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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quarterly Research Performance Progress Report (Q8)

As part of Task 1, we have started by testing our modeling capabilities by reproducing isothermal DFIT simulations presented in the literature. Once satisfied with the results we have started by targeting the modeling of the DFITs at conducted at well 58-32. We have a identified a specific test (cycle 4 in zone 2) as the most interesting to be model with GEOS hydraulic fracturing module. Thus, we have first produced results with an isothermal model and adjusted model parameters to get a satisfying match with field pressure data. The, we have added thermal effects and compared the modeling results with and without thermal effects to estimate how thermal effects may influence test interpretation. Models seem to suggest that, for small volumes of fluid, thermal effects are moderate. In Task 2, we have adapted GEOS phase-field formulation to be able to simulate near-wellbore hydraulic fracture nucleation and propagation. We have devised a novel formulation that, compared to other existing ones, incorporates rock strengths. We have submitted a journal publication about our work. We are currently employing this phase-field formulation to model the experiments taking place at U Pitt and help us understand the effect of various parameters. In Task 3, we have built a model of the region surround well 16A and have started modeling stage 3 stimulation because of its simpler planar geometry. After calibrating simulation parameters using known analytical solutions, we have simulated the stage 3 stimulation using our isothermal hydraulic fracturing module, varying the permeability field, the stress conditions including different physics to get a better understanding of the numerical challenges and of the effects of varying these parameters on the simulation results. In Task 4 laboratory experimentation, a set of specialized drilling and injection tools has been customized and constructed to accommodate an inclined well with an orientation of up to 30 degrees relative to material anisotropy or principal stress axes. These inclined samples have also undergone thermal stress and hydraulic fracturing at a temperature of 190 degrees Celsius. Furthermore, both vertical and deviated sampling testing setups enable an extended analysis of post-peak pressure behaviors, facilitating post-test pressure analyses such as the G-function, step rate, and fracture reopening measurements. Thus, the key components of in-situ stress estimation can be extracted and validated through our experiment, providing a solid foundation for validating existing in-situ stress estimation theories or proposing new ones. Simultaneously, we are integrating computer vision techniques with traditional experimental fracture observation methods such as multi-overcore/slicing and water-penetration fracture observation. This combination will prove beneficial in populating the hydraulic fracture patterns database, generated under challenging EGS conditions. This approach aims to deepen our understanding of the complexities in EGS reservoirs and pave the way for future data-driven investigations. Additionally, PITT has also equipped the ELE International compression machine, which is now prepared for conducting indirect tensile and fracture toughness tests. These tests will aid in characterizing how rock fabrics influence the resulting fracture patterns. Additionally, we have completed the required personnel training and gained access to Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) for conducting more detailed characterization and analysis of rock fabrics, as well as the examination of thermal and hydraulically induced fracture patterns. Thus, the PITT team has effectively demonstrated the capabilities of our experimental apparatuses in exploring the thermal effects, well deviation angles, material anisotropy, and operational choices (such as circulation rate, injection fluid viscosity, and injection rate) and their impact on pressure responses and fracture trajectories under the Utah FORGE conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

An Advanced ISOCS In Situ Gamma Spectrometry Services Tool to Reduce Uncertainties in Waste Characterization Projects - 16311

Canberra's In Situ Object Counting System (ISOCS) is an established tool used for gamma spectrometry allowing a physical representation of complex geometries and mathematical calculation of the calibration function. It avoids the need for radioisotope standards which can be costly and prohibitively difficult to produce. Uncertainties in the sample - detector geometry lead to uncertainties in the calibrations. Canberra's ISOCS Uncertainty Estimator (IUE) tool offers an automated means of accommodating known model geometry uncertainties, with calculation of robust defensible calibration uncertainties. However these uncertainties may be large leading to potential over-estimation of under-estimation of activity. This can be equated directly to waste disposal costs if one is using ISOCS for waste sentencing to classify wastes as (for example) Transuranic Waste (TRU) or Low Level Waste (LLW). An Advanced ISOCS in-situ Gamma Spectrometry (AIGS) services tool has been developed to reduce the uncertainties. This system is based on generating and comparing geometry models that yield Figures of Merit (FoM) indicative of improved consistency between modelled data and available diverse measurement data. This paper describes the development and features of AIGS, focusing on recent testing with radioisotope sources in a 200 litre drum filled with a simulated waste matrix. The results demonstrate a significant advantage for Am-241 where uncertainties can otherwise amount to a factor of 2 or more. We show how our specialist teams can develop procedures for deployment of standard ISOCS hardware, adapting measurement geometries and procedures through careful planning, to provide data that can be used to greatly reduce the uncertainties in the measured activities. Lastly, we comment on the range of potential applications for this new technique and the wider benefits for the decommissioning industry. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Collaborative development of diffraction-limited beamline optical systems at US DOE light sources

An ongoing collaboration among four US Department of Energy National Laboratories has demonstrated key technology prototypes and software modeling tools required for new high-coherent flux beamline optical systems. New free electron laser (FEL) and diffraction-limited storage ring (DLSR) light sources demand wavefront preservation from source to sample to achieve and maintain optimal performance. Fine wavefront control was achieved using a novel, roomtemperature cooled mirror system called REAL (resistive element adjustable length) that combines cooling with applied, spatially variable auxiliary heating. Single-grating shearing interferometry (also called Talbot interferometry) and Hartmann wavefront sensors were developed and used for optical characterization and alignment on several beamlines, across a range of photon energies. Demonstrations of non-invasive hard x-ray wavefront sensing were performed using a thin diamond single-crystal as a beamsplitter.

Goldberg, Kenneth A.↗
DOE OSTI2016

Implementation and testing of the on-the-fly thermal scattering Monte Carlo sampling method for graphite and light water in MCNP6

Here, a proper treatment of thermal neutron scattering requires accounting for chemical binding through a scattering law S(α,β,T). Monte Carlo codes sample the secondary neutron energy and angle after a thermal scattering event from probability tables generated from S(α,β,T) tables at discrete temperatures, requiring a large amount of data for multiscale and multiphysics problems with detailed temperature gradients. We have previously developed a method to handle this temperature dependence on-the-fly during the Monte Carlo random walk using polynomial expansions in 1/T to directly sample the secondary energy and angle. In this paper, the on-the-fly method is implemented into MCNP6 and tested in both graphite-moderated and light water-moderated systems. The on-the-fly method is compared with the thermal ACE libraries that come standard with MCNP6, yielding good agreement with integral reactor quantities like k-eigenvalue and differential quantities like single-scatter secondary energy and angle distributions. The simulation runtimes are comparable between the two methods (on the order of 5–15% difference for the problems tested) and the on-the-fly fit coefficients only require 5–15 MB of total data storage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesian inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Automated temporal tracking and segmentation of lymphoma on serial CT examinations

Purpose: It is challenging to reproducibly measure and compare cancer lesions on numerous follow-up studies; the process is time-consuming and error-prone. In this paper, we show a method to automatically and reproducibly identify and segment abnormal lymph nodes in serial computed tomography (CT) exams. Methods: Our method leverages initial identification of enlarged (abnormal) lymph nodes in the baseline scan. We then identify an approximate region for the node in the follow-up scans using nonrigid image registration. The baseline scan is also used to locate regions of normal, non-nodal tissue surrounding the lymph node and to map them onto the follow-up scans, in order to reduce the search space to locate the lymph node on the follow-up scans. Adaptive region-growing and clustering algorithms are then used to obtain the final contours for segmentation. We applied our method to 24 distinct enlarged lymph nodes at multiple time points from 14 patients. The scan at the earlier time point was used as the baseline scan to be used in evaluating the follow-up scan, resulting in 70 total test cases (e.g., a series of scans obtained at 4 time points results in 3 test cases). For each of the 70 cases, a ''reference standard'' was obtained by manual segmentation by a radiologist. Assessment according to response evaluation criteria in solid tumors (RECIST) using our method agreed with RECIST assessments made using the reference standard segmentations in all test cases, and by calculating node overlap ratio and Hausdorff distance between the computer and radiologist-generated contours. Results: Compared to the reference standard, our method made the correct RECIST assessment for all 70 cases. The average overlap ratio was 80.7 {+-} 9.7% s.d., and the average Hausdorff distance was 3.2 {+-} 1.8 mm s.d. The concordance correlation between automated and manual segmentations was 0.978 (95% confidence interval 0.962, 0.984). The 100% agreement in our sample between our method and the standard with regard to RECIST classification suggests that the true disagreement rate is no more than 6%. Conclusions: Our automated lymph node segmentation method achieves excellent overall segmentation performance and provides equivalent RECIST assessment. It potentially will be useful to streamline and improve cancer lesion measurement and tracking and to improve assessment of cancer treatment response.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Aluminum Metal Dissolution for Mark-18A Target Processing

The Mark-18A Program was established to preserve the unique materials found in Mark-18A targets for future research and development activity within the Department of Energy or other U.S. government agencies. The Savannah River Site has 65 Mark-18A targets to be provided for the recovery of high valued isotopes. The majority of the recovery work will be performed in the Savannah River National Laboratory (SRNL) Shielded Cells due to dose concerns. The recovered product will be transported to the Oak Ridge National Laboratory (ORNL) for future research and development tasks. The Mark-18A target material will be removed from their current configuration, dissolved, chemically separated, and calcined to a stable oxide. The baseline flowsheet is patterned after the flowsheet ORNL has previously used to process both Mark-18A and Mark-42 targets. However, it is necessary for SRNL to adapt its facility and the ORNL flowsheet to identify process improvements to successfully recover the actinide materials within the constraints of the SRNL Shielded Cells. These studies evaluated and demonstrated a chemical method for cladding removal using a mixture of sodium nitrate (NaNO 3 ) and sodium hydroxide (NaOH). Experiments provided better insights into dissolution of the Mark-18A aluminum cladding. In particular, these studies measured the effects of temperature on dissolution rate, flammable gas generation, and nitrite formation. Using the lessons learned from batch dissolution testing at SRNL, a continuous dissolution flowsheet was successfully demonstrated using prototypic-shaped materials and chemically-conservative materials. The SRNL target dissolution flowsheet departs from the baseline ORNL flowsheet in small but significant ways as discussed in the following paragraphs. These flowsheet changes facilitate faster initial reaction rates at a given temperature, enable cladding removal at a lower process temperature, and yield a more uniform dissolution rate throughout cladding removal. Multiple tests indicate that the total time at the dissolution temperatures will be about six hours for one fourth of a target. The shorter dissolution time provides the benefit of a single-shift dissolver operation. Off gas sampling determined that the quantities of flammable hydrogen (H 2 ) and ammonia (NH 3 ) expected in the process off gas will meet allowable flammable gas generation rates for the Shielded Cells Facility. The SRNL approach enables NaOH to be added at a constant rate, which simplifies operations in the shielded cells. In all six continuous dissolution tests, the process was easy to control with minimal operator interface. Analyses of process solutions throughout the experiments provide a better understanding of system behavior. The data show consistent behavior across several similar but different test conditions. Between the batch-test and continuous-test data, if future changes to the flowsheet are required, sufficient data exist to adequately predict how the system will respond to those changes. Future work will focus on design, fabrication, and evaluation of a system for dissolution of one-fourth of a Mark-18A target, which will be full-scale operations for SRNL. Based on these results, the process parameters are adequately understood and the system can be operated safely.

36 MATERIALS SCIENCE↗
DOE OSTI2025

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

SU-F-J-102: Lower Esophagus Margin Implications Based On Rapid Computational Algorithm for SBRT

Purpose: To quantify inter-fraction esophagus-variation. Methods: Computed tomography and daily on-treatment 0.3-T MRI data sets for 7 patients were analyzed using a novel Matlab-based (Mathworks, Natick, MA) rapid computational method. Rigid registration was performed from the cricoid to the gastro-esophageal junction. CT and MR-based contours were compared at slice intervals of 3mm. Variation was quantified by “expansion,” defined as additional length in any radial direction from CT contour to MR contour. Expansion computations were performed with 360° of freedom in each axial slice. We partitioned expansions into left anterior, right anterior, right posterior, and left posterior quadrants (LA, RA, RP, and LP, respectively). Sample means were compared by analysis of variance (ANOVA) and Fisher’s Protected Least Significant Difference test. Results: Fifteen fractions and 1121 axial slices from 7 patients undergoing SBRT for primary lung cancer (3) and metastatic lung disease (4) were analyzed, generating 41,970 measurements. Mean LA, RA, RP, and LP expansions were 4.30±0.05 mm, 3.71±0.05mm, 3.17±0.07, and 3.98±0.06mm, respectively. 50.13% of all axial slices showed variation > 5 mm in one or more directions. Variation was greatest in lower esophagus with mean LA, RA, RP, and LP expansion (5.98±0.09 mm, 4.59±0.09 mm, 4.04±0.16 mm, and 5.41±0.16 mm, respectively). The difference was significant compared to mid and upper esophagus (p<.0001). The 95th percentiles of expansion for LA, RA, RP, LP were 13.36 mm, 9.97 mm, 11.29 mm, and 12.19 mm, respectively. Conclusion: Analysis of on-treatment MR imaging of the lower esophagus during thoracic SBRT suggests margin expansions of 13.36 mm LA, 9.97 mm RA, 11.29 mm RP, 12.19 mm LP would account for 95% of measurements. Our novel algorithm for rapid assessment of margin expansion for critical structures with 360° of freedom in each axial slice enables continuously adaptive patient-specific margins which may reduce overlap with high-dose regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Eleven multiplanet systems from K2 campaigns 1 and 2 and the masses of two hot super-earths

We present a catalog of 11 multiplanet systems from Campaigns 1 and 2 of the K2 mission. We report the sizes and orbits of 26 planets split between seven two-planet systems and four three-planet systems. These planets stem from a systematic search of the K2 photometry for all dwarf stars observed by K2 in these fields. We precisely characterized the host stars with adaptive optics imaging and analysis of high-resolution optical spectra from Keck/HIRES and medium-resolution spectra from IRTF/SpeX. We confirm two planet candidates by mass detection and validate the remaining 24 candidates to >99% confidence. Thirteen planets were previously validated or confirmed by other studies, and 24 were previously identified as planet candidates. The planets are mostly smaller than Neptune (21/26 planets), as in the Kepler mission, and all have short periods (P < 50 days) due to the duration of the K2 photometry. The host stars are relatively bright (most have Kp < 12.5 mag) and are amenable to follow-up characterization. For K2-38, we measured precise radial velocities using Keck/HIRES and provide initial estimates of the planet masses. K2-38b is a short-period super-Earth with a radius of 1.55±0.16 R {sub ⊕}, a mass of 12.0±2.9 M {sub ⊕}, and a high density consistent with an iron-rich composition. The outer planet K2-38c is a lower-density sub-Neptune-size planet with a radius of 2.42±0.29 R {sub ⊕} and a mass of 9.9±4.6 M {sub ⊕} that likely has a substantial envelope. This new planet sample demonstrates the capability of K2 to discover numerous planetary systems around bright stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

AutoBEM: A scalable framework for nationwide building energy simulation and retrofit evaluation in the United States

This paper presents AutoBEM, an integrated, automated framework for nationwide building energy modeling and retrofit evaluation in the United States. Unlike prior UBEM platforms that either rely primarily on representative stock sampling or operate at city scale, AutoBEM automates the generation of building-resolved, physics-based EnergyPlus/OpenStudio simulation models at national scale using GIS-derived geometry, prototype-based assumptions, and standardized scalable workflows. Leveraging the Model America dataset and high-performance computing, AutoBEM generates and simulates energy models for 122.9 million buildings, representing 97.8% of the U.S. building stock. These models are being made publicly and freely available as the Model America v1.0 (MAv1) dataset. AutoBEM supports detailed, building-level assessments of energy consumption, CO2 emissions, and post-processed anthropogenic heat emissions (AHE), and evaluates 151 energy conservation measures (ECMs) using localized utility pricing and building characteristics. In addition, AutoBEM incorporates both typical and future climate conditions through integration with Typical Meteorological Year (TMY) and Future TMY (fTMY) weather data derived from IPCC scenarios. In a case study of Phoenix, Arizona, AutoBEM identified several high-efficiency HVAC upgrades and selected envelope measures with short modeled payback periods (1.5 years) for certain building types and standards. Simulations under future climate scenarios (SSP5–RCP8.5) project an 11.3% increase in electricity use and a 32% reduction in natural gas demand by 2100, underscoring the need for climate-adaptive retrofit planning. By enabling reproducible, bottom-up, and location-specific analysis at scale, AutoBEM provides a step toward a national digital twin of the built environment and supports data-driven screening and planning for decarbonization, resilience, and energy equity.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

A continuation multilevel Monte Carlo algorithm

Here, we propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. Moreover, the actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Our numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

miR-138 protects cardiomyocytes from hypoxia-induced apoptosis via MLK3/JNK/c-jun pathway

Highlights: •First time to find miR-138 is up-regulated in hypoxic cardiomyocytes. •First time to find miR-138 targets MLK3 and regulates JNK/c-jun pathway. •Rare myocardial biopsy of patients with CHD were collected. •Both silence and overexpression of miR-138 were implemented. •Various methods were used to detect cell function. -- Abstract: Cardiomyocytes experience a series of complex endogenous regulatory mechanisms against apoptosis induced by chronic hypoxia. MicroRNAs are a class of endogenous small non-coding RNAs that regulate cellular pathophysiological processes. Recently, microRNA-138 (miR-138) has been found related to hypoxia, and beneficial for cell proliferation. Therefore, we intend to study the role of miR-138 in hypoxic cardiomyocytes and the main mechanism. Myocardial samples of patients with congenital heart disease (CHD) were collected to test miR-138 expression. Agomir or antagomir of miR-138 was transfected into H9C2 cells to investigate its effect on cell apoptosis. Higher miR-138 expression was observed in patients with cyanotic CHD, and its expression gradually increased with prolonged hypoxia time in H9C2 cells. Using MTT and LDH assays, cell growth was significantly greater in the agomir group than in the negative control (NC) group, while antagomir decreased cell survival. Dual luciferase reporter gene and Western-blot results confirmed MLK3 was a direct target of miR-138. It was found that miR-138 attenuated hypoxia-induced apoptosis using TUNEL, Hoechst staining and Annexin V-PE/7-AAD flow cytometry analysis. We further detected expression of apoptosis-related proteins. In the agomir group, the level of pro-apoptotic proteins such as cleaved-caspase-3, cleaved-PARP and Bad significantly reduced, while Bcl-2 and Bcl-2/Bax ratio increased. Opposite changes were observed in the antagomir group. Downstream targets of MLK3, JNK and c-jun, were also suppressed by miR-138. Our study demonstrates that up-regulation of miR-138 plays a protective role in myocardial adaptation to chronic hypoxia, which is mediated mainly by MLK3/JNK/c-jun signaling pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Chebyshev polynomial filtered subspace iteration in the discontinuous Galerkin method for large-scale electronic structure calculations

The Discontinuous Galerkin (DG) electronic structure method employs an adaptive local basis (ALB) set to solve the Kohn-Sham equations of density functional theory in a discontinuous Galerkin framework. The adaptive local basis is generated on-the-fly to capture the local material physics and can systematically attain chemical accuracy with only a few tens of degrees of freedom per atom. A central issue for large-scale calculations, however, is the computation of the electron density (and subsequently, ground state properties) from the discretized Hamiltonian in an efficient and scalable manner. We show in this work how Chebyshev polynomial filtered subspace iteration (CheFSI) can be used to address this issue and push the envelope in large-scale materials simulations in a discontinuous Galerkin framework. We describe how the subspace filtering steps can be performed in an efficient and scalable manner using a two-dimensional parallelization scheme, thanks to the orthogonality of the DG basis set and block-sparse structure of the DG Hamiltonian matrix. The on-the-fly nature of the ALB functions requires additional care in carrying out the subspace iterations. We demonstrate the parallel scalability of the DG-CheFSI approach in calculations of large-scale twodimensional graphene sheets and bulk three-dimensional lithium-ion electrolyte systems. In conclusion, employing 55 296 computational cores, the time per self-consistent field iteration for a sample of the bulk 3D electrolyte containing 8586 atoms is 90 s, and the time for a graphene sheet containing 11 520 atoms is 75 s.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

THE PROPERTIES OF THE STAR-FORMING INTERSTELLAR MEDIUM AT z = 0.8-2.2 FROM HiZELS: STAR FORMATION AND CLUMP SCALING LAWS IN GAS-RICH, TURBULENT DISKS

We present adaptive optics assisted integral field spectroscopy of nine H{alpha}-selected galaxies at z = 0.84-2.23 drawn from the HiZELS narrowband survey. Our observations map the kinematics of these star-forming galaxies on {approx}kpc scales. We demonstrate that within the interstellar medium of these galaxies, the velocity dispersion of the star-forming gas ({sigma}) follows a scaling relation {sigma}{proportional_to}{Sigma}{sup 1/n} {sub SFR} + constant (where {Sigma}{sub SFR} is the star formation surface density and the constant includes the stellar surface density). Assuming the disks are marginally stable (Toomre Q = 1), this follows from the Kennicutt-Schmidt relation ({Sigma}{sub SFR} = A{Sigma} {sup n} {sub gas}), and we derive best-fit parameters of n = 1.34 {+-} 0.15 and A = 3.4{sup +2.5} {sub -1.6} Multiplication-Sign 10{sup -4} M {sub Sun} yr{sup -1} kpc{sup -2}, consistent with the local relation, and implying cold molecular gas masses of M {sub gas} = 10{sup 9-10} M {sub Sun} and molecular gas fractions of M {sub gas}/(M {sub gas} + M {sub *}) = 0.3 {+-} 0.1, with a range of 10%-75%. We also identify 11 {approx}kpc-scale star-forming regions (clumps) within our sample and show that their sizes are comparable to the wavelength of the fastest growing mode. The luminosities and velocity dispersions of these clumps follow the same scaling relations as local H II regions, although their star formation densities are a factor {approx}15 {+-} 5 Multiplication-Sign higher than typically found locally. We discuss how the clump properties are related to the disk, and show that their high masses and luminosities are a consequence of the high disk surface density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Acoustic Monitoring of Beluga Whale Interactions with Cook Inlet Tidal Energy Project

Cook Inlet, Alaska is home to some of the greatest tidal energy resources in the U.S., as well as an endangered population of beluga whales (Delphinapterus leucas). Successfully permitting and operating a tidal power project in Cook Inlet requires a biological assessment of the potential and realized effects of the physical presence and sound footprint of tidal turbines on the distribution, relative abundance, and behavior of Cook Inlet beluga whales. ORPC Alaska, working with the Project Team—LGL Alaska Research Associates, University of Alaska Anchorage, TerraSond, and Greeneridge Science—undertook the following U.S. Department of Energy (DOE) study to characterize beluga whales in Cook Inlet – Acoustic Monitoring of Beluga Whale Interactions with the Cook Inlet Tidal Energy Project (Project). ORPC Alaska, LLC, is a wholly-owned subsidiary of Ocean Renewable Power Company, LLC, (collectively, ORPC). ORPC is a global leader in the development of hydrokinetic power systems and eco-conscious projects that harness the power of ocean and river currents to create clean, predictable renewable energy. ORPC is developing a tidal energy demonstration project in Cook Inlet at East Foreland where ORPC has a Federal Energy Regulatory Commission (FERC) preliminary permit (P-13821). The Project collected baseline data to characterize pre-deployment patterns of marine mammal distribution, relative abundance, and behavior in ORPC’s proposed deployment area at East Foreland. ORPC also completed work near Fire Island where ORPC held a FERC preliminary permit (P-12679) until March 6, 2013. Passive hydroacoustic devices (previously utilized with bowhead whales in the Beaufort Sea) were adapted for study of beluga whales to determine the relative abundance of beluga whale vocalizations within the proposed deployment areas. Hydroacoustic data collected during the Project were used to characterize the ambient acoustic environment of the project site pre-deployment to inform the FERC pilot project process. The Project compared results obtained from this method to results obtained from other passive hydrophone technologies and to visual observation techniques performed simultaneously. This Final Report makes recommendations on the best practice for future data collection, for ORPC’s work in Cook Inlet specifically, and for tidal power projects in general. This Project developed a marine mammal study design and compared technologies for hydroacoustic and visual data collection with potential for broad application to future tidal and hydrokinetic projects in other geographic areas. The data collected for this Project will support the environmental assessment of future Cook Inlet tidal energy projects, including ORPC’s East Foreland Tidal Energy Project and any tidal energy developments at Fire Island. The Project’s rigorous assessment of technology and methodologies will be invaluable to the hydrokinetic industry for developing projects in an environmentally sound and sustainable way for areas with high marine mammal activity or endangered populations. By combining several different sampling methods this Project will also contribute to the future preparation of a comprehensive biological assessment of ORPC’s projects in Cook Inlet.

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DOE OSTI2017

Geothermal Play Fairway Analysis of the Snake River Plain: Phase 2

Play Fairway Analysis (PFA) is a methodology adapted from the petroleum industry that integrates data at the regional or basin scale to define favorable plays for exploration in a systematic fashion. Phase 2 of our Play Fairway Analysis of the Western Snake River Plain (WSRP) province in southern Idaho had three primary goals: first, to fill data gaps in critical areas in order to better define potential prospects, second, to integrate these data into new thermal and structural models, and finally, to infer the location of potential resources and drilling targets that could be validated during Phase 3. Prospects in the WSRP identified as potential target resources for Phase 3 validation include the Mountain Home region close to the Air Force Base, and the Camas Prairie. The Mountain Home region represents a blind geothermal resource in an area of high heat flow and young volcanism. The Camas Prairie is a semi-blind, structurally controlled resource in an area with indicators of magmatic heat. New geophysical data acquired at these sites includes reflection seismic, gravity and magnetic surveys, and a magnetotelluric field survey. New geochemical data collection focused on the Camas Prairie, and included the aqueous and isotope geochemistry of hot springs, cold springs, and wells (geothermal, groundwater, and irrigation). New field mapping, sampling, and basalt flow chronology was also conducted at Camas Prairie. Integrated results from Phase 1 and 2 studies suggest that the blind system near the Mountain Home Air Force Base is located at ~1.5– 2.3 km depth, and the structurally-controlled system at Camas Prairie is shallower, with upper reservoir depths perhaps only ~0.5–0.7 km.

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