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Review includes data on the chemical and physical properties of tellurium, its oxides, and fluorides, pertinent to the process problem of handling fission product tellurium in fluoride form. The technology of tellurium handling in nonaqueous processing of nuclear fuels is also reviewed.
A limitation has been identified in the existing test standards used for making controlled, two-body abrasion scratch measurements based solely on the width of the resultant score on the surface of the material. A new, more robust method is proposed for analyzing a surface scratch that takes into account the full three-dimensional profile of the displaced material. To accomplish this, a set of four volume- displacement metrics was systematically defined by normalizing the overall surface profile to denote statistically the area of relevance, termed the Zone of Interaction. From this baseline, depth of the trough and height of the plowed material are factored into the overall deformation assessment. Proof-of-concept data were collected and analyzed to demonstrate the performance of this proposed methodology. This technique takes advantage of advanced imaging capabilities that allow resolution of the scratched surface to be quantified in greater detail than was previously achievable. When reviewing existing data analysis techniques for conducting two-body abrasive scratch tests, it was found that the ASTM International Standard G 171 specified a generic metric based only on visually determined scratch width as a way to compare abraded materials. A limitation to this method was identified in that the scratch width is based on optical surface measurements, manually defined by approximating the boundaries, but does not consider the three-dimensional volume of material that was displaced. With large, potentially irregular deformations occurring on softer materials, it becomes unclear where to systematically determine the scratch width. Specifically, surface scratches on different samples may look the same from a top view, resulting in an identical scratch width measurement, but may vary in actual penetration depth and/or plowing deformation. Therefore, two different scratch profiles would be measured as having identical abrasion properties, although they differ significantly.
Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.
Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.
Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.
Demographic data of Sedum lanceolatum under a climate manipulation experiment (heating and watering). Dataset includes one .csv with demographic data for 232 individuals monitored over 2013-2014 which was used, in part, to draw conclusions in "Elevation effects on vital rate sensitivities generate variation in neighbor effects on population growth rate in Sedum lanceolatum" by Herzog et al. (in review). All data was collected under a watering and warming experiment as part of the Alpine Treeline Warming Experiment at Niwot Ridge, Colorado, USA. There are two main data file formats in this archive: comma-separated values (.csv) which can be read using any simple text editor program, such as TextEdit (Mac) and Notepad (Windows). The .pdf data user’s guide can be read using Adobe Acrobat Reader, or any other compatible software.
The present status of lunar knowledge based on U.S. and USSR lunar missions and the continuing analysis of lunar samples and data is reviewed. Particular attention given to exploration, samples, and recent concepts of the moon; the lunar environment; lunar surface processes; the lunar minerals, rocks, and regolith; chemical elements in the moon; physical properties of the lunar surface; and global and regional data about the moon.
The problem of proper reduction and treatment of the residual total magnetic field observed on satellite orbits is studied. The reduction procedure used for Pogo satellite data is reviewed, and a procedure is presented for reducing the residual total field observed on satellite orbits to a spherical surface. Several examples based on selected models are provided to demonstrate the accuracy of the formulas developed for continuation of the satellite data from an irregular to a spherical surface. This procedure is tested on a set of Pogo data covering the area that contains the Bangui magnetic anomaly in central Africa. A technique is also given for determining the field components on a spherical surface and calculating the total field in any fixed direction of the geomagnetic field.
Although our observing capabilities of solar-induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Additionally, biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in-situ SIF observing capability especially in “data desert” regions, improving cross-instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.
Techniques for the review, display, and manipulation of multidimensional data are developed and described. Multidimensional data is meant in this context to describe scalar data associated with a three dimensional geometry or otherwise too complex to be well represented by traditional graphs. Raster graphics techniques are used to display a shaded image of a three dimensional geometry. The use of color to represent scalar data associated with the geometries in shaded images is explored. Distinct hues are associated with discrete data ranges, thus emulating the traditional representation of data with isarithms, or lines of constant numerical value. Data ranges are alternatively associated with a continuous spectrum of hues to show subtler data trends. The application of raster graphics techniques to the display of bivariate functions is explored.
In the context of the Chicxulub impact, it became recently obvious that experimental and theoretical research on the shock behavior of sulfates is essential for an assessment of the role of shock-released gases in the K/T mass extinction. The Chicxulub crater is the most important large impact structure where the bolide penetrated a sedimentary layer with large amounts of interbedded anhydrite (Haughton has also significant anhydrite in the target). The sulfuric gas production by shock compression/decompression of anhydrite is an important issue, even if the size of Chicxulub crater is only half of the so far assumed size. The comparison of experimental data for anhydrite, shocked with different techniques at various laboratories, reveals large differences in the threshold pressures for melting and decomposition. To gain insight into this issue, we have made a theoretical investigation of the thermodynamic properties of anhydrite. The project includes the review of data published in the last 40 years - reasons to study anhydrite cover a wide field of interests: from industrial problems of cement and ceramic production to the analysis of nuclear underground explosions in salt domes, conducted in the USA and USSR in the 1970th.
The difficulties encountered when instrumenting solid rocket motors for acquiring strain data are reviewed, emphasizing the strong temperature dependence due to apparent strain effects. The development of a strain/temperature gage to overcome some of these problems is discussed. This gage is designed to produce low apparent strain when attached to a carbon-carbon substrate. Characterization and performance data for gages attached with ceramic cement to carbon-carbon tensile coupons are presented, and the effect of a flame-sprayed installation process is discussed.
The experimental results published before August 2020 from the various reaction and decay studies leading to nuclides of Z=55 to Z=72, 153 Ba, 153 La, 153 Ce, 153 Pr, 153 Nd, 153 Pm, 153 Sm, 153 Eu, 153 Gd, 153 Tb, 153 Dy, 153 Ho, 153 Er, 153 Tm, 153 Yb, 153 Lu, 153 Hf in the A=153 mass chain have been reviewed. These data are summarized and presented, together with adopted level schemes and properties. This work is intended to supersede the previous evaluation of the A=153 nuclides by R.G. Helmer (2006He06), which was published in Nuclear Data Sheets 107, 507 (2006).
The experimental results published before Aug 2022 from the various reaction and decay studies leading to nuclides of Z=56 to Z=72, 154 Ba, 154 La, 154 Ce, 154 Pr, 154 Nd, 154 Pm, 154 Sm, 154 Eu, 154 Gd, 154 Tb, 154 Dy, 154 Ho, 154 Er, 154 Tm, 154 Yb, 154 Lu, 154 Hf, in the A=154 mass chain have been reviewed. These data are collected and presented in decay or reaction datasets, together with Adopted Levels and gammas datasets that are the most extensive collections of nuclear structure data for each nuclide. Furthermore this work is intended to supersede the previous evaluation of the A=154 nuclides by C.W. Reich (2009Re14), which was published in Nuclear Data Sheets 110, 2257 (2009).
The main achievements of a 36-month research program are presented. The main objective was to gain more insight into the problem of crack growth under thermal mechanical fatigue (TMF) conditions. This program was conducted at M.I.T. for the period of September 1982 to September 1985. The program was arranged into five technical tasks. Under Task I, the literature of TMF data was reviewed. The goal was to identify the crack propagation conditions in aircraft engines (hot section) and to assess the validity of conventional fracture mechanics parameters to address TMF crack growth. The second task defined the test facilities, test specimen and the testing conditions needed to establish the effectiveness of data correlation parameters identified in Task I. Three materials (Inconel X-750, Hastelloy-X, and B-1900) were chosen for the program. Task II was accomplished in collaboration with Pratt & Whitney Aircraft engineers. Under Task III, a computerized testing system to measure the TMF behavior (LCF and CG behaviors) of various alloys systems was built. The software used to run isothermal and TMF tests was also developed. Built around a conventional servohydraulic machine, the system is capable of push-pull tests under stress or strain and temperature controlled conditions in the temperature range of 25C to 1050C. A crack propagation test program was defined and conducted under Task IV. The test variables included strain range, strain rate (frequency) and temperature. Task V correlated and generalized the Task IV data for isothermal and variable temperature conditions so that several crack propagation parameters could be compared and evaluated. The structural damage (mode of cracking and dislocation substructure) under TMF cycling was identified and contrasted with the isothermal damage to achieve a sound fundamental mechanistic understanding of TMF.
The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.
A review of the theory for the electromagnetic functional used to date to determine the lunar conductivity profile from spectral analyses of lunar magnetometer data. The 'hard' boundary condition used by Sonett et al. (1971) and others appears to be a good approximation for the sunlit lunar hemisphere. The use of the spectral data in conjunction with the functional to find a least squares conductivity profile is examined from the point of view of the nonuniqueness of nonlinear estimation. An unsuccessful search was carried out to find models that were both geophysically reasonable and consistent with the data. It is asserted that the failure to find these models is due to the inadequacy of the functional. Of the models generated, those that best fit the data all have a conductivity peak at a depth of 240 km similar to that of the model discussed by Sonett et al. However, all of these models are quite distinct elsewhere in the profile. It is shown how such models are dependent on both the nature of the functional as well as the initial guess in the least squares procedure. A correlation analysis shows that the only resolvable features from this type of model are a low conductivity crust, a high conductivity peak of limited radial extent, and a low conductivity zone beneath the peak.
Energy flexibility, through short-term demand-side management (DSM) and energy storage technologies, is now seen as a major key to balancing the fluctuating supply in different energy grids with the energy demand of buildings. This is especially important when considering the intermittent nature of ever-growing renewable energy production, as well as the increasing dynamics of electricity demand in buildings. This paper provides a holistic review of (1) data-driven energy flexibility key performance indicators (KPIs) for buildings in the operational phase and (2) open datasets that can be used for testing energy flexibility KPIs. The review identifies a total of 48 data-driven energy flexibility KPIs from 87 recent and relevant publications. These KPIs were categorized and analyzed according to their type, complexity, scope, key stakeholders, data requirement, baseline requirement, resolution, and popularity. Moreover, 330 building datasets were collected and evaluated. Of those, 16 were deemed adequate to feature building performing demand response or building-to-grid (B2G) services. The DSM strategy, building scope, grid type, control strategy, needed data features, and usability of these selected 16 datasets were analyzed. This review reveals future opportunities to address limitations in the existing literature: (1) developing new data-driven methodologies to specifically evaluate different energy flexibility strategies and B2G services of existing buildings; (2) developing baseline-free KPIs that could be calculated from easily accessible building sensors and meter data; (3) devoting non-engineering efforts to promote building energy flexibility, standardizing data-driven energy flexibility quantification and verification processes; and (4) curating and analyzing datasets with proper description for energy flexibility assessm.