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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Obtaining a Special Administrative License Exemption to Ship the West Valley Melter Box - 16327

In order to ship the West Valley Melter Package (WVMP) package to support its disposal, the U.S. Department of Energy (DOE) requested a one-time shipment license exemption from the U.S. Nuclear Regulatory Commission (NRC). Based on content, the previously constructed WVMP, containing residual borosilicate glass and Low Density Cellular Concrete was shown to require a Type B Package. Therefore, Title 10 of the United States Code of Federal Regulations, Part 71 (10 CFR 71) required that radioactive releases under Normal Conditions of Transport (NCT) and Hypothetical Accident Conditions (HAC) would remain less than 1 E-7 A{sub 2}/hour and 1 E-1 A{sub 2}/week, respectively. Although the NRC normal method for demonstrating conformance to the 10CFR71 requirement is through performance of leak rate testing per American National Standards Institute (ANSI) standard N14.5, the WVMP does not contain a pressure vessel; therefore, performance of leak rate testing was not applicable/possible. Instead, an alternate method, adapted from DOE Handbook 3010 was used to show that the maximum allowed 10 CFR 71 radionuclide release rates for NCT and HAC would not be exceeded. Summarizing the effort, this paper provides the technical synopsis for requesting the exemption. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Comparison of ADVANTG Simulations to Simple Shielding Measurements - Paper 36

Monte Carlo (MC) radiation transport simulations, like those performed using Monte Carlo N-Particle (MCNP), can be highly accurate but require time to reduce the statistical uncertainties in the calculated detector response(s). Many different 'variance reduction' techniques devised over the years increase the efficiency of MC calculations, but these methods can be more art than science. Many of these methods are problem specific or require careful tuning of parameters for good performance. One of the best variance reduction methods, in terms of both reliable performance increases and ease of use, is the use of weight windows. Weight windows are derived from an importance map in space and energy that allows the transport code to focus more simulation time on particles that have a higher likelihood of being important to the final detector response. Less time is spent simulating particles that have little chance of making a contribution to the detector response. MCNP already includes the abilities to generate and use weight windows. Unfortunately, generating weight windows can take a very long time, perhaps longer than the original problem. Oak Ridge National Laboratory has led the development of hybrid methods using a discrete ordinates adjoint calculation to quickly develop an importance map (weight windows) for use in a Monte Carlo code. The Consistent Adjoint Driven Importance Sampling (CADIS) method uses an adjoint calculation to develop both an importance map and a biased source distribution that work together. This method is reasonably automatic, is easy to use, and has been implemented in the Automated Variance reduction Generator (ADVANTG) package that works with MCNP5. ADVANTG reads an MCNP input file and a small amount of extra user information and then runs an adjoint deterministic calculation using Denovo. The importance map and biased source distribution derived from the CADIS method can then be incorporated back into the original MCNP input file to enhance the figure-of-merit (FOM) of the calculation. The FOM is a measure of the efficiency of the calculation using the amount of run time and corresponding level of statistical uncertainty in the detector result. ADVANTG-enhanced MCNP input files have been shown to increase the FOM of many types of problems, obtaining the same level of statistical uncertainty in a shorter time compared to standard MCNP. ADVANTG can also generate variance reduction parameters (importance map and biased source) using the Forward-Weighted CADIS (FW-CADIS) method for optimizing mesh tallies. The CADIS method creates variance reduction parameters that optimize a tally's total quantity (flux, dose rate, interaction rate, etc.) and will not generally increase performance for all parts of a segmented tally. To optimize a segmented tally, the FW-CADIS method uses two discrete ordinates calculations to make variance reduction parameters that help compute a segmented tally with uniform relative uncertainties in each bin. This report will demonstrate that using ADVANTG for neutron and photon radiation shielding problems will (1) preserve the standard MCNP results and (2) obtain those results either with less statistical uncertainty or in shorter times than the standard MCNP calculation. The four demonstration problems in this report are based on simple neutron or photon transmission measurements through different materials. All of the problems here used the CADIS method and still saw improvement across the flux tallies segmented by particle energy. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-F-T-33: Air-Kerma Strength and Dose Rate Constant by the Full Monte Carlo Simulations

Purpose: In general, the air-kerma strength (Sk) has been determined by the energy weighting the photon energy fluence and the corresponding mass-energy absorption coefficient or mass-energy transfer coefficient. Kerma is an acronym for kinetic energy released per unit mass, defined as the sum of the initial kinetic energies of all the charged particles. Monte Carlo (MC) simulations can investigate the kinetic energy of the charged particles after photo interactions and sum the energy. The Sk of {sup 192}Ir source is obtained in the full MC simulation and finally the dose rate constant Λ is determine. Methods: MC simulations were performed using EGS5 with the microSelectron HDR v2 type of {sup 192}Ir source. The air-kerma rate obtained to sum the electron kinetic energy after photoelectric absorption or Compton scattering for transverse-axis distance from 1 to 120 cm with a 10 m diameter air phantom. Absorbed dose in water is simulated with a 30 cm diameter water phantom. The transport cut-off energy is 10 keV and primary photons from the source need two hundred and forty billion in the air-kerma rate and thirty billion in absorbed dose in water. Results: Sk is multiplied by the square of the distance in air-kerma rate and determined by fitting a linear function. The result of Sk is (2.7039±0.0085)*10-{sup −11} µGy m{sup 2} Bq{sup −1} s{sup −1}. Absorbed dose rate in water at 1 cm transverse-axis distance D(r{sub 0}, θ{sub 0}) is (3.0114±0.0015)*10{sup −11} cGy Bq{sup −1} s{sup −1}. Conclusion: From the results, dose rate constant Λ of the microSelectron HDR v2 type of {sup 192}Ir source is (1.1137±0.0035) cGy h{sup −1} U{sup −1} by the full MC simulations. The consensus value conΛ is (1.109±0.012) cGy h{sup −1} U{sup −1}. The result value is consistent with the consensus data conΛ.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Rating PV Power and Energy: Cell, Module, and System Measurements

A summary of key points related to research-level measurements of current vs. voltage measurement theory including basic PV operation, equivalent circuit, and concept of spectral error; PV power performance including PV irradiance sensors, simulators and commercial and generic I-V systems; PV measurement artifacts, intercomparisons, and alternative rating methods.

14 SOLAR ENERGY↗
DOE OSTI2026

Stochastic Microgrid Scheduling With Chance‐Constrained Resilience Consideration

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

chance constrained optimization↗
DOE OSTI2014

The {sup 13}C(α,n){sup 16}O reaction as a neutron source for the s-process in AGB low-mass stars

The {sup 13}C(α,n){sup 16}O reaction is considered to be the most important neutron source for producing the main component of the s-process in low mass stars. In this paper we focus our attention on two of the main open problems concerning its operation as a driver for the slow neutron captures. Recently, a new measurement of the {sup 13}C(α,n){sup 16}O reaction rate was performed via the Trojan Horse Method greatly increasing the accuracy. Contemporarily, on the modelling side, magnetic mechanisms were suggested to justify the production of the {sup 13}C pocket, thus putting the s-process in stars on safe physical ground. These inputs allow us to reproduce satisfactorily the solar distribution of elements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Characterization of Wrapped Coil Tank Water Heater during Charging/Discharging

Heat pump water heaters (HPWH) are an energy efficient method for water heating compared to conventional electric water heaters. A wrapped coil around the water tank is often used as the condenser for the heat pump for such applications. Thermal stratification, caused by varying heat transfer rate from the condenser to the water depending on the phase of the refrigerant and the wrap configuration, is often observed inside the tank, especially for HPWHs using CO2 as the refrigerant. The current study investigates the impact of the charging/discharging process on thermal stratification. A series of simulations were conducted based on the draw patterns recommended by the DOE method of test for rating water heater performance. We also analyzed the water circulation patterns during charging/discharging process. The thermal stratification was adversely affected because of the circulation even when the Heat Pump (HP) was operational. It was observed that a relatively higher charge/discharge flow rate disrupts the thermal stratification quickly and thus lowers the supply water temperature. Furthermore, the duration of charging/discharging also plays an important role. It was noticed that the back flow has insignificant effect on the supply water temperature if charging/discharging time is relatively small. However, the effect was obvious for larger water draw flow rates that last for longer time.

Elatar, Ahmed↗
DOE OSTI2018

Global variance reduction method applied to HBR-2 benchmark - 25144

It is a great challenge to obtain reliable results in reasonable time by the Monte Carlo (MC) method in solving deep-penetration shielding problems. Global variance reduction (GVR) method uses biased source and weight window to decrease MC calculation tally error for deep-penetration problems. However, excessive splitting of large weight particles out of the source region is time-consuming for problems with significant fluence rate variation. A new GVR method, which performs space and energy splitting/roulette based on the importance of the phase space, is proposed in this paper to avoid excessive splitting of large weight particles. The improved GVR method is applied to HBR-2 benchmark. Numerical results show that the new GVR method achieves good corresponding results to those of references. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Noninvasive differential diagnosis of dental periapical lesions in cone-beam CT scans

Purpose: This paper proposes a novel application of computer-aided diagnosis (CAD) to an everyday clinical dental challenge: the noninvasive differential diagnosis of periapical lesions between periapical cysts and granulomas. A histological biopsy is the most reliable method currently available for this differential diagnosis; however, this invasive procedure prevents the lesions from healing noninvasively despite a report that they may heal without surgical treatment. A CAD using cone-beam computed tomography (CBCT) offers an alternative noninvasive diagnostic tool which helps to avoid potentially unnecessary surgery and to investigate the unknown healing process and rate for the lesions. Methods: The proposed semiautomatic solution combines graph-based random walks segmentation with machine learning-based boosted classifiers and offers a robust clinical tool with minimal user interaction. As part of this CAD framework, the authors provide two novel technical contributions: (1) probabilistic extension of the random walks segmentation with likelihood ratio test and (2) LDA-AdaBoost: a new integration of weighted linear discriminant analysis to AdaBoost. Results: A dataset of 28 CBCT scans is used to validate the approach and compare it with other popular segmentation and classification methods. The results show the effectiveness of the proposed method with 94.1% correct classification rate and an improvement of the performance by comparison with the Simon’s state-of-the-art method by 17.6%. The authors also compare classification performances with two independent ground-truth sets from the histopathology and CBCT diagnoses provided by endodontic experts. Conclusions: Experimental results of the authors show that the proposed CAD system behaves in clearer agreement with the CBCT ground-truth than with histopathology, supporting the Simon’s conjecture that CBCT diagnosis can be as accurate as histopathology for differentiating the periapical lesions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Wavefront shaping with a Hadamard basis for scattering soil imaging

Here, soil is a scattering medium that inhibits imaging of plant-microbial-mineral interactions that are essential to plant health and soil carbon sequestration. However, optical imaging in the complex medium of soil has been stymied by the seemingly intractable problems of scattering and contrast. Here, we develop a wavefront shaping method based on adaptive stochastic parallel gradient descent optimization with a Hadamard basis to focus light through soil mineral samples. Our approach allows a sparse representation of the wavefront with reduced dimensionality for the optimization. We further divide the used Hadamard basis set into subsets and optimize a certain subset at once. Simulation and experimental optimization results demonstrate our method has an approximately seven times higher convergence rate and overall better performance compared to that with optimizing all pixels at once. The proposed method can benefit other high-dimensional optimization problems in adaptive optics and wavefront shaping.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

An Efficient Pipeline for Abdomen Segmentation in CT Images

Computed tomography (CT) scans usually include some disadvantages due to the nature of the imaging procedure, and these handicaps prevent accurate abdomen segmentation. Discontinuous abdomen edges, bed section of CT, patient information, closeness between the edges of the abdomen and CT, poor contrast, and a narrow histogram can be regarded as the most important handicaps that occur in abdominal CT scans. Currently, one or more handicaps can arise and prevent technicians obtaining abdomen images through simple segmentation techniques. In other words, CT scans can include the bed section of CT, a patient’s diagnostic information, low-quality abdomen edges, low-level contrast, and narrow histogram, all in one scan. These phenomena constitute a challenge, and an efficient pipeline that is unaffected by handicaps is required. In addition, analysis such as segmentation, feature selection, and classification has meaning for a real-time diagnosis system in cases where the abdomen section is directly used with a specific size. A statistical pipeline is designed in this study that is unaffected by the handicaps mentioned above. Intensity-based approaches, morphological processes, and histogram-based procedures are utilized to design an efficient structure. Performance evaluation is realized in experiments on 58 CT images (16 training, 16 test, and 26 validation) that include the abdomen and one or more disadvantage(s). The first part of the data (16 training images) is used to detect the pipeline’s optimum parameters, while the second and third parts are utilized to evaluate and to confirm the segmentation performance. The segmentation results are presented as the means of six performance metrics. Thus, the proposed method achieves remarkable average rates for training/test/validation of 98.95/99.36/99.57% (jaccard), 99.47/99.67/99.79% (dice), 100/99.91/99.91% (sensitivity), 98.47/99.23/99.85% (specificity), 99.38/99.63/99.87% (classification accuracy), and 98.98/99.45/99.66% (precision). In summary, a statistical pipeline performing the task of abdomen segmentation is achieved that is not affected by the disadvantages, and the most detailed abdomen segmentation study is performed for the use before organ and tumor segmentation, feature extraction, and classification.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Transmission Line Ampacity Improvements of AltaLink Wind Plant Overhead Tie-Lines Using Weather-Based Dynamic Line Rating

Abstract—Overhead transmission lines (TLs) are conventionally given seasonal ratings based on conservative environmental assumptions. Such an approach often results in underutilization of the line ampacity as the worst conditions prevail only for a short period over a year/season. We presents dynamic line rating (DLR) as an enabling smart grid technology that adaptively computes ratings of TLs based on local weather conditions to utilize additional headroom of existing lines. In particular, general line ampacity state solver utilizes measured weather data for computing the real-time thermal rating of the TLs. The performance of the presented method is demonstrated from a field study of DLR technology implementation on four TL segments at AltaLink, Canada. The performance is evaluated and quantified by comparing the existing static and proposed dynamic line ratings, and the potential benefits of DLR for enhanced transmission assets utilization. For the given line segments, the proposed DLR results in real-time ratings above the seasonal static ratings for most of the time; up to 95.1% of the time, with a mean increase of 72% over static rating.

17 WIND ENERGY↗
DOE OSTI2025

The development and application of the stirred‐reactor coupon analysis (SRCA) test method

A new technique, termed the stirred‐reactor coupon analysis (SRCA) method, has been developed to measure the rate of glass dissolution in forward‐rate conditions. Monolithic glass coupons are partially masked with an inert material before placement in a large volume of well‐mixed solution with known chemistry and temperature for a predetermined duration. After the test, the mask is removed, and the difference in step height between the protected area and the exposed corroded portions of the sample coupon is measured to determine the extent of glass dissolution. The step height is converted to a rate measurement using the test duration and glass density. Test parameters such as sample surface preparation and test duration were evaluated to determine their effects on the measured rates. Additionally, results from an interlaboratory study (ILS) consisting of 12 laboratories from 11 different institutions are presented, where each laboratory performed 12 independent tests. When removing experimental outlier data, the 95% reproducibility limits for the SRCA method has no statistical difference with previously published standardized test methods used to determine the forward rate of glass dissolution. Overall, this paper describes steps necessary to perform the test method and provides the statistical calculations to evaluate test accuracy.

chemical durability↗
DOE OSTI2023

Results of FY 2023 Alloy 617 and Alloy 709 High-Temperature Crack-Growth Testing

This report summarizes the work performed at Idaho National Laboratory under the “Creep, fatigue and creep-fatigue crack growth tests” task of the “Long-Term VHTR Material Qualification – INL” work package. Work was performed this year to validate the crack growth monitoring setup used with the test frames against both continuous crack length monitoring using an optical camera, as well as post-mortem analysis of marker bands on the fracture surface. Delays prevented the use of a gauge to measure load-line displacement for early tests, and so the creep-fatigue crack growth setup was evaluated using the actuator displacement for a load-line displacement setup. While not ideal, this allowed examination of the shortcomings with the current software setup that was originally designed for performing stress corrosion crack growth rate studies. The method for data collection was modified to link the crack growth monitoring software with Instron’s Wave Matrix software. Once the load-line displacement gauge arrived, the crack growth equipment was successfully modified to permit continuous monitoring of both load-line displacement and crack length. This is critical for creep-fatigue and creep crack growth rate studies for ductile material, as it permits the C* and Ct analyses. Test results are shown for Alloy 617 fatigue and creep-fatigue (without the gauge for load-line displacement measurements), as well as creep-fatigue of Alloy 709, which was performed with the completed test setup, allowing for crack length and load-line displacement monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Magnetite (Fe 3 O 4 )—multiwalled carbon nanotube composite structures with performance as high rate electrode materials for Li-ion batteries

A method of synthesizing an electrode material for lithium ion batteries from Fe 3 O 4 nanoparticles and multiwalled carbon nanotubes (MWNTs) to yield (Fe 3 O 4 -NWNTs) composite heterostructures. The method includes linking the Fe 3 O 4 nanoparticles and multiwalled carbon nanotubes using a π-π interaction synthesis process to yield the composite heterostructure electrode material. Since Fe 3 O 4 has an intermediate voltage, it can be considered an anode (when paired with a higher voltage material) or a cathode (when paired with a lower voltage material).

Wong, Stanislaus↗
DOE OSTI2018

Compact 3D Copper with Uniform Porous Structure Derived by Electrochemical Dealloying as Dendrite-Free Lithium Metal Anode Current Collector

Here, the development of lithium (Li) metal anodes Li metal batteries faces huge challenges such as uncontrolled Li dendrite growth and large volume change during Li plating/stripping, resulting in severe capacity decay and high safety hazards. A 3D porous copper (Cu) current collector as a host for Li deposition can effectively settle these problems. However, constructing a uniform and compact 3D porous Cu structure is still an enormous challenge. Herein, an electrochemical etching method for Cu–Zinc (Zn) alloy is reported to precisely engrave a 3D Cu structure with uniform, smooth, and compact porous network. Such a continuous structure endows 3D Cu excellent mechanical properties and high electrical conductivity. The uniform and smooth pores with a large internal surface area ensures well dispersed current density for homogeneous Li metal deposition and accommodation. A smooth and stable solid electrolyte interphase is formed and meanwhile Li dendrites and dead Li are effectively suppressed. The Li metal anode conceived 3D Cu current collector can stably cycle for 400 h under an Li plating/stripping capacity of 1 mA h cm –2 and a current density of 1 mA cm –2 . The Li@3D Cu||LiFePO 4 full cells present excellent cycling and rate performances. The electrochemical dealloying is a robust method to construct 3D Cu current collectors for dendrite–free Li metal anodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Insights into Chemical Prelithiation of SiO x /Graphite Composite Anodes through Scanning Electron Microscope Imaging

Initial Coulombic efficiency (ICE) is critical for determining the energy density of lithium-ion batteries (LIBs) used for practical applications; however, it is typically disregarded in anode research. We used SiO x and graphite composite anodes for commercial lithium-ion batteries in our preliminary research to achieve a balance between ICE, capacity, and cycling life. ICE reached 88%; however, it needs further improvement for commercial applications. Prelithiation is a process that involves the introduction of extra lithium ions into LIBs during their manufacturing to enhance the overall performance of the LIBs. We applied a chemical prelithiation method on our SiO x /graphite composite anodes, which comprised 95 wt % of the active material mass loading on the electrode. The ICE increased from 88% to 98% using an aryllithium reagent impregnation method within 2 min of prelithiation. The anode’s specific capacity density, rate, and cycle performance also significantly improved. Scanning electron microscopy (SEM) imaging enhanced by an osmium tetroxide staining method indicated that the P-anode contained a stable solid electrolyte interface (SEI) layer after the prelithiation process and cycling electrochemical test. The P-anode’s stable charge differential peak over 500 cycles also showcases a robust artificial SEI layer that was generated by the prelithiation procedure. Here, this prelithiation process has significant potential for adoption in the LIB industry’s current electrode manufacturing process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluating county-level lung cancer incidence from environmental radiation exposure, PM 2.5 , and other exposures with regression and machine learning models

Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM 2.5 , may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute’s Surveillance, Epidemiology, and End-Results data (2013–17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross γ activity and indoor radon) and PM 2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM 2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM 2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure’s association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗