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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Interpretation of a short-term anomaly in the gravitational microlensing event MOA-2012-BLG-486

A planetary microlensing signal is generally characterized by a short-term perturbation to the standard single lensing light curve. A subset of binary-source events can produce perturbations that mimic planetary signals, thereby introducing an ambiguity between the planetary and binary-source interpretations. In this paper, we present the analysis of the microlensing event MOA-2012-BLG-486, for which the light curve exhibits a short-lived perturbation. Routine modeling not considering data taken in different passbands yields a best-fit planetary model that is slightly preferred over the best-fit binary-source model. However, when allowed for a change in the color during the perturbation, we find that the binary-source model yields a significantly better fit and thus the degeneracy is clearly resolved. This event not only signifies the importance of considering various interpretations of short-term anomalies, but also demonstrates the importance of multi-band data for checking the possibility of false-positive planetary signals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

ON THE DENSITY PROFILE OF THE GLOBULAR CLUSTER M92

We present new number density and surface brightness profiles for the globular cluster M92 (NGC 6341). These profiles are calculated from optical images collected with the CCD mosaic camera MegaCam at the Canada-France-Hawaii Telescope and with the Advanced Camera for Surveys on the Hubble Space Telescope. The ground-based data were supplemented with the Sloan Digital Sky Survey photometric catalog. Special care was taken to discriminate candidate cluster stars from field stars and to subtract the background contamination from both profiles. By examining the contour levels of the number density, we found that the stellar distribution becomes clumpy at radial distances larger than {approx}13', and there is no preferred orientation of contours in space. We performed detailed fits of King and Wilson models to the observed profiles. The best-fit models underestimate the number density inside the core radius. Wilson models better represent the observations, in particular in the outermost cluster regions: the good global agreement of these models with the observations suggests that there is no need to introduce an extra-tidal halo to explain the radial distribution of stars at large radial distances. The best-fit models for the number density and the surface brightness profiles are different, even though they are based on the same observations. Additional tests support the evidence that this fact reflects the difference in the radial distribution of the stellar tracers that determine the observed profiles (main-sequence stars for the number density, bright evolved stars for the surface brightness).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

{sup 18}F-FLT uptake kinetics in head and neck squamous cell carcinoma: A PET imaging study

Purpose: To analyze the kinetics of 3{sup ′}-deoxy-3{sup ′}-[F-18]-fluorothymidine (18F-FLT) uptake by head and neck squamous cell carcinomas and involved nodes imaged using positron emission tomography (PET). Methods: Two- and three-tissue compartment models were fitted to 12 tumor time-activity-curves (TACs) obtained for 6 structures (tumors or involved nodes) imaged in ten dynamic PET studies of 1 h duration, carried out for five patients. The ability of the models to describe the data was assessed using a runs test, the Akaike information criterion (AIC) and leave-one-out cross-validation. To generate parametric maps the models were also fitted to TACs of individual voxels. Correlations between maps of different parameters were characterized using Pearson'sr coefficient; in particular the phosphorylation rate-constants k{sub 3-2tiss} and k{sub 5} of the two- and three-tissue models were studied alongside the flux parameters K{sub FLT-2tiss} and K{sub FLT} of these models, and standardized uptake values (SUV). A methodology based on expectation-maximization clustering and the Bayesian information criterion (“EM-BIC clustering”) was used to distil the information from noisy parametric images. Results: Fits of two-tissue models 2C3K and 2C4K and three-tissue models 3C5K and 3C6K comprising three, four, five, and six rate-constants, respectively, pass the runs test for 4, 8, 10, and 11 of 12 tumor TACs. The three-tissue models have lower AIC and cross-validation scores for nine of the 12 tumors. Overall the 3C6K model has the lowest AIC and cross-validation scores and its fitted parameter values are of the same orders of magnitude as literature estimates. Maps ofK{sub FLT} and K{sub FLT-2tiss} are strongly correlated (r = 0.85) and also correlate closely with SUV maps (r = 0.72 for K{sub FLT-2tiss}, 0.64 for K{sub FLT}). Phosphorylation rate-constant maps are moderately correlated with flux maps (r = 0.48 for k{sub 3-2tiss} vs K{sub FLT-2tiss} and r = 0.68 for k{sub 5} vs K{sub FLT}); however, neither phosphorylation rate-constant correlates significantly with SUV. EM-BIC clustering reduces the parametric maps to a small number of levels—on average 5.8, 3.5, 3.4, and 1.4 for K{sub FLT-2tiss}, K{sub FLT}, k{sub 3-2tiss}, and k{sub 5.} This large simplification is potentially useful for radiotherapy dose-painting, but demonstrates the high noise in some maps. Statistical simulations show that voxel level noise degrades TACs generated from the 3C6K model sufficiently that the average AIC score, parameter bias, and total uncertainty of 2C4K model fits are similar to those of 3C6K fits, whereas at the whole tumor level the scores are lower for 3C6K fits. Conclusions: For the patients studied here, whole tumor FLT uptake time-courses are represented better overall by a three-tissue than by a two-tissue model. EM-BIC clustering simplifies noisy parametric maps, providing the best description of the underlying information they contain and is potentially useful for radiotherapy dose-painting. However, the clustering highlights the large degree of noise present in maps of the phosphorylation rate-constantsk{sub 5} and k{sub 3-2tiss}, which are conceptually tightly linked to cellular proliferation. Methods must be found to make these maps more robust—either by constraining other model parameters or modifying dynamic imaging protocols.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SELECTION OF BURST-LIKE TRANSIENTS AND STOCHASTIC VARIABLES USING MULTI-BAND IMAGE DIFFERENCING IN THE PAN-STARRS1 MEDIUM-DEEP SURVEY

We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands g {sub P1}, r {sub P1}, i {sub P1}, and z {sub P1}. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

ACCELERATED FITTING OF STELLAR SPECTRA

Stellar spectra are often modeled and fitted by interpolating within a rectilinear grid of synthetic spectra to derive the stars’ labels: stellar parameters and elemental abundances. However, the number of synthetic spectra needed for a rectilinear grid grows exponentially with the label space dimensions, precluding the simultaneous and self-consistent fitting of more than a few elemental abundances. Shortcuts such as fitting subsets of labels separately can introduce unknown systematics and do not produce correct error covariances in the derived labels. In this paper we present a new approach—Convex Hull Adaptive Tessellation (chat)—which includes several new ideas for inexpensively generating a sufficient stellar synthetic library, using linear algebra and the concept of an adaptive, data-driven grid. A convex hull approximates the region where the data lie in the label space. A variety of tests with mock data sets demonstrate that chat can reduce the number of required synthetic model calculations by three orders of magnitude in an eight-dimensional label space. The reduction will be even larger for higher dimensional label spaces. In chat the computational effort increases only linearly with the number of labels that are fit simultaneously. Around each of these grid points in the label space an approximate synthetic spectrum can be generated through linear expansion using a set of “gradient spectra” that represent flux derivatives at every wavelength point with respect to all labels. These techniques provide new opportunities to fit the full stellar spectra from large surveys with 15–30 labels simultaneously.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Fitting a deep generative hadronization model

Hadronization is a critical step in the simulation of high-energy particle and nuclear physics experiments. As there is no first principles understanding of this process, physically-inspired hadronization models have a large number of parameters that are fit to data. Deep generative models are a natural replacement for classical techniques, since they are more flexible and may be able to improve the overall precision. Proof of principle studies have shown how to use neural networks to emulate specific hadronization when trained using the inputs and outputs of classical methods. However, these approaches will not work with data, where we do not have a matching between observed hadrons and partons. In this paper, we develop a protocol for fitting a deep generative hadronization model in a realistic setting, where we only have access to a set of hadrons in data. Our approach uses a variation of a Generative Adversarial Network with a permutation invariant discriminator. We find that this setup is able to match the hadronization model in Herwig with multiple sets of parameters. This work represents a significant step forward in a longer term program to develop, train, and integrate machine learning-based hadronization models into parton shower Monte Carlo programs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Reduced quantum dynamics with arbitrary bath spectral densities: Hierarchical equations of motion based on several different bath decomposition schemes

We investigated applications of the hierarchical equation of motion (HEOM) method to perform high order perturbation calculations of reduced quantum dynamics for a harmonic bath with arbitrary spectral densities. Three different schemes are used to decompose the bath spectral density into analytical forms that are suitable to the HEOM treatment: (1) The multiple Lorentzian mode model that can be obtained by numerically fitting the model spectral density. (2) The combined Debye and oscillatory Debye modes model that can be constructed by fitting the corresponding classical bath correlation function. (3) A new method that uses undamped harmonic oscillator modes explicitly in the HEOM formalism. Methods to extract system-bath correlations were investigated for the above bath decomposition schemes. We also show that HEOM in the undamped harmonic oscillator modes can give detailed information on the partial Wigner transform of the total density operator. Theoretical analysis and numerical simulations of the spin-Boson dynamics and the absorption line shape of molecular dimers show that the HEOM formalism for high order perturbations can serve as an important tool in studying the quantum dissipative dynamics in the intermediate coupling regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

LICK INDICES AND SPECTRAL ENERGY DISTRIBUTION ANALYSIS BASED ON AN M31 STAR CLUSTER SAMPLE: COMPARISONS OF METHODS AND MODELS

Application of fitting techniques to obtain physical parameters—such as ages, metallicities, and α-element to iron ratios—of stellar populations is an important approach to understanding the nature of both galaxies and globular clusters (GCs). In fact, fitting methods based on different underlying models may yield different results and with varying precision. In this paper, we have selected 22 confirmed M31 GCs for which we do not have access to previously known spectroscopic metallicities. Most are located at approximately one degree (in projection) from the galactic center. We performed spectroscopic observations with the 6.5 m MMT telescope, equipped with its Red Channel Spectrograph. Lick/IDS absorption-line indices, radial velocities, ages, and metallicities were derived based on the EZ-Ages stellar population parameter calculator. We also applied full spectral fitting with the ULySS code to constrain the parameters of our sample star clusters. In addition, we performed χ{sub min}{sup 2} fitting of the clusters’ Lick/IDS indices with different models, including the Bruzual and Charlot models (adopting Chabrier or Salpeter stellar initial mass functions and 1994 or 2000 Padova stellar evolutionary tracks), the galev, and the Thomas et al. models. For comparison, we collected their UVBRIJK photometry from the Revised Bologna Catalogue (v.5) to obtain and fit the GCs’ spectral energy distributions (SEDs). Finally, we performed fits using a combination of Lick/IDS indices and SEDs. The latter results are more reliable and the associated error bars become significantly smaller than those resulting from either our Lick/IDS indices-only or our SED-only fits.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Deeper snow increases the net soil organic carbon accrual rate in moist acidic tussock tundra: 210Pb evidence from Arctic Alaska

The net change in the carbon inventory of arctic tundra remains uncertain as global warming leads to shifts in arctic water and carbon cycles. To better understand the response of arctic tundra carbon to changes in winter precipitation amount, we investigated soil depth profiles of carbon concentration and radionuclide activities ( 7 Be, 137 Cs, 210 Pb, and 241 Am) in the active layer of a twenty-two-year winter snow depth manipulation experiment in moist acidic tussock tundra at Toolik Lake, Alaska. Depth correlations of cumulative carbon dry mass (g cm -2 ) vs. unsupported 210 Pb activity (mBq g -1 ) were examined using a modified constant rate of supply (CRS) model. Results were best fit by two-slope CRS models indicating an apparent step temporal increase in the accumulation rate of soil organic carbon. Most of the best-fit model chronologies indicated that the increase in carbon accumulation rate apparently began and persisted after snow fence construction in 1994. The inhomogeneous nature of permafrost soils and their relatively low net carbon accumulation rates make it challenging to establish robust chronologic records. Nonetheless, the data obtained in this study support a decadal-scale increase in net soil organic carbon accumulation rate in the active layer of arctic moist acidic tussock tundra under conditions of increased winter precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Pore growth in U-Mo/Al dispersion fuel

U-Mo/Al dispersion fuel is currently under development in the DOE’s Material Management and Minimization program to convert HEU-fueled research reactors to LEU-fueled reactors. In some demanding conditions in high-power and high-performance reactors, large pores form in the interaction layers between the U-Mo fuel particles and the Al matrix, which pose a potential to cause fuel failure. In this study, comprehension of the formation and growth of these pores was explored. As a product, a model to predict pore growth and porosity increase was developed. Well-characterized in-pile data from reduced-size plates were used to fit the model parameters. A data set of full-sized plates, independent and distinctively different from those used to fit the model parameters, was used to examine the accuracy of the model.

in-pile data↗
DOE OSTI2020

f-Orbital Mixing in the Octahedral f 2 Compounds UX 6 2– [X = F, Br, Cl, I] and PrCl 6 3–

Understanding how interactions between the f orbitals and ligand orbitals in lanthanide and actinide systems affect their physical properties is the central issue in f-element chemistry. A wide variety of approaches including both theoretical and experimental tools have been used to study these relationships. Among the most widely used tools has been crystal field theory (CFT), which bridges theory and experiment in that it is a model based largely on atomic theory that is parametrized using experimental data. Crystal field theory is quite accurate for the lanthanides, due in part to the highly contracted nature of the 4f orbitals. For actinides, crystal field theory is less accurate, potentially due to the treatment of orbital mixing. In CFT, orbital mixing is handled implicitly by allowing the electron repulsion parameters (Slater F k parameters) and the spin–orbit coupling constant to vary. As a result, orbital mixing in CFT is isotropic in that the F k parameters and the spin–orbit coupling constant affect all f orbitals equally. This approximation works well for the lanthanides due to the limited degree of orbital mixing in these complexes. In actinide complexes, the 5f orbitals have greater overlap with the ligand orbitals, and this approximation is less accurate than in the lanthanides. In this work, we report a modification of CFT that includes the effect of orbital mixing on electron repulsion and spin–orbit coupling for each f orbital. The model is applied to the tetravalent uranium hexahalide dianions and PrCl 6 3– for which the energies of many low-lying excited states are known. The new model generally fits the data as well the traditional CFT although with fewer parameters. However, the new model does not fit the data better than the more complex CFT models of Faucher and co-workers. The results of the model show in detail how changes in overlap and orbital energies influence the energies of the bonding and antibonding orbitals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Measurement of the Se 80 ( γ , n ) reaction with linearly polarized γ rays

This paper reports the results of the first measurements of the differential cross section of the 80 Se(γ , n) 79 Se reaction with a linearly polarized gamma-ray (γ-ray) beam. The cross section was measured at three incident γ-ray beam energies: 15.6, 15.8, and 16.0 MeV, with a beam energy spread of 3.0% full width at half-maximum (FWHM). The differential cross section for the excitation spectrum in 79Se was measured at two scattering angles in the plane of the beam polarization: θ = 90° and 135°, and at one angle in the plane perpendicular to the plane of polarization: θ = 90°. The total photoneutron cross sections determined from these data are between 0.8 and 1.3 standard deviations smaller than previously published results. Here, the excitation spectra measured in this work were fit with a Hauser-Feshbach model. Better fits to the data were obtained with a constant-temperature formulation of the nuclear level density (NLD) than with a Fermi-gas NLD model. The parameters for the constant-temperature NLD model obtained in this work are consistent with those obtained for medium-mass nuclei in previous studies.

59 ≤ A ≤ 89↗
DOE OSTI2026

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics↗
DOE OSTI2012

z'-BAND GROUND-BASED DETECTION OF THE SECONDARY ECLIPSE OF WASP-19b

We present the ground-based detection of the secondary eclipse of the transiting exoplanet WASP-19b. The observations were made in the Sloan z' band using the ULTRACAM triple-beam CCD camera mounted on the New Technology Telescope. The measurement shows a 0.088% {+-} 0.019% eclipse depth, matching previous predictions based on H- and K-band measurements. We discuss in detail our approach to the removal of errors arising due to systematics in the data set, in addition to fitting a model transit to our data. This fit returns an eclipse center, T{sub 0}, of 2455578.7676 HJD, consistent with a circular orbit. Our measurement of the secondary eclipse depth is also compared to model atmospheres of WASP-19b and is found to be consistent with previous measurements at longer wavelengths for the model atmospheres we investigated.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Understanding the extreme luminosity of DES14X2fna

We present DES14X2fna, a high-luminosity, fast-declining Type IIb supernova (SN IIb) at redshift z = 0.0453, detected by the Dark Energy Survey (DES). DES14X2fna is an unusual member of its class, with a light curve showing a broad, luminous peak reaching M r ≃ –19.3 mag 20 d after explosion. This object does not show a linear decline tail in the light curve until ≃60 d after explosion, after which it declines very rapidly (4.30 ± 0.10 mag 100 d –1 in the r band). By fitting semi-analytic models to the photometry of DES14X2fna, we find that its light curve cannot be explained by a standard 56 Ni decay model as this is unable to fit the peak and fast tail decline observed. Inclusion of either interaction with surrounding circumstellar material or a rapidly-rotating neutron star (magnetar) significantly increases the quality of the model fit. Furthermore, we also investigate the possibility for an object similar to DES14X2fna to act as a contaminant in photometric samples of SNe Ia for cosmology, finding that a similar simulated object is misclassified by a recurrent neural network (RNN)-based photometric classifier as an SN Ia in ~1.1–2.4 per cent of cases in DES, depending on the probability threshold used for a positive classification.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks

Here we analyze a plurality of epidemiological models through the lens of physics-informed neural networks (PINNs) that enable us to identify time-dependent parameters and data-driven fractional differential operators. In particular, we consider several variations of the classical susceptible-infectious-removed (SIR) model by introducing more compartments and fractional-order and time-delay models. We report the results for the spread of COVID-19 in New York City, Rhode Island and Michigan states and Italy, by simultaneously inferring the unknown parameters and the unobserved dynamics. For integer-order and time-delay models, we fit the available data by identifying time-dependent parameters, which are represented by neural networks. In contrast, for fractional differential models, we fit the data by determining different time-dependent derivative orders for each compartment, which we represent by neural networks. We investigate the structural and practical identifiability of these unknown functions for different datasets, and quantify the uncertainty associated with neural networks and with control measures in forecasting the pandemic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Determining neutron star properties by fitting oblate-star waveform models to X-ray burst oscillations

We describe sophisticated new Bayesian analysis methods that make it possible to estimate quickly the masses and radii of rapidly rotating, oblate neutron stars by fitting oblate-star waveform models to energy-resolved observations of the waveforms of X-ray burst oscillations produced by such stars. We find that a 25% variation of the temperature of the hot spot in the north-south direction does not significantly bias estimates of the mass M and equatorial radius R{sub eq} derived by fitting a model that assumes a uniform-temperature spot. Our results show that fits of oblate-star waveform models to waveform data can simultaneously determine M and R{sub eq} with 1σ uncertainties ≲7% if (1) the star's rotation rate is ≳ 600 Hz; (2) the spot center and observer's sightline are both within 30{sup ∘} of the star's rotational equator; and (3) ∼10{sup 7} counts are collected during burst oscillations that have a fractional rms amplitude ≳10%. A fractional amplitude of ∼10% is realistic, and the accepted NICER and proposed LOFT and AXTAR space missions could collect 10{sup 7} counts from a single star by combining data from many X-ray bursts from the star. Uncertainties ≲7% are small enough to improve substantially our understanding of cold, ultradense matter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Long-term sinking of nuclear waste canisters in salt formations by low-stress creep at high temperature

Abstract Rock salt has a self-sealing capacity, low permeability, and high thermal conductivity, making it a potential host for heat-generating nuclear waste. The feasibility of nuclear waste disposal within salt formations has been investigated mostly for small-sized canisters. Geologic disposal of larger-sized canisters originally designed for spent fuel storage and transportation has lately been examined as a cost-effective alternative. This raises questions about their long-term vertical movement due to their weight and high decay heat. Low-stress creep governs this movement; however, most salt constitutive models do not incorporate it. In this paper, the Norton and the WIPP creep models are compared with the Lux/Wolters/Lerche (LWL) model and a simpler model that combines linear and Norton creep laws (named combined creep model). The LWL and combined creep models consider pressure solution creep, though all incorporate dislocation creep. The models are first applied to creep tests under various stress levels. The LWL and the combined creep models results fit the experimental data well in both high and low stress ranges, whereas the Norton and WIPP models results only fit in higher-stress ranges. The different models are further applied for analyzing long-term canister movement. A sinking rate of $$-4.4\times 10^{-7}$$ - 4.4 × 10 - 7 mm/year was predicted using the Norton and WIPP models versus $$-2.1\times 10^{-2}$$ - 2.1 × 10 - 2 mm/year and $$-3.1\times 10^{-2}$$ - 3.1 × 10 - 2 mm/year using the LWL and the combined creep models, respectively. This comparative study confirms that creep models calibrated exclusively against high-deviatoric stress data might result in an inaccurate estimation of waste packages sinking rate in salt formations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗