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At least 883 records · Page 49

Assessment of Current Global and Regional Mean Sea Level Estimates Based on the TOPEX/Poseidon Jason-1 and 2 Climate Data Record

Recent developments in Precise Orbit Determinations (POD) due to in particular to revisions to the terrestrial reference frame realization and the time variable gravity (TVG) continues to provide improvements to the accuracy and stability of the PO directly affecting mean sea level (MSL) estimates. Long-term credible MSL estimates require the development and continued maintenance of a stable reference frame, along with vigilant monitoring of the performance of the independent tracking systems used to calculate the orbits for altimeter spacecrafts. The stringent MSL accuracy requirements of a few tenths of an mm/yr are particularly essential for mass budget closure analysis over the relative short time period of Jason-l &2, GRACE, and Argo coincident measurements. In an effort to adhere to cross mission consistency, we have generated a full time series of experimental orbits (GSFC stdlllO) for TOPEX/Poseidon (TP), Jason-I, and OSTM based on an improved terrestrial reference frame (TRF) realization (ITRF2008), revised static (GGM03s), and time variable gravity field (Eigen6s). In this presentation we assess the impact of the revised precision orbits on inter-mission bias estimates, and resultant global and regional MSL trends. Tide gauge verification results are shown to assess the current stability of the Jason-2 sea surface height time series that suggests a possible discontinuity initiated in early 2010. Although the Jason-2 time series is relatively short (approximately 3 years), a thorough review of the entire suite of geophysical and environmental range corrections is warranted and is underway to maintain the fidelity of the record.

Beckley, B. D.↗

Energy modeling and efficiency analysis of aluminum die-casting processes

Energy modeling and efficiency analysis are considered the foundation of manufacturing process optimization to improve quality and efficiency and reduce energy consumption and carbon emissions during aluminum die-casting processes. Our report introduced an energy modeling method to connect gas and electric energy consumption with production rate of aluminum die-casting processes based on data collected at workshops with various combination of machines and products. The detailed modeling process involved the development of a data-acquiring system and the comparison of various kinds of nonlinear regression methods. The resulting models were confirmed with actual production data and were also used to improve production scheduling. Furthermore, it was found that if the modeling results are reasonably used and production is accordingly well-scheduled, 10 to 15% of energy savings could be realized without sacrificing profits.

42 ENGINEERING↗

Investigation of Frozen Chemistry for Molten Salt Reactors (MSRs)

Understanding accident progression and the potential/conditions for fission product release from fuel is necessary to evaluate safety for any nuclear reactor system. Molten Salt Reactors (MSRs) under development need such analysis to support safety evaluations. Fission product chemistry specific to MSR concepts is a critical area that introduces distinct considerations relative to the current state-of-knowledge in reactor safety, primarily developed for water-moderated nuclear reactor systems. In Light Water Reactor (LWR) systems, it is necessary to capture the chemical interaction of fission products with the reactor evironment, containment and confinement systems. The overall effects at this point are relatively well understood for the purposes of performing safety evaluations. A key insight from LWR studies is that fission product chemical behavior can be reasonably captured by modeling approaches where the chemistry is "frozen". These modeling approaches assume that radionuclide reaction and speciation can be represented by chemical classes, each with characteristic transport behavior that is invariant under a broad range of thermochemical conditions. However, radionuclides can exhibit a range of behavior in the liquid salt-melt phase of the coolant used in MSRs. Radionuclides, salt, and the metal containment surfaces (i.e. pipes) can co-exist in dynamic equilibrium that could evolve with small system mass changes. A detailed investigation to the degree the equilibrium state can dynamically evolve with changes in the conditions of the molten salt mixture has not been previously conducted. It is currently not well understood where frozen chemistry assumptions are valid. Expanding the state-of-knowledge in this regard is relevant to better assessing the range of chemical effects that should be incorporated as part of MSR safety assessments. This investigation used the Oak Ridge Isotope GENeration (ORIGEN) module of the Standardized Computer-Analysis for Licensing Evaluation (SCALE) code to generate simulated radionuclide inventories for the MSR Experiment (MSRE) and then modeled reactor chemical speciation using the Molten Salt Thermodynamic Database – Thermochemical (MSTDB-TC) coupled with Thermochimica. The effect of composition variation during decay of fission product inventory in a molten salt over a period of 500 days prolonged post- at multiple temperatures was studied. Mass fractions for fluorine and berilium were varied in order to probe the effects of free fluorine control. Finally, speciation of fluoride reactors were showed by comparing MSRE readionuclide inventories with a FLiBe based molten salt breeder reactor (MSBR). The results showed that fission product mass change has little effect on phase mass changes and vapor pressures for fluoride species, but differ with varying carrier and fuel salt compositions. However, iodine species were found to have a vapor pressure not only dependent on temperature, but also the free fluorine potential, releasing iodine when the free fluorine potential is equal to the iodine inventory. This observation, however, arose under free fluorine potentials that are very unlikely to be realized in typical molten salt mixtures. Despite this observation, temperature was found to be the dominant parameter that drove phase change and fission product species vapor pressure. The results indicate that the current frozen chemistry approach is adequate for MSR analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Combined Weekly Coordinate Solutions from SLR and DORIS

In International Terrestrial Reference Frame (ITRF) 2005 and ITRF2008, the approach for the construction of solutions by the IERS has been for individual analysis centers of each technique to process geodetic tracking data, and for each technique to develop a solution (or contribution) that is integrated into the final ITRF solution by careful combination of the technique solutions. The connections between the geodetic networks are realized by the application of local ties. In an alternate approach, we may assure processing homogeneity by creating normal equations for different techniques with the same orbit determination software, using identically derived algorithms. Another derivative of this approach is to realize the ties between the techniques using satellites tracked with multiple techniques; in effect tieing the networks together using satellite dynamics. In this solution, we develop a time series and a set of cumulative solutions from Satellite Laser Ranging (SLR) & Doppler Orbitography and Radio-positioning Integrated by Satellite (DORIS) based on homogeneous processing with the NASA GEODYN precise orbit determination suite of programs, where we jointly combine weekly the SLR data to Lageos1, Lageos2, Starlette, and Stella with the DORIS data from SPOT2-SPOT5, as well as satellites that utilize both techniques (TOPEX/Poseidon, Envisat, Jason-2). We discuss the modeling that is applied including upgrades implemented since the submission of the GSC ITRF2008 contributions for IDS. Firstly, we compare the SLR-only solutions comprising four geodetic satellites with the standard approach of utilizing only Lageos1 & Lageos2. Secondly, we evaluate the impact on the DORIS coordinates of the joint analysis with the SLR data.

Lemoine, F.↗

Incorporating the Impacts of Climate Change on Hydrology in a Performance Assessment Model - 20403

The evidence of climate change is increasingly well-documented and impacts should be incorporated in performance assessment studies. The current climate literature provides both observational evidence and climate model projections of climate trends and/or climate change in the late 20. and early 21. centuries for North America and the northeast United States. Probabilistic modeling is a core requirement for quantifying uncertainty and evaluating its impacts. Not evaluating future climate states in a performance assessment because of the existence of uncertainty is contradictory to good modeling practices - the most uncertain issues and parameters require the most attention in effective probabilistic modeling. Excluding climate change limits development of modeling information that could aid in effective decision making. In this work we develop methods to use the output from hydrologic models and analysis of historical aerial imagery to quantify and implement the impacts of climate change on hydrologic processes at a nuclear waste site in West Valley, New York. Specifically, we used the HELP (Hydraulic Performance of Landfill Performance) model to characterize key hydrologic processes under both current and future climate conditions to assess the impacts of changing climate on hydrology. A suite of previous climatic models were reviewed and synthesized to produce a cohesive representation of the current state of knowledge of the impact of climate change on important model inputs such as precipitation. Output from the HELP simulations was coupled to the GoldSim model that was used to develop the Probabilistic Performance Assessment (PPA) approach through the application of a novel 'nearest neighbor' technique. First, several thousand realizations were generated from the HELP model using a Latin Hypercube experimental design to ensure adequate coverage of the parameter space of explanatory variables used to drive HELP. For example, porosity is a physical parameter that is used as an input to both HELP and the GoldSim PA model. We then ran sensitivity analysis (SA) algorithms on the output of HELP for each of the responses of interest. For each predictor, each time we build an SA model we get a different value for the sensitivity index (SI). From the collection of all the SA models, the average was computed among all of the SIs to represent the predictor within the context of the nearest neighbor approach. That is, we conduct SA on each HELP outcome for each scenario. This gives us parameter sensitivity indices for the outcomes. We average the parameter sensitivity indices across the outcomes to get the average SI for a scenario. For each realization that is generated from the Goldsim PA model, Goldsim generates random values for physical/empirical parameters that HELP uses as well. For each vector of physical/empirical parameters that Goldsim generates, the vector from the 5,000 HELP runs that is most 'similar' to the Goldsim vector is computed using the nearest neighbor approach. In this context 'similar' means minimization of the SA-weighted sum of the absolute differences among the 5,000 values computed for this statistic, where each value corresponds to a different HELP realization. In order to account for the impacts of climate change, this process was repeated using the spatially downscaled future climate projections. For each of the key parameters of interest, it was assumed that a linear change depicted the relationship between the values for the present day and those for 2100. In this way, the climatically-driven changes in key parameters used to inform the GoldSim model are quantified and incorporated into the PA model output for the future. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An analysis of the adaptability of Loran-C to air navigation

The sources of position errors characteristics of the Loran-C navigation system were identified. Particular emphasis was given to their point on entry as well as their elimination. It is shown that the ratio of realized accuracy to theoretical accuracy of the Loran-C is highly receiver dependent.

Littlefield, J. A.↗

Reduced order models for assessing CO 2 impacts in shallow unconfined aquifers

Risk assessment studies of potential CO 2 sequestration projects consider many factors, including the possibility of brine and/or CO 2 leakage from the storage reservoir. Detailed multiphase reactive transport simulations have been developed to predict the impact of such leaks on shallow groundwater quality; however, these simulations are computationally expensive and thus difficult to directly embed in a probabilistic risk assessment analysis. Here we present a process for developing computationally fast reduced-order models which emulate key features of the more detailed reactive transport simulations. A large ensemble of simulations that take into account uncertainty in aquifer characteristics and CO 2 /brine leakage scenarios were performed. Twelve simulation outputs of interest were used to develop response surfaces (RSs) using a MARS (multivariate adaptive regression splines) algorithm (Milborrow, 2015). A key part of this study is to compare different measures of ROM accuracy. We then show that for some computed outputs, MARS performs very well in matching the simulation data. The capability of the RS to predict simulation outputs for parameter combinations not used in RS development was tested using cross-validation. Again, for some outputs, these results were quite good. For other outputs, however, the method performs relatively poorly. Performance was best for predicting the volume of depressed-pH-plumes, and was relatively poor for predicting organic and trace metal plume volumes. We believe several factors, including the non-linearity of the problem, complexity of the geochemistry, and granularity in the simulation results, contribute to this varied performance. The reduced order models were developed principally to be used in probabilistic performance analysis where a large range of scenarios are considered and ensemble performance is calculated. We demonstrate that they effectively predict the ensemble behavior. But, the performance of the RSs is much less accurate when used to predict time-varying outputs from a single simulation. If an analysis requires only a small number of scenarios to be investigated, computationally expensive physics-based simulations would likely provide more reliable results. Finally, if the aggregate behavior of a large number of realizations is the focus, as will be the case in probabilistic quantitative risk assessment, the methodology presented here is relatively robust.

54 ENVIRONMENTAL SCIENCES↗

Multimodal quantification of degradation pathways during extreme fast charging of lithium-ion batteries

Enabling fast charging of Li-ion batteries will be a key step towards realizing the technology's full potential in electric vehicles. Currently, fast charging is limited by a variety of processes that reduce cell capacity upon extended cycling. Using a multimodal approach combining incremental capacity analysis (dQ/dV), high energy X-ray diffraction (HEXRD), and mass spectrometry titration (MST), we identify specific degradation mechanisms—including Li plating, dead Li x C 6 formation, Li 2 C 2 formation, solid carbonate solid-electrolyte interphase (SEI) deposition, and loss of positive electrode active material (LAM PE )—that occur during extended fast charge cycling. We find that Li plating is the major source of capacity loss in cells cycled at 6C, while non-carbonate SEI species deposition on the graphite anode is the main source of capacity loss when cycled at 4C. We also study local degradative phenomena by examining specific ~1–5 cm 2 regions of the cells using HEXRD and MST. Here, we find that plated Li is often collocated with dead Li x C 6 , Li 2 C 2 , and solid carbonate SEI species, and these additional species cumulatively account for ~20% of the capacity lost during 6C cycling. Finally, in a cell with an anomalously high amount of LAM PE (quantified via dQ/dV), we find that regions of cathode degradation were accompanied by non-carbonate SEI products on the adjacent region of the anode. We postulate that this phenomenon arises due to crosstalk between the electrodes, wherein soluble electrolyte oxidation products formed at the delithiated cathode migrate to the graphite anode and are ultimately deposited on the graphite surface. This work demonstrates the utility of combining multiple characterization techniques to reveal a more holistic understanding of degradative phenomena that occur across multiple length scales during fast charge.

25 ENERGY STORAGE↗

Beta gallium oxide (β-Ga 2 O 3 ) nanoelectromechanical transducer for dual-modality solar-blind ultraviolet light detection

Empowered by an ultrawide bandgap ( E g = 4.5–4.9 eV), beta gallium oxide (β-Ga 2 O 3 ) crystal is an ideal material for solar-blind ultraviolet (SBUV, λ < 280 nm) detection. Here, we report on the first demonstration of dual-modality SBUV light sensing integrated in the same device enabled by multi-physics coupling across photo-electrical and photo-thermo-mechanical domains. The specially designed suspended β-Ga 2 O 3 nanoelectromechanical systems (NEMS) transducer reveals dual-modality responses, with a photocurrent responsivity of 4 mA/W and a frequency shift responsivity of 250 Hz/nW, upon SBUV light exposure. An additional demonstration of a β-Ga 2 O 3 photo-field-effect transistor exhibits a boosted responsivity of 63 A/W. Analysis on the device suggests that reducing the thickness and length of the transducer could further improve the SBUV light sensing responsivities for both modalities. The demonstration could pave the way for future realization of SBUV detectors with dual modalities for enhanced detection fidelity, or respectively optimized for different sensing scenarios.

36 MATERIALS SCIENCE↗

Three-dimensional Majorana fermions in chiral superconductors

Using a systematic symmetry and topology analysis, we establish that three-dimensional chiral superconductors with strong spin-orbit coupling and odd-parity pairing generically host low-energy nodal quasiparticles that are spin-nondegenerate and realize Majorana fermions in three dimensions. By examining all types of chiral Cooper pairs with total angular momentum J formed by Bloch electrons with angular momentum j in crystals, we obtain a comprehensive classification of gapless Majorana quasiparticles in terms of energy-momentum relation and location on the Fermi surface. We show that the existence of bulk Majorana fermions in the vicinity of spin-selective point nodes is rooted in the nonunitary nature of chiral pairing in spin-orbit–coupled superconductors. We address experimental signatures of Majorana fermions and find that the nuclear magnetic resonance spin relaxation rate is significantly suppressed for nuclear spins polarized along the nodal direction as a consequence of the spin-selective Majorana nature of nodal quasiparticles. Furthermore, Majorana nodes in the bulk have nontrivial topology and imply the presence of Majorana bound states on the surface, which form arcs in momentum space. We conclude by proposing the heavy fermion superconductor PrOs 4 Sb 12 and related materials as promising candidates for nonunitary chiral superconductors hosting three-dimensional Majorana fermions.

36 MATERIALS SCIENCE↗

Towards a data-driven model of hadronization using normalizing flows

We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Additionally, we introduce a new training method for normalizing flows, termed MAGIC, that improves the agreement between simulated and experimental distributions of high-level (macroscopic) observables by adjusting single-emission (microscopic) dynamics. Our results constitute an important step toward realizing a machine-learning based model of hadronization that utilizes experimental data during training. Finally, we demonstrate how a Bayesian extension to this normalizing-flow architecture can be used to provide analysis of statistical and modeling uncertainties on the generated observable distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Final Technical Report for ``Paths to Discovery at the LHC : Dark Matter and Track Triggering"

Particle Dark Matter (DM) is perhaps the most compelling and experimentally well-motivated new physics scenario anticipated at the Large Hadron Collider (LHC). The DE-SC0014073 award allowed the PI to define and pursue a path to the discovery of Dark Matter in Run-2 of the LHC with the Compact Muon Solenoid (CMS) experiment. CMS can probe regions of Dark Matter phase-space that direct and indirect detection experiments are unable to constrain. The PI’s team initiated the exploration of these regions, searching specifically for the associated production of Dark Matter with top quarks. The effort focuses on the high-yield, hadronic decays of W bosons produced in top decay, which provides the highest sensitivity to DM produced via through low-mass spin-0 mediators. The group developed identification algorithms that achieve high efficiency and purity in the selection of hadronic top decays, and analysis techniques that provide powerful signal discrimination in Run-2. The ultimate reach of new physics searches with CMS will be established at the high-luminosity LHC (HL-LHC). To fully realize the sensitivity the HL-LHC promises, CMS must minimize the impact of soft, inelastic (“pileup”) interactions on the real-time “trigger” system the experiment uses for data refinement. Charged particle trajectory information (“tracking”) will be essential for pileup mitigation at the HL-LHC. The award allowed the PI’s team to develop firmware-based data delivery and track fitting algorithms for an unprecedented, real-time tracking trigger to sustain the experiment’s sensitivity to new physics in the next decade.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

The RAVE-on Catalog of Stellar Atmospheric Parameters and Chemical Abundances for Chemo-dynamic Studies in the Gaia Era

The orbits, atmospheric parameters, chemical abundances, and ages of individual stars in the Milky Way provide the most comprehensive illustration of galaxy formation available. The Tycho- Gaia Astrometric Solution (TGAS) will deliver astrometric parameters for the largest ever sample of Milky Way stars, though its full potential cannot be realized without the addition of complementary spectroscopy. Among existing spectroscopic surveys, the RAdial Velocity Experiment (RAVE) has the largest overlap with TGAS (≳200,000 stars). We present a data-driven re-analysis of 520,781 RAVE spectra using The Cannon . For red giants, we build our model using high-fidelity APOGEE stellar parameters and abundances for stars that overlap with RAVE. For main sequence and sub-giant stars, our model uses stellar parameters from the K2/EPIC . We derive and validate effective temperature T {sub eff}, surface gravity log g , and chemical abundances of up to seven elements (O, Mg, Al, Si, Ca, Fe, and Ni). We report a total of 1,685,851 elemental abundances with a typical precision of 0.07 dex, a substantial improvement over previous RAVE data releases. The synthesis of RAVE-on and TGAS is the most powerful data set for chemo-dynamic analyses of the Milky Way ever produced.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA's SESAC report on research and analysis in space and Earth sciences

The Research and Analysis Program is the core of the OSSA program in the space and Earth sciences because it provides the means of identifying the most appropriate missions and ensures that scientific results are fully realized. Consequently, this program must be given a priority in funding that is commensurate with that of flight programs. The goals of the R&A program and its role in meeting present day OSSA objectives; management of the R&A program by NASA Headquarters Discipline Chiefs and Programs Managers; and funding and distribution trends are assessed. Recommendations are advanced for halting the declining support of this program.

Source record↗

Aerospace Systems Design in NASA's Collaborative Engineering Environment

Past designs of complex aerospace systems involved an environment consisting of collocated design teams with project managers, technical discipline experts, and other experts (e.g., manufacturing and systems operation). These experts were generally qualified only on the basis of past design experience and typically had access to a limited set of integrated analysis tools. These environments provided less than desirable design fidelity, often lead to the inability of assessing critical programmatic and technical issues (e.g., cost, risk, technical impacts), and generally derived a design that was not necessarily optimized across the entire system. The continually changing, modern aerospace industry demands systems design processes that involve the best talent available (no matter where it resides) and access to the the best design and analysis tools. A solution to these demands involves a design environment referred to as collaborative engineering. The collaborative engineering environment evolving within the National Aeronautics and Space Administration (NASA) is a capability that enables the Agency's engineering infrastructure to interact and use the best state-of-the-art tools and data across organizational boundaries. Using collaborative engineering, the collocated team is replaced with an interactive team structure where the team members are geographical distributed and the best engineering talent can be applied to the design effort regardless of physical location. In addition, a more efficient, higher quality design product is delivered by bringing together the best engineering talent with more up-to-date design and analysis tools. These tools are focused on interactive, multidisciplinary design and analysis with emphasis on the complete life cycle of the system, and they include nontraditional, integrated tools for life cycle cost estimation and risk assessment. NASA has made substantial progress during the last two years in developing a collaborative engineering environment. NASA is planning to use this collaborative engineering engineering infrastructure to provide better aerospace systems life cycle design and analysis, which includes analytical assessment of the technical and programmatic aspects of a system from "cradle to grave." This paper describes the recent NASA developments in the area of collaborative engineering, the benefits (realized and anticipated) of using the developed capability, and the long-term plans for implementing this capability across Agency.

Monell, Donald W.↗

Reusable Autonomy

Currently, spacecraft ground systems have a well defined and somewhat standard architecture and operations concept. Based on domain analysis studies of various control centers conducted over the years it is clear that ground systems have core capabilities and functionality that are common across all ground systems. This observation alone supports the realization of reuse. Additionally, spacecraft ground systems are increasing in their ability to do things autonomously. They are being engineered using advanced expert systems technology to provide automated support for operators. A clearer understanding of the possible roles of agent technology is advancing the prospects of greater autonomy for these systems. Many of their functional and management tasks are or could be supported by applied agent technology, the dynamics of the ground system's infrastructure could be monitored by agents, there are intelligent agent-based approaches to user-interfaces, etc. The premise of this paper is that the concepts associated with software reuse, applicable in consideration of classically-engineered ground systems, can be updated to address their application in highly agent-based realizations of future ground systems. As a somewhat simplified example consider the following situation, involving human agents in a ground system context. Let Group A of controllers be working on Mission X. They are responsible for the command, control and health and safety of the Mission X spacecraft. Let us suppose that mission X successfully completes it mission and is turned off. Group A could be dispersed or perhaps move to another Mission Y. In this case there would be reuse of the human agents from Mission X to Mission Y. The Group A agents perform their well-understood functions in a somewhat but related context. There will be a learning or familiarization process that the group A agents go through to make the new context, determined by the new Mission Y, understood. This simplified scenario highlights some of the major issues that need to be addressed when considering the situation where Group A is composed of software-based agents (not their human counterparts) and they migrate from one mission support system to another. This paper will address: - definition of an agent architecture appropriate to support reuse; - identification of non-mission-specific agent capabilities required; - appropriate knowledge representation schemes for mission-specific knowledge; - agent interface with mission-specific knowledge (a type of Learning); development of a fully-operational group of cooperative software agents for ground system support; architecture and operation of a repository of reusable agents that could be the source of intelligent components for realizing an autonomous (or nearly autonomous) agent-based ground system, and an agent-based approach to repository management and operation (an intelligent interface for human use of the repository in a ground-system development activity).

Truszkowski, Walt↗