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DOE OSTI2011

Current Trends in Gamma Radiation Detection for Radiological Emergency Response

Passive and active detection of gamma rays from shielded radioactive materials, including special nuclear materials, is an important task for any radiological emergency response organization. This article reports on the current trends and status of gamma radiation detection objectives and measurement techniques as applied to nonproliferation and radiological emergencies. In recent years, since the establishment of the Domestic Nuclear Detection Office by the Department of Homeland Security, a tremendous amount of progress has been made in detection materials (scintillators, semiconductors), imaging techniques (Compton imaging, use of active masking and hybrid imaging), data acquisition systems with digital signal processing, field programmable gate arrays and embedded isotopic analysis software (viz. gamma detector response and analysis software [GADRAS]1), fast template matching, and data fusion (merging radiological data with geo-referenced maps, digital imagery to provide better situational awareness). In this stride to progress, a significant amount of interdisciplinary research and development has taken place–techniques and spin-offs from medical science (such as x-ray radiography and tomography), materials engineering (systematic planned studies on scintillators to optimize several qualities of a good scintillator, nanoparticle applications, quantum dots, and photonic crystals, just to name a few). No trend analysis of radiation detection systems would be complete without mentioning the unprecedented strategic position taken by the National Nuclear Security Administration (NNSA) to deter, detect, and interdict illicit trafficking in nuclear and other radioactive materials across international borders and through the global maritime transportation–the so-called second line of defense.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Prospective estimation of organ dose in CT under tube current modulation

Purpose: Computed tomography (CT) has been widely used worldwide as a tool for medical diagnosis and imaging. However, despite its significant clinical benefits, CT radiation dose at the population level has become a subject of public attention and concern. In this light, optimizing radiation dose has become a core responsibility for the CT community. As a fundamental step to manage and optimize dose, it may be beneficial to have accurate and prospective knowledge about the radiation dose for an individual patient. In this study, the authors developed a framework to prospectively estimate organ dose for chest and abdominopelvic CT exams under tube current modulation (TCM). Methods: The organ dose is mainly dependent on two key factors: patient anatomy and irradiation field. A prediction process was developed to accurately model both factors. To model the anatomical diversity and complexity in the patient population, the authors used a previously developed library of computational phantoms with broad distributions of sizes, ages, and genders. A selected clinical patient, represented by a computational phantom in the study, was optimally matched with another computational phantom in the library to obtain a representation of the patient’s anatomy. To model the irradiation field, a previously validated Monte Carlo program was used to model CT scanner systems. The tube current profiles were modeled using a ray-tracing program as previously reported that theoretically emulated the variability of modulation profiles from major CT machine manufacturers Li et al., [Phys. Med. Biol. 59, 4525–4548 (2014)]. The prediction of organ dose was achieved using the following process: (1) CTDI{sub vol}-normalized-organ dose coefficients (h{sub organ}) for fixed tube current were first estimated as the prediction basis for the computational phantoms; (2) each computation phantom, regarded as a clinical patient, was optimally matched with one computational phantom in the library; (3) to account for the effect of the TCM scheme, a weighted organ-specific CTDI{sub vol} [denoted as (CTDI{sub vol}){sub organ,weighted}] was computed for each organ based on the TCM profile and the anatomy of the “matched” phantom; (4) the organ dose was predicted by multiplying the weighted organ-specific CTDI{sub vol} with the organ dose coefficients (h{sub organ}). To quantify the prediction accuracy, each predicted organ dose was compared with the corresponding organ dose simulated from the Monte Carlo program with the TCM profile explicitly modeled. Results: The predicted organ dose showed good agreements with the simulated organ dose across all organs and modulation profiles. The average percentage error in organ dose estimation was generally within 20% across all organs and modulation profiles, except for organs located in the pelvic and shoulder regions. For an average CTDI{sub vol} of a CT exam of 10 mGy, the average error at full modulation strength (α = 1) across all organs was 0.91 mGy for chest exams, and 0.82 mGy for abdominopelvic exams. Conclusions: This study developed a quantitative model to predict organ dose for clinical chest and abdominopelvic scans. Such information may aid in the design of optimized CT protocols in relation to a targeted level of image quality.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Superfluid effective field theory for dark matter direct detection

We develop an effective field theory (EFT) framework for superfluid 4 He to model the interactions among quasiparticles, helium atoms and probe particles. Our effective field theory approach brings together symmetry arguments and power-counting and matches to classical fluid dynamics. We then present the decay and scattering rates for the relevant processes involving quasiparticles and helium atoms. The presented EFT framework and results can be used to understand the dynamics of thermalization in the superfluid, and can be further applied to sub-GeV dark matter direct detection with superfluid 4 He.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

HOW DID A MAJOR CONFINED FLARE OCCUR IN SUPER SOLAR ACTIVE REGION 12192?

We study the physical mechanism of a major X-class solar flare that occurred in the super NOAA active region (AR) 12192 using data-driven numerical magnetohydrodynamic (MHD) modeling complemented with observations. With the evolving magnetic fields observed at the solar surface as bottom boundary input, we drive an MHD system to evolve self-consistently in correspondence with the realistic coronal evolution. During a two-day time interval, the modeled coronal field has been slowly stressed by the photospheric field evolution, which gradually created a large-scale coronal current sheet, i.e., a narrow layer with intense current, in the core of the AR. The current layer was successively enhanced until it became so thin that a tether-cutting reconnection between the sheared magnetic arcades was set in, which led to a flare. The modeled reconnecting field lines and their footpoints match well the observed hot flaring loops and the flare ribbons, respectively, suggesting that the model has successfully “reproduced” the macroscopic magnetic process of the flare. In particular, with simulation, we explained why this event is a confined eruption—the consequence of the reconnection is a shared arcade instead of a newly formed flux rope. We also found a much weaker magnetic implosion effect compared to many other X-class flares.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Gemini frontier fields: wide-field adaptive optics K{sub s}-band imaging of the galaxy clusters MACS J0416.1-2403 and ABELL 2744

We have observed two of the six Frontier Fields galaxy clusters, MACS J0416.1-2403 and Abell 2744, using the Gemini Multi-Conjugate Adaptive Optics System (GeMS) and the Gemini South Adaptive Optics Imager (GSAOI). With 0.″ 08–0.″ 10 FWHM our data are nearly diffraction-limited over a 100{sup ′′}×100{sup ′′} wide area. GeMS/GSAOI complements the Hubble Space Telescope (HST) redwards of 1.6 μm with twice the angular resolution. We reach a 5σ depth of K{sub s}∼25.6 mag (AB) for compact sources. In this paper, we describe the observations, data processing, and initial public data release. We provide fully calibrated, co-added images matching the native GSAOI pixel scale as well as the larger plate scales of the HST release, adding to the legacy value of the Frontier Fields. Our work demonstrates that even for fields at high galactic latitude where natural guide stars are rare, current multi-conjugated adaptive optics technology at 8 m telescopes has opened a new window on the distant universe. Observations of a third Frontier Field, Abell 370, are planned.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2011

Quasi-phase-matching and second-harmonic generation enhancement in a semiconductor microresonator array using slow-light effects

We theoretically analyze the second-harmonic generation process in a sequence of unidirectionnaly coupled doubly resonant whispering gallery mode semiconductor resonators. By using a convenient design, it is possible to coherently sum the second-harmonic fields generated inside each resonator. We show that resonator coupling allows the bandwidth of the phase-matching curve to be increased with respect to single-resonator configurations simultaneously taking advantage of the resonant feature of the resonators. This quasi-phase-matching technique could be applied to obtain small-footprint nonlinear devices with large bandwidth and limited nonlinear losses. The results are discussed in the framework of the slow-light-effect enhancement of second-order optical nonlinearities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Random quasi-phase-matching for pulse characterization from the near to the long wavelength infrared

Experiments requiring ultrafast laser pulses require a full characterization of the electric field to glean meaning from the experimental data. Such characterization typically requires a separate parametric optical process. As the central wavelength range of new sources continues to increase so too does the need for nonlinear crystals suited for characterizing these wavelengths. Here we report on the use of poly-crystalline zinc selenide as a universal nonlinear crystal in the frequency resolved optical gating characterization technique from the near to long-wavelength infrared. Due to its property of random quasi-phase-matching it’s capable of phase matching second-harmonic and sum-frequency generation of ultra-broadband pulses in the near and long wavelength infrared, while being crystal orientation independent. With the majority of ultra-fast laser sources being in this span of wavelengths, this work demonstrates a greatly simplified approach towards ultra-fast pulse characterization spanning from the near to the long-wavelength infrared. To our knowledge there is no single optical technique capable of such flexible capabilities.

Davis, Brandin (ORCID:0000000166964548)↗

DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗

NASA NTRS2002

Evaluation of Cirrus Cloud Simulations using ARM Data-Development of Case Study Data Set

Cloud-resolving models (CRMs) are being increasingly used to develop parametric treatments of clouds and related processes for use in global climate models (GCMs). CRMs represent the integrated knowledge of the physical processes acting to determine cloud system lifecycle and are well matched to typical observational data in terms of physical parameters/measurables and scale-resolved physical processes. Thus, they are suitable for direct comparison to field observations for model validation and improvement. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. The objective is to compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. Progress is assessing cloud and other environmental conditions will be described. Results of preliminary simulations using a regional cloud system model (MM5) and a CRM will be discussed. Focal science questions for the model comparison are strongly based on results of the idealized GCSS WG2 cirrus cloud model comparison projects (Idealized Cirrus Cloud Model Comparison Project and Cirrus Parcel Model Comparison Project), which will also be briefly summarized.

Starr, David OC.↗

NASA NTRS2005

Spectral Ratio Imaging with Hyperion Satellite Data for Geological Mapping

Since the advent of LANDSAT I in 1972, many different multispectral satellites have been orbited by the U.S. and other countries. These satellites have varied from 4 spectral bands in LANDSAT I to 14 spectral bands in the ASTER sensor aboard the TERRA space platform. Hyperion is a relatively new hyperspectral sensor with over 220 spectral bands. The huge increase in the number of spectral bands offers a substantial challenge to computers and analysts alike when it comes to the task of mapping features on the basis of chemical composition, especially if little or no ground truth is available beforehand from the area being mapped. One approach is the theoretical approach of the modeler, where all extraneous information (atmospheric attenuation, sensor electronic gain and offset, etc.) is subtracted off and divided out, and laboratory (or field) spectra of materials are used as training sets to map features in the scene of similar composition. This approach is very difficult to keep accurate because of variations in the atmosphere, solar illumination, and sensor electronic gain and offset that are not always perfectly recorded or accounted for. For instance, to apply laboratory or field spectra of materials as data sets from the theoretical approach, the header information of the files must reflect the correct, up-to-date sensor electronic gain and offset and the analyst must pick the exact atmospheric model that is appropriate for the day of data collection in order for classification procedures to accurately match pixels in the scene with the laboratory or field spectrum of a desired target on the basis of the hyperspectral data. The modeling process is so complex that it is difficult to tell when it is operating well or determine how to fix it when it is incorrect. Recently RSI has announced that the latest version of their ENVI software package is not performing atmospheric corrections correctly with the FLAASH atmospheric model. It took a long time to determine that it was wrong, and may take an equally long time (or longer) to fix.

Vincent, Robert K.↗

DOE OSTI2016

Resonantly enhanced second-harmonic generation using III–V semiconductor all-dielectric metasurfaces

Nonlinear optical phenomena in nanostructured materials have been challenging our perceptions of nonlinear optical processes that have been explored since the invention of lasers. For example, the ability to control optical field confinement, enhancement, and scattering almost independently allows nonlinear frequency conversion efficiencies to be enhanced by many orders of magnitude compared to bulk materials. Also, the subwavelength length scale renders phase matching issues irrelevant. Compared with plasmonic nanostructures, dielectric resonator metamaterials show great promise for enhanced nonlinear optical processes due to their larger mode volumes. Here, we present, for the first time, resonantly enhanced second-harmonic generation (SHG) using gallium arsenide (GaAs) based dielectric metasurfaces. Using arrays of cylindrical resonators we observe SHG enhancement factors as large as 10 4 relative to unpatterned GaAs. At the magnetic dipole resonance, we measure an absolute nonlinear conversion efficiency of ~2 × 10 –5 with ~3.4 GW/cm 2 pump intensity. In conclusion, the polarization properties of the SHG reveal that both bulk and surface nonlinearities play important roles in the observed nonlinear process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)

In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.

03 NATURAL GAS↗

DOE OSTI2015

Soft collinear effective theory for heavy WIMP annihilation

In a large class of models for Weakly Interacting Massive Particles (WIMPs), the WIMP mass M lies far above the weak scale m W . This work identifies universal Sudakov-type logarithms ~ α log 2 (2 M/m W ) that spoil the naive convergence of perturbation theory for annihilation processes. An effective field theory (EFT) framework is presented, allowing the systematic resummation of these logarithms. Another impact of the large separation of scales is that a long-distance wavefunction distortion from electroweak boson exchange leads to observable modifications of the cross section. Careful accounting of momentum regions in the EFT allows the rigorous disentanglement of this so-called Sommerfeld enhancement from the short-distance hard annihilation process. In addition, the WIMP is described as a heavy-particle field, while the electroweak gauge bosons are treated as soft and collinear fields. Hard matching coefficients are computed at renormalization scale μ ~ 2 M , then evolved down to μ ~ m W , where electroweak symmetry breaking is incorporated and the matching onto the relevant quantum mechanical Hamiltonian is performed. The example of an SU(2) W triplet scalar dark matter candidate annihilating to line photons is used for concreteness, allowing the numerical exploration of the impact of next-to-leading order corrections and log resummation. As a result, for M ≃ 3 TeV, the resummed Sommerfeld enhanced cross section is reduced by a factor of ~ 3 with respect to the treelevel fixed order result.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2011

Control of high-order harmonics for attoscience using a static-electric-field pattern

Quantum control in high-order-harmonic generation is considered theoretically by using a spatial distribution of static electric fields along the propagation direction of the driving field. It is shown that the trajectories of the electrons during its acceleration by the laser field in the high-harmonics-generation process can be controlled by periodically distributed static electric fields, which conveniently shape the driving laser field during propagation. Applying this mechanism, a quasi-phase-matching scheme that leads to filtered enhanced high harmonics is achieved. The harmonics in the plateau region are enhanced due to periodical phase variations in the long quantum trajectories as a consequence of the faster change experienced by the intensity-dependent phase along the longer electron trajectories. This effect should be observed in all quasi-phase-matching schemes based on perturbation of the microscopic quantum phase. The richness of adding a static-electric-field spatial pattern in the interaction region suggests a general scheme for feedback loop control in high-order-harmonic generation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2014

Frequency-Modulated, Continuous-Wave Laser Ranging Using Photon-Counting Detectors

Optical ranging is a problem of estimating the round-trip flight time of a phase- or amplitude-modulated optical beam that reflects off of a target. Frequency- modulated, continuous-wave (FMCW) ranging systems obtain this estimate by performing an interferometric measurement between a local frequency- modulated laser beam and a delayed copy returning from the target. The range estimate is formed by mixing the target-return field with the local reference field on a beamsplitter and detecting the resultant beat modulation. In conventional FMCW ranging, the source modulation is linear in instantaneous frequency, the reference-arm field has many more photons than the target-return field, and the time-of-flight estimate is generated by balanced difference- detection of the beamsplitter output, followed by a frequency-domain peak search. This work focused on determining the maximum-likelihood (ML) estimation algorithm when continuous-time photoncounting detectors are used. It is founded on a rigorous statistical characterization of the (random) photoelectron emission times as a function of the incident optical field, including the deleterious effects caused by dark current and dead time. These statistics enable derivation of the Cramér-Rao lower bound (CRB) on the accuracy of FMCW ranging, and derivation of the ML estimator, whose performance approaches this bound at high photon flux. The estimation algorithm was developed, and its optimality properties were shown in simulation. Experimental data show that it performs better than the conventional estimation algorithms used. The demonstrated improvement is a factor of 1.414 over frequency-domainbased estimation. If the target interrogating photons and the local reference field photons are costed equally, the optimal allocation of photons between these two arms is to have them equally distributed. This is different than the state of the art, in which the local field is stronger than the target return. The optimal processing of the photocurrent processes at the outputs of the two detectors is to perform log-matched filtering followed by a summation and peak detection. This implies that neither difference detection, nor Fourier-domain peak detection, which are the staples of the state-of-the-art systems, is optimal when a weak local oscillator is employed.

Erkmen, Baris I.↗

DOE OSTI2013

Rehabilitation of notch damaged steel beam using a carbon fiber reinforced multiphase-matrix composite

The retrofit of notch damaged steel beams is investigated via the experimental testing of nine wide-flange steel beam specimens and finite element simulation. Three notch configurations representing various damage levels were identified, and the beam specimens were retrofitted using CFRP laminates and a recently developed polymeric matrix composite - CarbonFlex - that exhibits superior energy dissipation and ductility properties, where the peak-load deflections were between 49.4% and 65.2% higher using the CarbonFlex-retrofitted beams. The results are attributed to the substantially higher damage tolerance capability of CarbonFlex than conventional CFRP. Finite element models were developed to investigate the damage processes and strain/ stress distributions near the notch tips. The numerical results match closely with the experimentally determined load-deflection curves and the strain fields obtained by the digital imaging correlations (DIC) system. Both experimental and numerical results clearly indicate the effectiveness of CarbonFlex, as a candidate retrofitting material, to retrofit damaged steel structures. Lastly, the micro-mechanisms by which CarbonFlex could sufficiently sustain a significant amount of the peak strength at large displacement ductility values are discussed with the aid of scanning electron microscopy (SEM) pictures.

Zhou, HongYu↗

DOE OSTI2015

D and D decision model and mobile application for selection of fixative, strippable coating, and decontamination gel products - 15696

Deactivation and decommissioning (D and D) is the process of taking an active/excess/abandoned facility to a final disposition end state. D and D presents unique hazards that must be addressed from a safety, programmatic, environmental, and technological standpoint. This definition is especially applicable to Savannah River Site's 235-F facility. The facility was constructed in the 1950's as part of the weapons complex materials production and fabrication. The most significant quantities of residual contamination remaining in 235-F building is in the form of Plutonium-238. A Decision Model was created using MatLab to work hand-in-hand with a product list containing commercially available D and D products. This model was created to further enhance and accelerate the decontamination process. It is envisioned that D and D engineers will be able to use this Decision Model in the field via a mobile device. It allows the user to select four inputs to match their situation. The model searches the database and returns the products that fit the criteria selected by the user. This Decision Model will be made available in a web-based application and as a mobile application to ensure end users can access it when needed. The MatLab code recognizes what position in the text box is selected and then this input is converted to the corresponding string. The string is then compared with the information in the product list in the specified column in order to reduce processing time. Then the products that contain the string inputted are displayed on the table and are separated by category. The web-based version of the model will receive three specified criteria and sub-criteria from the user and update the table with products that fit each criteria. A web-based version of this Decision Model is under way and will be set up on the D and D KM-IT platform. There will be two versions of this mobile application: for devices with internet connection and for those that do not have internet connection. This will ensure end users have access to the Decision application at any time or place during the D and D process. A mobile version of the model will also be developed in the near future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Data & Code from Phoenix CPPP Phase 2 Analysis

This data and code package supports the analysis presented in “Beyond Surface Cooling: Comprehensive Field Assessment of Reflective Pavement Thermal Performance in Phoenix, Arizona” and provides fully reproducible workflows for evaluating the thermal performance of cool pavement treatments in a hot urban environment. The dataset integrates multi-modal field measurements collected across residential and nonresidential settings, including mobile air temperature traverses, stationary air temperature monitoring, residential mean radiant temperature (MRT) measurements, subsurface temperature profiles, and controlled testbed observations. The data package contains raw and processed datasets in comma-separated value (CSV) format, accompanying metadata files describing site characteristics and measurement protocols, and R scripts (.R files) used for data cleaning, time synchronization, spatial and temporal matching, quality control filtering, statistical comparison, and figure generation. All analyses were conducted using R (version ≥ 4.2.0) with commonly available packages (e.g., tidyverse, lubridate, data.table, ggplot2). No proprietary software is required to reproduce results. Field campaigns were designed to quantify the effects of high-reflectance pavement coatings on surface temperature, near-surface air temperature, subsurface heat propagation, and radiative heat exposure. Temporal alignment procedures include standardized timestamp conversion and nearest-neighbor matching of high-frequency sensor measurements to stop-based metadata within defined tolerance windows to ensure comparability across instruments. The workflows generate summary statistics, treatment–control contrasts, depth-dependent thermal gradients, and time-series visualizations used in the associated publication. By integrating mobile, stationary, radiative, and subsurface measurements within a unified and transparent processing framework, this package enables comprehensive evaluation of cool pavement performance across multiple thermal exposure pathways and supports reuse in future urban heat mitigation and climate resilience studies.

AIR TEMPERATURE↗