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At least 127 records · Page 7

Organic matter transformations are disconnected between surface water and the hyporheic zone

Abstract. Biochemical transformations of organic matter (OM) are a primary driver of river corridor biogeochemistry, thereby modulating ecosystem processes at local to global scales. OM transformations are driven by diverse biotic and abiotic processes, but we lack knowledge of how the diversity of those processes varies across river corridors and across surface and subsurface components of river corridors. To fill this gap we quantified the number of putative biotic and abiotic transformations of organic molecules across diverse river corridors using ultra-high-resolution mass spectrometry. The number of unique transformations is used here as a proxy for the diversity of biochemical processes underlying observed profiles of organic molecules. For this, we use public data spanning the contiguous United States (ConUS) from the Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS) consortium. Our results show that surface water OM had more biotic and abiotic transformations than OM from shallow hyporheic zone sediments (1–3 cm depth). We observed substantially more biotic than abiotic transformations, and the numbers of biotic and abiotic transformations were highly correlated with each other. We found no relationship between the number of transformations in surface water and sediments and no meaningful relationships with latitude, longitude, or climate. We also found that the composition of transformations in sediments was not linked with transformation composition in adjacent surface waters. We infer that OM transformations represented in surface water are an integrated signal of diverse processes occurring throughout the upstream catchment. In contrast, OM transformations in sediments likely reflect a narrower range of processes within the sampled volume. This indicates decoupling between the processes influencing surface water and sediment OM, despite the potential for hydrologic exchange to homogenize OM. We infer that the processes influencing OM transformations and the scales at which they operate diverge between surface water and sediments.

58 GEOSCIENCES↗

High temperature co-axial winding transformers

The analysis and design of co-axial winding transformers is presented. The design equations are derived and the different design approaches are discussed. One of the most important features of co-axial winding transformers is the fact that the leakage inductance is well controlled and can be made low. This is not the case in conventional winding transformers. In addition, the power density of co-axial winding transformers is higher than conventional ones. Hence, using co-axial winding transformers in a certain converter topology improves the power density of the converter. The design methodology used in meeting the proposed specifications of the co-axial winding transformer specifications are presented and discussed. The final transformer design was constructed in the lab. Co-axial winding transformers proved to be a good choice for high power density and high frequency applications. They have a more predictable performance compared with conventional transformers. In addition, the leakage inductance of the transformer can be controlled easily to suit a specific application. For space applications, one major concern is the extraction of heat from power apparatus to prevent excessive heating and hence damaging of these units. Because of the vacuum environment, the only way to extract heat is by using a cold plate. One advantage of co-axial winding transformers is that the surface area available to extract heat from is very large compared to conventional transformers. This stems from the unique structure of the co-axial transformer where the whole core surface area is exposed and can be utilized for cooling effectively. This is a crucial issue here since most of the losses are core losses.

Divan, Deepakraj M.↗

Broadband Characterization and Circuit Model Development of Transmission-Scale Transformers

This report describes broadband measurements of transmission-scale transformers typical in the electric power grid. This work was performed as part of the EMP Resilient Grid LDRD project at Sandia National Laboratories to generate circuit models that can be used for high-altitude electromagnetic pulse (HEMP) coupling simulations and response predictions. The objective of the work was to obtain characterization data of substation yard equipment across a frequency range relevant to HEMP. Vector network analyzer measurements up to 100 MHz were performed on two power transformers at ABB-Hitachi and a single ITEC potential transformer. Custom cable breakouts were designed to interface with the transformer terminals and provide ground connections to the chassis at the base of the transformer bushings. The three-phase terminals of the power transformers were measured as a common mode impedance using a parallel resistive splitter, and the single-phase terminals of the potential transformer were measured directly. A vector fitting algorithm was used to empirically fit circuit models to the resulting two-port networks and input impedances of the measured objects. Simplified circuit representations of the input impedances were also generated to assess the degree of precision needed for high-altitude electromagnetic pulse response predictions, which were performed in Sandia's XYCE circuit simulator platform. HEMP coupling simulations using the transformer models showed significant reduction in the voltage peak and broadening in the pulse width seen at the power transformer compared to the traveling wave voltage. This indicated the importance of the load condition when defining the coupled insult in an electric power substation. Simplified circuit models showed a similar voltage at the transformer with a smoothed waveform. The presence of potential transformers in the simulation did not significantly change the simulated voltage at the power transformer. Single-port input impedance models were also developed to define load conditions when transfer characteristics were not necessary.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Effect of radiance-to-reflectance transformation and atmosphere removal on maximum likelihood classification accuracy of high-dimensional remote sensing data

Many analysis algorithms for high-dimensional remote sensing data require that the remotely sensed radiance spectra be transformed to approximate reflectance to allow comparison with a library of laboratory reflectance spectra. In maximum likelihood classification, however, the remotely sensed spectra are compared to training samples, thus a transformation to reflectance may or may not be helpful. The effect of several radiance-to-reflectance transformations on maximum likelihood classification accuracy is investigated in this paper. We show that the empirical line approach, LOWTRAN7, flat-field correction, single spectrum method, and internal average reflectance are all non-singular affine transformations, and that non-singular affine transformations have no effect on discriminant analysis feature extraction and maximum likelihood classification accuracy. (An affine transformation is a linear transformation with an optional offset.) Since the Atmosphere Removal Program (ATREM) and the log residue method are not affine transformations, experiments with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were conducted to determine the effect of these transformations on maximum likelihood classification accuracy. The average classification accuracy of the data transformed by ATREM and the log residue method was slightly less than the accuracy of the original radiance data. Since the radiance-to-reflectance transformations allow direct comparison of remotely sensed spectra with laboratory reflectance spectra, they can be quite useful in labeling the training samples required by maximum likelihood classification, but these transformations have only a slight effect or no effect at all on discriminant analysis and maximum likelihood classification accuracy.

Hoffbeck, Joseph P.↗

Mn(II)-induced phase transformation of Mn(IV) oxide in seawater

Manganese (Mn) oxides are key components of oceanic and lacustrine Mn nodules and influence metal cycling through oxidation and adsorption processes. Layered Mn oxides (LMOs) are the most common minerals in these nodules and the immediate products of microbially mediated Mn(II) oxidation by O 2 . LMOs can transform into tunneled Mn oxides (TMOs), Mn oxyhydroxides (MnOOH), or Mn(II,III) phase (Mn 3 O 4 ). LMOs often concur with Mn(II) in the environment and the adsorption and oxidation of Mn(II) by LMOs can greatly promote the transformation of LMOs to those phases. However, the Mn(II)-promoted transformation of LMOs in seawater—rich in various cations (300 mM Na + , 10 mM K + , 50 mM Ca 2+ , and 10 mM Mg 2+ ) remains poorly understood. We examined the transformation of δ-MnO 2 in artificial seawater (pH 8.2) under anoxic conditions with the Mn(II)/MnO 2 ratio (r) ranging from 0.08 to 3.83. To assess the effect of ionic strength (IS), parallel experiments were conducted in a mixed 530 mM NaCl and 10 mM KCl solution (having seawater ionic strength but without Ca 2+ and Mg 2+ ) and in 100 mM NaCl solution as a control. At low r (0.08), δ-MnO 2 transformed into triclinic birnessite and a 4 × 4 TMO in 100 mM NaCl solution, which, however, was suppressed in seawater due to strong interactions of Ca 2+ /Mg 2+ with δ-MnO 2 . In the mixed 530 mM NaCl and 10 mM KCl solution (the same ionic strength as of seawater), the transformation occurred extensively but the products had lower crystallinity compared to in 100 mM NaCl solution. At the high Mn(II)/MnO 2 ratios (0.5 ≤ r ≤ 3.83), δ-MnO 2 transformed extensively into MnOOH phases and hausmannite (Mn 3 O 4 ) in 100 mM NaCl solution. The seawater suppressed the transformation, but the suppression became weaker with increasing Mn(II)/MnO 2 ratio. For example, the transformation was completely suppressed at r = 0.5 but essentially negligible at r = 3.83. The suppression at these high Mn(II)/MnO 2 ratios was mainly ascribed to the influence of Ca 2+ and Mg 2+ rather than of the high IS, and the weaker suppression at the higher Mn(II)/MnO 2 ratio suggests stronger competition of Mn(II) with Ca 2+ /Mg 2+ for interacting with δ-MnO 2 . Moreover, the composition and crystallinity of the transformation products (i.e., the relative abundance of MnOOH (α, β, and γ) and Mn 3 O 4 ) were influenced by both the high ionic strength and the presence of Ca 2+ and Mg 2+ . Therefore, even though Ca 2+ and Mg 2+ concentrations are much lower than Na + in seawater, their impacts on the transformation are dominant. Our study explains why MnOOH phases, hausmannite, and TMOs are less common than LMOs in oceanic environments, partially because seawater chemistry suppresses their formation. LMOs are the most reactive for metal adsorption and oxidation among all Mn oxides. Thus, the high stability of LMOs in an oceanic environment confers the high impacts of Mn oxides on metal cycling in the ocean.

Divalent manganese↗

An extension of the Laplace transform to Schwartz distributions

A characterization of the Laplace transform is developed which extends the transform to the Schwartz distributions. The class of distributions includes the impulse functions and other singular functions which occur as solutions to ordinary and partial differential equations. The standard theorems on analyticity, uniqueness, and invertibility of the transform are proved by using the characterization as the definition of the Laplace transform. The definition uses sequences of linear transformations on the space of distributions which extends the Laplace transform to another class of generalized functions, the Mikusinski operators. It is shown that the sequential definition of the transform is equivalent to Schwartz' extension of the ordinary Laplace transform to distributions but, in contrast to Schwartz' definition, does not use the distributional Fourier transform. Several theorems concerning the particular linear transformations used to define the Laplace transforms are proved. All the results proved in one dimension are extended to the n-dimensional case, but proofs are presented only for those situations that require methods different from their one-dimensional analogs.

Price, D. R.↗

A survey of techniques for optimizing transformer inference

Recent years have seen a phenomenal rise in the performance and applications of transformer neural networks. The family of transformer networks, including Bidirectional Encoder Representations from Transformer (BERT), Generative Pretrained Transformer (GPT) and Vision Transformer (ViT), have shown their effectiveness across Natural Language Processing (NLP) and Computer Vision (CV) domains. Transformer-based networks such as ChatGPT have impacted the lives of common men. However, the quest for high predictive performance has led to an exponential increase in transformers' memory and compute footprint. Researchers have proposed techniques to optimize transformer inference at all levels of abstraction. Further, this paper presents a comprehensive survey of techniques for optimizing the inference phase of transformer networks. We survey techniques such as knowledge distillation, pruning, quantization, neural architecture search and lightweight network design at the algorithmic level. We further review hardware-level optimization techniques and the design of novel hardware accelerators for transformers. We summarize the quantitative results on the number of parameters/FLOPs and the accuracy of several models/techniques to showcase the tradeoff exercised by them. We also outline future directions in this rapidly evolving field of research. We believe that this survey will educate both novice and seasoned researchers and also spark a plethora of research efforts in this field.

97 MATHEMATICS AND COMPUTING↗

A Novel Gene Stacking Method in Plant Transformation Utilizing Split Selectable Markers

Gene stacking, the process of introducing multiple genes into a single plant to enhance desired traits, is essential for plant genetic improvement through both conventional breeding and genetic transformation. In general, transformation-based gene stacking can be achieved through either co-transformation to simultaneously introduce multiple genes or sequential multi-round transformation. While co-transformation is generally faster and more efficient than sequential multi-round transformation, it often requires two selectable marker genes, which confer resistance to antibiotics, for selecting transgenic events. However, in most cases, there is only one best selectable marker gene for a specific plant species or genotype. Also, it is harder to optimize the concentrations of two antibiotics for co-transformation than using one antibiotic for selecting transgenic events. To overcome this challenge, we recently developed an innovative split selectable marker system for plant co-transformation, allowing the use of one selectable marker gene to select transgenic events. This method involves constructing two binary vectors, each carrying a subset of genes of interest and a partial fragment of the selectable marker gene, which is connected to a partial intein fragment. Following Agrobacterium -mediated co-transformation, plants harboring both binary vectors are selected using a single antibiotic, such as kanamycin. This split-marker system can be used to co-transform multiple genes into both herbaceous and woody plants, accelerating genetic improvement of polygenic traits or integrative improvement of multiple traits to simultaneously increase crop yield and quality.

59 BASIC BIOLOGICAL SCIENCES↗

Iterative-Transform Phase Retrieval Using Adaptive Diversity

A phase-diverse iterative-transform phase-retrieval algorithm enables high spatial-frequency, high-dynamic-range, image-based wavefront sensing. [The terms phase-diverse, phase retrieval, image-based, and wavefront sensing are defined in the first of the two immediately preceding articles, Broadband Phase Retrieval for Image-Based Wavefront Sensing (GSC-14899-1).] As described below, no prior phase-retrieval algorithm has offered both high dynamic range and the capability to recover high spatial-frequency components. Each of the previously developed image-based phase-retrieval techniques can be classified into one of two categories: iterative transform or parametric. Among the modifications of the original iterative-transform approach has been the introduction of a defocus diversity function (also defined in the cited companion article). Modifications of the original parametric approach have included minimizing alternative objective functions as well as implementing a variety of nonlinear optimization methods. The iterative-transform approach offers the advantage of ability to recover low, middle, and high spatial frequencies, but has disadvantage of having a limited dynamic range to one wavelength or less. In contrast, parametric phase retrieval offers the advantage of high dynamic range, but is poorly suited for recovering higher spatial frequency aberrations. The present phase-diverse iterative transform phase-retrieval algorithm offers both the high-spatial-frequency capability of the iterative-transform approach and the high dynamic range of parametric phase-recovery techniques. In implementation, this is a focus-diverse iterative-transform phaseretrieval algorithm that incorporates an adaptive diversity function, which makes it possible to avoid phase unwrapping while preserving high-spatial-frequency recovery. The algorithm includes an inner and an outer loop (see figure). An initial estimate of phase is used to start the algorithm on the inner loop, wherein multiple intensity images are processed, each using a different defocus value. The processing is done by an iterative-transform method, yielding individual phase estimates corresponding to each image of the defocus-diversity data set. These individual phase estimates are combined in a weighted average to form a new phase estimate, which serves as the initial phase estimate for either the next iteration of the iterative-transform method or, if the maximum number of iterations has been reached, for the next several steps, which constitute the outerloop portion of the algorithm. The details of the next several steps must be omitted here for the sake of brevity. The overall effect of these steps is to adaptively update the diversity defocus values according to recovery of global defocus in the phase estimate. Aberration recovery varies with differing amounts as the amount of diversity defocus is updated in each image; thus, feedback is incorporated into the recovery process. This process is iterated until the global defocus error is driven to zero during the recovery process. The amplitude of aberration may far exceed one wavelength after completion of the inner-loop portion of the algorithm, and the classical iterative transform method does not, by itself, enable recovery of multi-wavelength aberrations. Hence, in the absence of a means of off-loading the multi-wavelength portion of the aberration, the algorithm would produce a wrapped phase map. However, a special aberration-fitting procedure can be applied to the wrapped phase data to transfer at least some portion of the multi-wavelength aberration to the diversity function, wherein the data are treated as known phase values. In this way, a multiwavelength aberration can be recovered incrementally by successively applying the aberration-fitting procedure to intermediate wrapped phase maps. During recovery, as more of the aberration is transferred to the diversity function following successive iterations around the ter loop, the estimated phase ceases to wrap in places where the aberration values become incorporated as part of the diversity function. As a result, as the aberration content is transferred to the diversity function, the phase estimate resembles that of a reference flat.

Dean, Bruce H.↗

Radiogenic transformation of human mammary epithelial cells in vitro

Cancer induction by space radiations is a major concern for manned space exploration. Accurate assessment of radiation risk at low doses requires basic understanding of mechanism(s) of radiation carcinogenesis. For determining the oncogenic effects of ionizing radiation in human epithelial cells, we transformed a mammary epithelial cell line (185B5), which was immortalized by benzo(a)pyrene, with energetic heavy ions and obtained several transformed clones. These transformed cells showed growth properties on Matrigel similar to human mammary tumor cells. To better understand the mechanisms of radiogenic transformation of human cells, we systematically examined the alterations in chromosomes and cancer genes. Among 16 autosomes examined for translocations, by using fluorescence in situ hybridization (FISH) technique, chromosomes 3, 12, 13, 15, 16, and 18 appeared to be normal in transformed cells. Chromosomes 1, 4, 6, 8, and 17 in transformed cells, however, showed patterns different from those in nontransformed cells. Southern blot analyses indicated no detectable alterations in myc, ras, Rb, or p53 genes. Further studies of chromosome 17 by using in situ hybridization with unique sequence p53 gene probe and a centromere probe showed no loss of p53 gene in transformed cells. Experimental results from cell fusion studies indicated that the transforming gene(s) is recessive. The role of genomic instability and tumor suppressor gene(s) in radiogenic transformation of human breast cells remains to be identified.

NASA Center JSC↗

Causal Correlation Functions and Fourier Transforms: Application in Calculating Pressure Induced Shifts

By adopting a concept from signal processing, instead of starting from the correlation functions which are even, one considers the causal correlation functions whose Fourier transforms become complex. Their real and imaginary parts multiplied by 2 are the Fourier transforms of the original correlations and the subsequent Hilbert transforms, respectively. Thus, by taking this step one can complete the two previously needed transforms. However, to obviate performing the Cauchy principal integrations required in the Hilbert transforms is the greatest advantage. Meanwhile, because the causal correlations are well-bounded within the time domain and band limited in the frequency domain, one can replace their Fourier transforms by the discrete Fourier transforms and the latter can be carried out with the FFT algorithm. This replacement is justified by sampling theory because the Fourier transforms can be derived from the discrete Fourier transforms with the Nyquis rate without any distortions. We apply this method in calculating pressure induced shifts of H2O lines and obtain more reliable values. By comparing the calculated shifts with those in HITRAN 2008 and by screening both of them with the pair identity and the smooth variation rules, one can conclude many of shift values in HITRAN are not correct.

correlation function↗

Effect of bacterial cell addition on Fe(III) reduction and soil organic matter transformation in a farmland soil

The coupled biogeochemical processes of Fe(III) reduction and organic matter transformation profoundly impact terrestrial carbon cycling. However, little is known about the microbial role in soil organic matter (SOM) transformation during Fe(III) bio-reduction. Here we investigated the bio-reduction behavior of a black farmland soil and corresponding SOM transformation under circumneutral and anoxic conditions. A model dissimilatory Fe reducing bacterium, Geobacter sulfurreducens, was added in either live or dead form in order to enhance Fe(III) reduction in soil and to evaluate the accompanying transformation of SOM. The progress of Fe reduction was monitored and SOM transformation was characterized by various spectroscopy methods. Results showed that addition of either dead or live G. sulfurreducens cells increased the Fe(III) reduction rate and extent. Without cell addition, SOM transformation was insignificant within 13 days of incubation, only with some consumption of aliphatic/protein compounds, apparently due to their higher bio-degradability. Addition of dead or live cells resulted in more drastic SOM transformation, but through different mechanisms. With dead cell amendment, cell necromass and debris stimulated the activity of indigenous soil microbes by serving as extra carbon/energy sources. During Fe(III) reduction, the aliphatic/protein compounds were preferentially consumed by indigenous microbial communities, similar to the treatment without cell addition but with a greater extent of consumption. In comparison, addition of live G. sulfurreducens cells stimulated degradation of less bioavailable compounds, including more saturated and higher molecular weight SOM. It is possible that fast depletion of labile SOM by live G. sulfurreducens cells favored utilization of less bioavailable molecules (such as those with more aromatic structures) by the originally dormant species in native microbial community, suggesting an active role of live Fe(III)-reducing bacteria in affecting SOM transformation. In addition, fast assimilation of microbial related carbon, such as aromatic proteins and microbial byproducts, into SOM pools was also observed. Overall, our results suggest that addition of Fe(III)-reducing bacteria to a native soil can enhance Fe(III) reduction and accelerate the turnover of SOM through various mechanisms. The study provides new insights into coupled Fe(III) reduction and SOM transformation, as well as the “priming effect” of SOM using microbial cells as substrate.

54 ENVIRONMENTAL SCIENCES↗

The effects of Ti content and quenching on phase transformations, microstructures, and mechanical properties in uranium-titanium alloys

In this work, the effect of Ti content on phase transformations, microstructures, and mechanical properties of U-Ti alloys are described for alloys containing 0.3 wt.% to 2.0 wt.%Ti. Rapid cooling is required to overcome diffusional decomposition of γ-phase and facilitate diffusionless transformation to supersaturated variants of α-phase. Critical cooling rate increases with increasing Ti content, opposite to the trend observed in U-Mo and U-Nb alloys. This difference occurs because the martensite transformation temperatures in these relatively dilute U-Ti alloys are above the knee of the C-curve for diffusional decomposition, unlike those in the more concentrated U-Mo and U-Nb alloys. In these U-Ti alloys critical cooling rate depends on the amount of undercooling required to reach M s , which increases with increasing Ti content, and the time for diffusional decomposition to occur just above M s , which decreases with increasing Ti content. The net result is that higher cooling rates are required as Ti content increases. Full quenching results in diffusionless transformation of γ-phase to supersaturated variants of α-phase. Very dilute alloys transform via a γ → β → α m sequence of massive transformations. Martensitic γ → α' a transformation begins at ~0.4%Ti, and 100% α' a microstructures are obtained from ~0.65% to ~1.4% Ti. A transition to banded α'b martensite occurs at ~1.5%Ti. Evidence suggests that the α' a to α' b transition may occur when the cubic γ-phase first transforms to tetragonal γ°, which in turn transforms to orthorhombic α' b via the sequence γ → γ° → α' b . Fully quenched alloys exhibit moderate strengths and ductilities, and their supersaturation with Ti makes them amenable to subsequent age hardening. Subcritical quenching typically results in two-phase microstructures with lower ductilities and near-zero Ti-supersaturation, eliminating the possibility of subsequent age hardening.

36 MATERIALS SCIENCE↗

Low-cost embedded optical sensing systems for distribution transformer monitoring

There is a mounting need for low-cost monitoring with online sensing technologies to maintain grid reliability and uptime. Here we introduce an innovative low-cost, embedded optical sensing technology initially focused on transformers that was developed and demonstrated at a major electric utility, Con Edison. A version of it that can be retrofitted onto existing transformers in the field was also developed. Two new 500 kVA distribution network transformers were built with embedded fiber-optic (FO) sensors and qualified per industry standards. Vibration, temperature, and corrosion were key parameters monitored. The first transformer with embedded FO sensors was installed at a Con Edison facility and monitored at our team’s office. The second one was installed in an urban street-side underground location with online data processing/feature extraction algorithms and monitored through a wireless router. Additionally, an older transformer was also retrofitted. Data analysis was done on these transformers showing promising correlations with their corresponding loading cycles. Furthermore, key events such as the transformer primary-side energizing, and other events were detected. In general, the technology was demonstrated over 6 months across the 3 transformers instrumented with promising results. Thus, it has the potential to enable predictive maintenance for transformers and other grid assets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Geomagnetically Induced Current Field Test on Large Grid-Connected Power Transformers: Analysis, Model Development, and Simulations

Geomagnetic-induced current (GIC) flow in power grids can cause undesirable effects such as transformer overheating, harmonics, higher reactive power demand, etc. Many simulation models have been developed to study these effects, but real-world verification on modern transformer designs is rare. Here, this paper presents the first long-duration GIC field test in the U.S. performed on high-voltage, grid-connected transformers featuring winding clamps and tie rods instead of conventional tie bars. Field measurements were taken to evaluate GIC effects. These measurements also aided in developing and validating thermal and electromagnetic transient (EMT) models of the transformers. During the test, significant current and voltage distortions were observed along with considerable transformer reactive power losses. Analysis of the field measurements showed that the transformers’ hottest spot was at the inner windings, and their k-factors were close to factory test and software default values. Thermal simulations indicated that the transformers would not violate their thermal limits even for a GIC waveform that peaks at about 200 A/phase. EMT simulations revealed that increased transformer loading may reduce GIC-induced reactive power demand and harmonics in certain scenarios. The study also highlighted potential inaccuracies in using the k-factor method to calculate transformer reactive power losses.

EMTDC↗

Retaining Geochemical Signatures during Aragonite-Calcite Transformation at Hydrothermal Conditions

Transformation of aragonite, a mineral phase metastable at Earth’s surface, to calcite widely occurs in both sedimentary and metamorphic systems with the presence of an aqueous phase. The transformation process can affect geochemical signatures of aragonite (a protolith). This study focused on quantification of the retention of Mg/Ca and Sr/Ca ratios, and δ18O during the transformation process as well as evaluation of the transformation rate. To investigate the effect of transformation from aragonite to calcite on elemental and stable isotope ratios, we conducted a series of experiments in NaCl solutions at temperatures between 120 and 184 °C. Two additional experiments at 250 °C were conducted to estimate the transformation rate of aragonite to calcite. Protolith materials consist of (1) synthetic (Mg; Sr-bearing or non-Mg; Sr bearing) needle-shaped microcrystals of aragonite (<5 µm in size) and (2) larger chips (>100 µm in size) of natural aragonite. X-ray diffraction (XRD) showed that microcrystals successfully transformed to calcite within 30 h and scanning electron microscopy (SEM) yielded a change in the crystal size to >10 µm in rhombohedral shape. Electron backscatter diffraction (EBSD) of the larger aragonite chips showed that transformation to randomly oriented calcite occurred at the rims and along the cracks while the core retained an aragonite crystal structure. Isotope-ratio mass spectrometry (IRMS) analyses showed that calcite δ18O was controlled by temperature and δ18O of the solution. The obtained calibration curve of isotope fractionation factor versus temperature is consistent with other studies. Inductively coupled plasma optical emission spectroscopy (ICP-OES) analyses showed that calcite partially or completely retained Mg/Ca and Sr/Ca ratios through the transformation.

58 GEOSCIENCES↗

On the accuracy of compressibility transformations

This study highlights the importance of satisfying the eddy viscosity equivalence below the logarithmic layer, to deriving accurate compressibility transformations. First, we analyze the ability of known transformations to satisfy the eddy viscosity equivalence and show that the accuracy of these transformations is strongly dependent on this ability. Second, in a step-by-step manner, we devise new transformations that satisfy this hypothesis. An approach based on curve fitting of the incompressible Direct Numerical Simulation data for eddy viscosity profiles below the logarithmic layer provides an extremely accurate transformation, which motivates self-contained methods, making use of mixing length formulas in the inner region. It is shown that the accuracy of existing transformations can be significantly improved by applying these ideas, below the logarithmic layer. Motivated by the effectiveness of the formulations derived from eddy viscosity equivalence, we introduce a new integral transformation based on Reynolds number equivalence between compressible and incompressible flows. This approach is based on defining a new compressible velocity scale, which affects the accuracy of transformations. Several choices for the velocity scale are tested, and in each attempt, it is shown that the eddy viscosity equivalence plays a very important role for the accuracy of compressibility transformations.

42 ENGINEERING↗

Assessment of Current MACCS Capabilities for Modeling Atmospheric Physical and Chemical Transformations

The physical and chemical transformation during atmospheric transport of radionuclides released into the environment has the possibility of impacting consequence modeling results. Accordingly, this report identifies physical and chemical transformations that may occur following release of chemically reactive radioactive species, how those transformations may affect modeling of consequences of release to the atmosphere and identifies current capabilities – in both MACCS and other state-of-practice atmospheric transport and dispersions models– to model those transformations. It was found that the inclusion of physical and chemical transformations is currently very limited in current state-of-practice codes for atmospheric dispersion of radionuclides. State-of-practice atmospheric dispersion codes appear to be typically limited to simulating either physical-chemical transformations or radioactive transformations, but not both. A state-of-practice atmospheric dispersion code capable of performing parallel physical, chemical, and radioactive transformation was not identified. A few atmospheric dispersion codes capable of modeling physical and chemical transport of specific species such as tritium or uranium hexafluoride were identified. Consequently, there is currently no information available that clearly suggests updates to the MACCS code are needed to bring it up to state-of-practice. However, investigations concluded that the MACCS computational framework can currently accommodate multiple physical/chemical forms in one simulation. Additionally, with some major assumptions, the computational framework in MACCS can accommodate parallel physical-chemical and radioactive transformations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗