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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 757 records · Page 42

Ocean Carbon From Space: Current Status and Priorities for the Next Decade

The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.

oceanography↗

NASA: Model development for human factors interfacing

The results of an intensive literature review in the general topics of human error analysis, stress and job performance, and accident and safety analysis revealed no usable techniques or approaches for analyzing human error in ground or space operations tasks. A task review model is described and proposed to be developed in order to reduce the degree of labor intensiveness in ground and space operations tasks. An extensive number of annotated references are provided.

Smith, L. L.↗

Identification of linear system models and state estimators for controls

The following paper is presented in viewgraph format and covers topics including: (1) linear state feedback control system; (2) Kalman filter state estimation; (3) relation between residual and stochastic part of output; (4) obtaining Kalman filter gain; (5) state estimation under unknown system model and unknown noises; and (6) relationship between filter Markov parameters and system Markov parameters.

Chen, Chung-Wen↗

Battery Resistance Analysis of ISS Power System

The computer package, SPACE (Systems Power Analysis for Capability Evaluation) was created by the members of LT-9D to perform power analysis and modeling of the electrical power system on the International Space Station (ISS). Written in FORTRAN, SPACE comprises thousands of lines of code and has been used profficiently in analyzing missions to the ISS. LT-9D has also used its expertise recently to investigate the batteries onboard the Hubble telescope. During the summer of 2004, I worked with the members of LT-9D, under the care of Dave McKissock. Solar energy will power the ISS through eight solar arrays when the ISS is completed, although only two arrays are currently connected. During the majority of the periods of sunlight, the solar arrays provide enough energy for the ISS. However, rechargeable Nickel-Hydrogen batteries are used during eclipse periods or at other times when the solar arrays cannot be used (at docking for example, when the arrays are turned so that they will not be damaged by the Shuttle). Thirty-eight battery cells are connected in series, which make up an ORU (Orbital Replacement Unit). An ISS "battery" is composed of two ORUs. a great deal of time into finding the best way to represent them in SPACE. During my internship, I investigated the resistance of the ISS batteries. SPACE constructs plots of battery charge and discharge voltages vs. time using a constant current. To accommodate for a time-varying current, the voltages are adjusted using the formula, DeltaV = DeltaI * Cell Resistance. To enhance our model of the battery resistance, my research concentrated on several topics: investigating the resistance of a qualification unit battery (using data gathered by LORAL), comparing the resistance of the qualification unit to SPACE, looking at the internal resistance and wiring resistance, and examining the impact of possible recommended changes to SPACE. The ISS batteries have been found to be very difficult to model, and LT-9D has dedicated

Newstadt, Gregory E.↗

Gravitational Biology: The Rat Model

In this session, Session JP3, the discussion focuses on the following topics: Morphology of brain, pituitary and thyroid in the rats exposed to altered gravity; Biochemical Properties of B Adrenoceptors After Spaceflight (LMS-STS78) or Hindlimb Suspension in Rats; Influence of Hypergravity on the Development of Monoaminergic Systems in the Rat Spinal Cord; A Vestibular Evoked Potentials (VsEPs) Study of the Function of the Otolith Organs in Different Head Orientations with respect to Earth Gravity Vector in the Rat; Quantitative Observations on the Structure of Selected Proprioceptive Components in Adult Rats that Underwent About Half of their Fetal Development in Space; Effects of a Nine-Day Shuttle Mission on the Development of the Neonatal Rat Nervous System, A Behavioral Study; Muscle Atrophy Associated to Microgravity in Rat, Basic Data For Countermeasures; Simulated Weightlessness by Unloading in the Rat, Results of a Time Course Study of Biochemical Events Occurring During Unloading and Lack of Effect of a rhBNP-2 Treatment on Bone Formation and Bone Mineral Content in Unloading Rats; and Cytological Mechanism of the Osteogenesis Under Microgravity Conditions.

Source record↗

A review of machine learning in building load prediction

The surge of machine learning in recent years has been empowering engineer modeling in various fields. The decreasing hardware cost, increasing data accessibility, and advances of building automation system (BAS) allow the collection and storage of a significant amount of building operation data. The two facts provide great opportunities of applying machine learning to building energy systems modeling and analysis. There are a great number of research papers on this topic but there lacks a comprehensive and general review to summarize the current development, limitations, gaps and future trend. In this review paper series, machine learning techniques in building energy system modeling and analysis are reviewed under the organization and logic of the machine learning definition by Tom M. Mitchell: a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. This paper is the first part of the review paper series, which focuses on building load prediction. First, the applications of building load prediction model (task T) are reviewed. Then, the modeling algorithms improving machine learning performance and accuracy (performance P) are reviewed. At the same time, the literature on the data perspective for modeling (experience E), including data engineering from sensors level to data level, pre-processing, feature extraction and selection, is reviewed. Finally, what is well-studied and what is lacking but with great potential are concluded; the gaps between present and future utilization of machine learning techniques are identified; the future trend and development are also predicted. The target readers of this paper are not only researchers from the building side who can get exposed to cutting edge machine learning tools, but also those from machine learning side who can understand the potential and challenge to apply machine learning in buildings.

Liang, Zhang↗

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement: Preprint

Distribution system resilience enhancement is an important topic to ensure customers have access to the power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecasts. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗

Water isotopes, climate variability, and the hydrological cycle: recent advances and new frontiers

Abstract The hydrologic cycle is a fundamental component of the climate system with critical societal and ecological relevance. Yet gaps persist in our understanding of water fluxes and their response to increased greenhouse gas forcing. The stable isotope ratios of oxygen and hydrogen in water provide a unique opportunity to evaluate hydrological processes and investigate their role in the variability of the climate system and its sensitivity to change. Water isotopes also form the basis of many paleoclimate proxies in a variety of archives, including ice cores, lake and marine sediments, corals, and speleothems. These records hold most of the available information about past hydrologic variability prior to instrumental observations. Water isotopes thus provide a ‘common currency’ that links paleoclimate archives to modern observations, allowing us to evaluate hydrologic processes and their effects on climate variability on a wide range of time and length scales. Building on previous literature summarizing advancements in water isotopic measurements and modeling and describe water isotopic applications for understanding hydrological processes, this topical review reflects on new insights about climate variability from isotopic studies. We highlight new work and opportunities to enhance our understanding and predictive skill and offer a set of recommendations to advance observational and model-based tools for climate research. Finally, we highlight opportunities to better constrain climate sensitivity and identify anthropogenically-driven hydrologic changes within the inherently noisy background of natural climate variability.

Dee, Sylvia (ORCID:000000022140785X)↗

Earth Observing System (EOS) Snow and Ice Products for Observation and Modeling

Snow and ice are the key components of the Earth's cryosphere, and their influence on the Earth's energy balance is very significant due at least in part to the large areal extent and high albedo characterizing these features. Large changes in the cryosphere have been measured over the last century and especially over the past decade, and remote sensing plays a pivotal role in documenting these changes. Many of NASA's Earth Observing System (EOS) products derived from instruments on the Terra, Aqua, and Ice, Cloud and land Elevation Satellite (ICESat) satellites are useful for measuring changes in features that are associated with climate change. The utility of the products is continually enhanced as the length of the time series increases. To gain a more coherent view of the cryosphere and its historical and recent changes, the EOS products may be employed together, in conjunction with other sources of data, and in models. To further this goal, the first EOS Snow and Ice Products Workshop was convened. The specific goals of the workshop were to provide current and prospective users of EOS snow and ice products up-to-date information on the products, their validation status and future enhancements, to help users utilize the data products through hands-on demonstrations, and to facilitate the integration of EOS products into models. Oral and poster sessions representing a wide variety of snow and ice topics were held; three panels were also convened to discuss workshop themes. Panel discussions focused on data fusion and assimilation of the products into models. Approximately 110 people attended, representing a wide array of interests and organizations in the cryospheric community.

Hall, D.↗

Mathematical Modeling of Ni/H2 and Li-Ion Batteries

The modelling effort outlined in this viewgraph presentation encompasses the following topics: 1) Electrochemical Deposition of Nickel Hydroxide; 2) Deposition rates of thin films; 3) Impregnation of porous electrodes; 4) Experimental Characterization of Nickel Hydroxide; 5) Diffusion coefficients of protons; 6) Self-discharge rates (i.e., oxygen-evolution kinetics); 7) Hysteresis between charge and discharge; 8) Capacity loss on cycling; 9) Experimental Verification of the Ni/H2 Battery Model; 10) Mathematical Modeling Li-Ion Batteries; 11) Experimental Verification of the Li-Ion Battery Model; 11) Integrated Power System Models for Satellites; and 12) Experimental Verification of Integrated-Systems Model.

Weidner, John W.↗

Modeling Nitrogen Oxides in the Lower Stratosphere

This talk will focus on the status of current understanding (not a historical review) as regards modeling nitrogen oxides (NOy) in the lower stratosphere (LS). The presentation will be organized around three major areas of process understanding: 1) NOy sources, sinks, and transport to the LS, 2) NOy species partitioning, and 3) polar multiphase processes. In each area, process topics will be identified with an estimate of the degree of confidence associated with their representation in numerical models. Several exotic and/or speculative processes will also be discussed. Those topics associated with low confidence or knowledge gaps, weighted by their prospective importance in stratospheric chemical modeling, will be collected into recommendations for further study. Suggested approaches to further study will be presented for discussion.

Kawa, S. Randy↗

A numerical homogenization method for heterogeneous, anisotropic elastic media based on multiscale theory

The development of reliable methods for upscaling fine scale models of elastic media has long been an important topic for rock physics and applied seismology. Several effective medium theories have been developed to provide elastic parameters for materials such as finely layered media or randomly oriented or aligned fractures. In such cases, the analytic solutions for upscaled properties can be used for accurate prediction of wave propagation. However, such theories cannot be applied directly to homogenize elastic media with more complex, arbitrary spatial heterogeneity. We therefore propose a numerical homogenization algorithm based on multiscale finite element methods for simulating elastic wave propagation in heterogeneous, anisotropic elastic media. Specifically, our method used multiscale basis functions obtained from a local linear elasticity problem with appropriately defined boundary conditions. Homogenized, effective medium parameters were then computed using these basis functions, and the approach applied a numerical discretization that is similar to the rotated staggered-grid finite difference scheme. Comparisons of the results from our method and from conventional, analytical approaches for finely layered media showed that the homogenization reliably estimated elastic parameters for this simple geometry. Additional tests examined anisotropic models with arbitrary spatial heterogeneity where the average size of the heterogeneities ranged from several centimeters to several meters, and the ratio between the dominant wavelength and the average size of the arbitrary heterogeneities ranged from 10 to 100. Comparisons to finite-difference simulations proved that the numerical homogenization was equally accurate for these complex cases.

58 GEOSCIENCES↗

Ice Nuclei in Marine Air: Biogenic Particles or Dust?

Ice nuclei impact clouds, but their sources and distribution in the atmosphere are still not well known. Particularly little attention has been paid to IN sources in marine environments, although evidence from field studies suggests that IN populations in remote marine regions may be dominated by primary biogenic particles associated with sea spray. In this exploratory model study, we aim to bring attention to this long-neglected topic and identify promising target regions for future field campaigns. We assess the likely global distribution of marine biogenic ice nuclei using a combination of historical observations, satellite data and model output. By comparing simulated marine biogenic immersion IN distributions and dust immersion IN distributions, we predict strong regional differences in the importance of marine biogenic IN relative to dust IN. Our analysis suggests that marine biogenic IN are most likely to play a dominant role in determining IN concentrations in near-surface-air over the Southern Ocean, so future field campaigns aimed at investigating marine biogenic IN should target that region. Climate related changes in the abundance and emission of biogenic marine IN could affect marine cloud properties, thereby introducing previously unconsidered feedbacks that influence the hydrological cycle and the Earth’s energy balance. Furthermore, marine biogenic IN may be an important aspect to consider in proposals for marine cloud brightening by artificial sea spray production.

air↗

Vadose and Saturated Zone Flow and Transport Model Package Report for the Active Trenches of the Low-Level Burial Grounds, Hanford Site, Washington

This model package report (MPR) documents the development of the integrated vadose and saturated zone flow and transport model developed for the performance assessment of Trenches 31 and 34 in the low-level burial grounds (LLBGs). This modeling capability is intended for use in addressing the analysis requirements outlined in DOE O 435.1, Chg 1, Radioactive Waste Management1. The overall objective of the modeling effort is to provide a basis for making informed disposal decisions pertinent to Trenches 31 and 34. The purpose of the MPR is to document the development of the three-dimensional numerical vadose zone and saturated flow and transport model test case and evaluate its adequacy to support the LLBG performance assessment. The purpose is not to present results for DOE 435.1 decision making. The use of the model to perform base case and sensitivity analysis for the LLBG performance assessment, including inputs and results, is documented separately in subsequent environmental calculation files. This report discusses the development and translation of the conceptual model for flow and contaminant transport into the LLBG performance assessment three-dimensional numerical flow and transport model evaluated using the Subsurface Transport Over Multiple Phases (STOMP©) simulator. The development of representative geologic framework is described along with the implementation of waste release models used to represent contaminant release from waste disposed in the trenches. The report also provides the technical basis for specific model parameters and boundary conditions, along with description of modeling assumptions. This MPR includes certain calculations that are necessary to demonstrate the soundness of the model. Results provided by the model include vadose zone and saturated zone flow fields, and estimates of the possible future concentration in groundwater of technetium-99 and iodine-129 as example test cases. As an evaluation of the test cases, the model estimates of current vadose conditions are compared to available and analogous field and laboratory data, and compared to the results from the original performance assessment model (WHC-EP-0645, Performance Assessment for the Disposal of Low-Level Waste in the 200 West Area Burial Grounds 2 ). The features, events, and processes applicable to vadose zone and saturated zone flow and transport model are identified, and representative initial estimates for various parameters are documented. Note that the parameter estimates presented in this MPR are for illustration purposes, and may or may not reflect values selected for eventual performance assessment. Several key topical discussions (i.e., basis for recharge estimates, basis for vadose zone modeling, basis for saturated zone model development, and calibration) are included, which serve as the groundwork for confidence building for the groundwater pathway modeling and results. Numerical simulation results based on an example test case are included to illustrate the use of the combined saturated-unsaturated model in performance assessment calculations. Sensitivity and uncertainty results are not included in this MPR. Those results will be included in future environmental calculation files. The inclusion of the trapezoidal trench geometry and construction details in the finite difference grid introduces some gross simplifications regarding the trench and liner systems. The model test case presented in this MPR includes the assumption that the trench liner system does not affect flow through or around the trenches after the liner system is assumed to fail. This MPR also includes results of other test cases that involve alternate assumptions about how to incorporate the hydraulic effects of the trenches into the vadose zone of the model. These alternate cases do not attempt to account for the presence of the liner system after its assumed failure either. None of these cases is considered to be the base case at this time. Analysis and alternate cases that attempt to account for the presence of the liner system in greater detail, and its effect on flow through and around it, are to be documented in subsequent environmental calculation files. Depending on the results of those analyses and alternate cases, the eventual base case may involve more detailed inclusion of the effects of the liner system hydraulics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NOAA/NASA/DOD Workshop on Satellite Data Assimilation

A workshop on the assimilation of satellite sounding information using global forecast and climate models was held at College Park, MD, 23-25 August 1999. Topics discussed included: comparisons of assimilations of satellite retrievals versus satellite-observed radiances, planning for the use of advanced infrared sounders, the use of satellite sounding data affected by land surfaces, radiative transfer issues, and error characteristics of models and observations. The workshop concluded with a number of general and specific recommendations to advance the state of the art of assimilation of satellite sounding data.

Errico, Ronald M.↗

Utah FORGE: Phase 2C Topical Report

This is the topical report that wraps up the work and results achieved during Utah FORGE Phase 2C. The zip file includes several folders containing (1) an overview; (2) the results; (3) the lessons learned; and (4) the conclusions. It also contains a folder containing appendices including (1) the updated permitting inventory; (2) the updated site characterization data inventory; (3) the updated conceptual geological model; and (4) the stakeholders engagement and outreach status.

15 GEOTHERMAL ENERGY↗

Real-Time Identification of Oxygen Vacancy Centers in LiNbO 3 and SrTiO 3 during Irradiation with High Energy Particles

Oxygen vacancies are known to play a central role in the optoelectronic properties of oxide perovskites. A detailed description of the exact mechanisms by which oxygen vacancies govern such properties, however, is still quite incomplete. The unambiguous identification of oxygen vacancies has been a subject of intense discussion. Interest in oxygen vacancies is not purely academic. Precise control of oxygen vacancies has potential technological benefits in optoelectronic devices. In this review paper, we focus our attention on the generation of oxygen vacancies by irradiation with high energy particles. Irradiation constitutes an efficient and reliable strategy to introduce, monitor, and characterize oxygen vacancies. Unfortunately, this technique has been underexploited despite its demonstrated advantages. This review revisits the main experimental results that have been obtained for oxygen vacancy centers (a) under high energy electron irradiation (100 keV–1 MeV) in LiNbO 3 , and (b) during irradiation with high-energy heavy (1–20 MeV) ions in SrTiO 3 . In both cases, the experiments have used real-time and in situ optical detection. Moreover, the present paper discusses the obtained results in relation to present knowledge from both the experimental and theoretical perspectives. Our view is that a consistent picture is now emerging on the structure and relevant optical features (absorption and emission spectra) of these centers. One key aspect of the topic pertains to the generation of self-trapped electrons as small polarons by irradiation of the crystal lattice and their stabilization by oxygen vacancies. What has been learned by observing the interplay between polarons and vacancies has inspired new models for color centers in dielectric crystals, models which represent an advancement from the early models of color centers in alkali halides and simple oxides. The topic discussed in this review is particularly useful to better understand the complex effects of different types of radiation on the defect structure of those materials, therefore providing relevant clues for nuclear engineering applications.

36 MATERIALS SCIENCE↗

Laboratory for Engineering Man/Machine Systems (LEMS): System identification, model reduction and deconvolution filtering using Fourier based modulating signals and high order statistics

Several important problems in the fields of signal processing and model identification, such as system structure identification, frequency response determination, high order model reduction, high resolution frequency analysis, deconvolution filtering, and etc. Each of these topics involves a wide range of applications and has received considerable attention. Using the Fourier based sinusoidal modulating signals, it is shown that a discrete autoregressive model can be constructed for the least squares identification of continuous systems. Some identification algorithms are presented for both SISO and MIMO systems frequency response determination using only transient data. Also, several new schemes for model reduction were developed. Based upon the complex sinusoidal modulating signals, a parametric least squares algorithm for high resolution frequency estimation is proposed. Numerical examples show that the proposed algorithm gives better performance than the usual. Also, the problem was studied of deconvolution and parameter identification of a general noncausal nonminimum phase ARMA system driven by non-Gaussian stationary random processes. Algorithms are introduced for inverse cumulant estimation, both in the frequency domain via the FFT algorithms and in the domain via the least squares algorithm.

Pan, Jianqiang↗