consistent with the requirements of the renormalization group. It is remarkable that two distinctly different scales are determined by using the PMC for heavy fermion pair production near the threshold region. One scale is the order of the fermion mass m f , which enters the hard virtual corrections, and the other scale is of order v m f , where v is the quark velocity, which enters the Coulomb rescattering amplitude. The PMC scales yield the correct physical behavior and reflect the virtuality of the propagating gluons (photons) for the QCD (QED) processes. Moreover, we demonstrate the consistency of PMC scale setting from QCD to QED. Perfect agreement between the Abelian unambiguous Gell-Mann-Low and the PMC scale-setting methods in the limit of zero number of colors is demonstrated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

A Large Deviations Analysis of Certain Qualitative Properties of Parallel Tempering and Infinite Swapping Algorithms

Parallel tempering, or replica exchange, is a popular method for simulating complex systems. The idea is to run parallel simulations at different temperatures, and at a given swap rate exchange configurations between the parallel simulations. From the perspective of large deviations it is optimal to let the swap rate tend to infinity and it is possible to construct a corresponding simulation scheme, known as infinite swapping. In this paper we propose a novel use of large deviations for empirical measures for a more detailed analysis of the infinite swapping limit in the setting of continuous time jump Markov processes. Using the large deviations rate function and associated stochastic control problems we consider a diagnostic based on temperature assignments, which can be easily computed during a simulation. Here we show that the convergence of this diagnostic to its a priori known limit is a necessary condition for the convergence of infinite swapping. Finally, the rate function is also used to investigate the impact of asymmetries in the underlying potential landscape, and where in the state space poor sampling is most likely to occur.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

In situ laser profilometry for material segmentation and digital reconstruction of a multicomponent additively manufactured part

In addition to its ability to produce geometrically complex parts, additive manufacturing offers a unique opportunity to collect data about a component while it is being fabricated. However, there has only been limited effort to characterize parts morphologically and compositionally in situ. In this article, we present a layer-by-layer, laser profilometry-based in situ characterization technique as a method to digitally reconstruct a multi-material part. Data collected by the laser profilometer yields height maps and grayscale images which are voxelized using purpose-built software to volumetrically reconstruct the part. Additionally, the same part was also analyzed using X-ray computed tomography (CT) which was not able to resolve the different compositional regions within the part, but captured the filament morphology. The part was then bisected to compare the digital reconstruction to the actual part morphology and composition. Overall, the digital reconstruction was in good agreement with both the CT and bisected images. Deviations between the digital reconstruction and the CT/bisected images are likely the result of image segmentation settings or material shifts after data was collected. The in situ characterization method demonstrated here sets the stage for real time process monitoring and paves the way for additively manufactured parts that are “born qualified.”

36 MATERIALS SCIENCE↗
DOE OSTI2018

Biochemical Production with Purified Cell-Free Systems

Bioprocesses offer a powerful set of opportunities for current chemical process innovation. Such conversions provide opportunities to employ process intensification strategies and the right characteristics to scale down and harness the power of modular process design, but strain engineering and the use of microbial systems for industrial biochemicals production remain unpredictable and expensive. Purified cell-free technologies, in which complex enzyme reaction cascades are used to catalyze bioconversions of interest, can be designed to mitigate these limitations. Such systems allow predictive kinetic modeling and full control of reaction conductions, enabling a dramatically increased design-built-test cycle iteration rate. When sufficiently robust engineered enzymes are used, opportunities to leverage harsh reaction conditions, long-term recycling strategies, and hybridization with chemical catalysis can be used to dramatically improve the value proposition of biochemicals production. As a result, further research is required to realize the potential of these approaches and to address the current platform-limiting challenges around cofactor cost and reuse.

09 BIOMASS FUELS↗
DOE OSTI2019

Microstructure optimization with constrained design objectives using machine learning-based feedback-aware data-generation

Microstructure sensitive design has a critical impact on the performance of engineering materials. The safety and performance requirements of critical components, as well as the cost of material and machining of Titanium components, make dovetailing of the microstructure imperative. This paper addresses the optimization of several microstructure design problems for Titanium components under specific design constraints using a feedback-aware data-driven solution methodology. In this study, the microstructure is modeled with an orientation distribution function (ODF) that measures the volumes of different crystallographic orientations. Two algorithms are used to sample the entire microstructure space followed by machine learning-aided identification of a minimal subset of ODF dimensions which is subsequently explored by targeted sampling. Conventional optimization methods lead to a unique microstructure rather than yielding a comprehensive space of optimal or near-optimal microstructures. Multiple solutions are crucial for the deployment of materials design for manufacturing as traditional manufacturing processes can only generate a limited set of microstructures. Our data sampling-based methodology not only outperforms or is on par with other optimization techniques in terms of the optimal property value, but also provides numerous near-optimal solutions, 3–4 orders of magnitude more than previous methods. Consequently, the proposed framework delivers a spectrum of optimal solutions in the microstructure space which can accelerate materials development and reduce manufacturing costs.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Kinetics of D/H isotope fractionation between molecular hydrogen and water

At equilibrium, the D/H isotope fractionation factor between H 2 and H 2 O (α H 2 O-H 2 (eq) ) is a sensitive indicator of temperature, and has been used as a geothermometer for natural springs and gas discharges. However, δD H 2 measured in spring waters may underestimate subsurface temperatures of origin due to partial isotopic re-equilibration during ascent and cooling. In this work, we present new experimental data on the kinetics of D–H exchange for H 2 dissolved in liquid water at temperatures below 100 °C. Comparing these results with published exchange rates obtained from gas phase experiments (100–400 °C), we derive a consistent activation energy of 52 kJ/mol, and the following rate expressions; ln k =9.186 - 6298/ T and k 1 = 9764.61[H 2 O] e-6298/ T where T is absolute temperature (K), k is the universal rate constant ([L/mol]/hr), and k 1 is a pseudo-first-order constant (hr -1 ) applicable to water-dominated terrestrial systems by constraining [H 2 O] as the density of H 2 O (in mol/L) at the P-T of interest. The density-dependent rate constant accounts for the kinetic disparity of D–H exchange with H 2 when dissolved in liquid H 2 O relative to a gas/steam phase, exemplifed by 1/ k 1 at 100 °C of ~2 days in liquid, versus ~7 yrs in saturated steam. This difference may explain the high variability of δDH 2 observed in fumarolic gases. Fluids convecting in the crust frequently reach T > 225 °C, where isotopic equilibrium is rapidly attained (<1 hr). We compare fractionation factors measured in natural fluids (α OBS ) with values expected for equilibrium at the T of acquisition. Where these values differ, we use kinetic models to estimate cooling rates during upward advection that account for the observed disequilibrium. Models fit to fluids from Yellowstone Park and the Lost City (deep-sea) vent field, both recovered at ~90 °C, require respective transit times of ~7 hrs and ~11 days between higher temperature reaction zones and the surface. Using estimates of subsurface depths of origin, however, suggests similar mean fluid flow rates (10 s of meters/hr). Additional complications must be considered when interpreting the δDH 2 of lower-temperature effluent. When applied to data from deep-sea hydrothermal systems, our kinetic models indicate microbial catalysis accelerates D–H exchange once fluids cool below ~60 °C. The H 2 measured in both continental alkaline springs and fracture fluids from Precambrian shield rock is likely produced at T < 100 °C, through processes such as serpentinization. In these settings, δDH 2 values appear closer to equilibrium with H 2 O than those from geothermal systems. Considering kinetic isotope effects may yield H 2 that is out of equilibrium when generated at lower temperatures, we calculate maximum (isothermal) times to apparent isotopic equilibrium of 1.3 yrs at 50 °C, 9 yrs at 25 °C, and 35 yrs at 10 °C. A similar calculation applied to Antarctic brines (-13 °C), where measured δDH 2 is far from equilibrium, yields ~350 yrs. This time is shorter than the fluids have been isolated (2.8 ka), suggesting kinetic isotope effects associated with H 2 destruction or loss via diffusion may also be possible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Cost of power or power of cost: A U.S. modeling perspective

Future scenarios and assessment studies used to prepare for long-term energy transitions and develop robust strategies to address climate change are highly dependent on the assessment of technology characteristics and availability. The electric power sector in the United States recently experienced a significant cost escalation: e.g. construction costs for large plants such as nuclear and coal-fired power plants doubled between 2003 and 2007. In this work, we assess the main drivers of this escalation. While many factors have affected costs, some of the most significant include cost of materials, particularly the price of metals and to a lesser extent cement, possible increases in labor quantity requirements, the aggressive worldwide competition for power plant design and construction resources, driven by high demand in Asia, regulatory tightening, and general uncertainty about future regulations and climate policies. We recalibrate power sector technology costs in the Global Change Assessment Model (GCAM) based on an extensive literature review of recent (post-2010) studies and in the process develop a coherent and updated set of current cost and performance assumptions for all major electricity-generating technologies. While current cost and performance assumptions of electricity-generating technologies are key drivers of short-term technology deployment and technology mix in the electricity sector, medium- and long-term deployment pathways are significantly affected by assumed efficiency improvement rates and cost reductions. Furthermore, we develop and demonstrate a method to forecast efficiency and construction cost of power plants and a sensitivity analysis to explore the importance of such assumptions in future scenarios generated by GCAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗