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For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorge.c1 (ge=general sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.
For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorhi.c1 (hi=high sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.
For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorge.c1 (ge=general sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity. Note that reflectivity in this product is not calibrated.
Performance confirmation is an important element of the Waste Isolation Pilot Plant (WIPP) program. Performance confirmation was first used during the early WIPP site characterization phase to focus experimental activities that address the development of probabilistic repository performance models and to address stakeholder assurance needs. The program is currently used to analyze the conditions of the repository and its surroundings to ensure that the basis for the repository's long-term radioactive waste containment predictions is valid. This basis is related to the parameters, assumptions, conceptual and numerical models that are used to predict or validate the potential radioactive waste containment performance of the system. The concept of performance confirmation for the WIPP is one that has evolved since the first repository work was initiated decades ago and plays an important role in assuring adequate repository performance both now and in the long-term. The WIPP mission has progressed from a pilot project to an operational disposal facility and will progress to eventual site closure when disposal operations are completed. Performance confirmation is an important part of each of these progressions. The concept of disposing radioactive waste in a geologic repository today involves a complete understanding of many technical, political, regulatory, societal and economic elements. Many of these elements overlap and solving all relevant issues necessary to site, operate and decommission a disposal facility should be done with knowledge of each element's requirements and impacts. Performance confirmation is one tool that can help to coordinate many of these elements into a program that actively investigates what is thought to be adequately understood about the system and what information is lacking. A performance confirmation program is used to determine ways to challenge and verify those areas that are thought to be understood and to find ways to understand those areas that are not well understood. Performance confirmation programs have been used twice at WIPP, first during site characterization and PA development and later in a Compliance Monitoring program. At first, only certain technical aspects of the system were deemed important because it was a scientifically-based, government project. Early site characterization work was design to gather information about the geology and hydrology of the area and the mechanical properties of the natural barrier. The information would be used in a PA to determine the long-term containment performance of the disposal system. A performance confirmation element was used to identify the sensitive elements of the system that were certain, well understood or justified and those that were not. It identified experimental and analytical programs that could be used to reduce uncertainty, confirm sensitive assumptions and provide useful data. This performance confirmation program provided data to justify the adequacy of the information used in PA to demonstrate compliance with EPA's containment requirements. Performance confirmation will continue to be used in the post-closure period for at least 30 years and likely up to the end of the 100-year institutional controls period. As the technical basis for the repository matures throughout the operational period, the currently planned post-closure monitoring program will need to be reassessed prior to implementation. However, the intent of the program will be the same as it was for the previous programs, to ensure the ultimate goal of the repository. This goal is to safely isolate waste from the accessible environment and ensure public and environmental safety. (authors)
Lawrence Livermore National Laboratory has completed the final design for the first phase of the Thermal Epithermal experiments (TEX), which focused on critical configurations composed of plutonium/aluminum Zero Power Physics Reactor (ZPPR) plates moderated by polyethylene with and without a tantalum diluent. {sup 239}Pu and {sup 240}Pu were identified as being the number one and two nuclear data need by the nuclear criticality safety and nuclear data communities, with special emphasis placed on performance issues of the Pu cross sections in the intermediate energy region. Preliminary TEX design recommended tantalum as the first diluent to pursue for final design, as it represented a high priority data need, showed the highest sensitivity and largest contribution to uncertainty with the Pu ZPPR system, and a large number of high quality Ta plates from the ZPPR inventory in Idaho was readily available. The goals of the new critical experiments are 1) to create assemblies that span a wide range of fission energy spectra, from thermal (below 0.625 eV), through the intermediate (0.65 eV to 100 keV), and to fast energies (above 100 keV), and 2) to easily modify the assemblies to include high priority materials like tantalum. A total of ten critical configurations were designed as part of CED-2. Five TEX experiments (Experiments 1-5) were designed to establish baseline configurations with the Pu ZPPR plates covering the thermal, intermediate, and fast fission energy regimes. For all five experiments, the ZPPR plates will be arranged in layers of 24 plates (6 plates by 4 plates), resulting in approximately a 12 inch by 12 inch footprint. Multiple layers will be stacked together with varying thicknesses of interspersed polyethylene placed between the layers to fine tune the neutron spectrum of the assembly. The other five experiments (Experiments 6-10) will be similar to the five baseline experiments, except that a tantalum layer will be placed next to each plutonium plate layer, thus diluting the stack and allowing for tests of the neutron cross section for tantalum. (authors)
This dissertation demonstrates the first of its kind distributed magnetic field sensor based on a fiber optic distributed acoustic sensing (DAS) scheme. Ferromagnetic nickel and Metglas® were dispersed internally within a fiber optic preform and then drawn on an in-house fiber optic draw tower to lengths in the kilometers. Due to the close proximity of the ferromagnetic metals and fiber optic core, the magnetostrictive strain response of the ferromagnetic materials when exposed to a magnetic field would perturbate within the fiber cladding and transfer that strain, internally, to the fiber optic core. Strain resulting from the magnetostrictive effect allows the DAS based sensor to accurately translate strain into readable magnetic field data. Due to the high sensitivity seen in this sensor design, multiparameter sources, acoustic and magnetic fields, were tested and validated and a three dimensional magnetic-field vector sensor was proposed. Numerical analysis of the novel sensor design was first implemented using COMSOL Multiphysics, where inputs such as magnetostrictive element shape, size, distance, and number were first investigated. Upon optimizing system constraints, the sensor design was further modified such that single mode operation was consistent across multiple fiber draws while retaining high strain transfer from the ferromagnetic elements to the fiber optic core. Ferromagnetic material selection was evaluated as a function of the saturation magnetostriction constants and a total of 4 modules were used to fully characterize the complex physics involved in this sensor design. All fabrication and testing were performed in-house using a full scale 3-story fiber draw tower and custom environmental testing stations to imitate naturally occurring events such as magnetic or acoustic point sources. A unique stacking method was used to embed ferromagnetic nickel and Metglas® into a fiber optic preform which when combined with a custom fiber draw process resulted in consistent multi-material fibers drawn to lengths of 1-km. In-house testing facilities included different types of electromagnetic generators, in addition to a soil test bed, and an outdoor test bed which allowed 100 meters of fiber to be tested simultaneously. All tested sensors demonstrated high strain transfer capabilities on the order of 0.01-10 μϵ depending on the materials used, ferromagnetic rod number, and core to metal spacing. Due to the sensitivity of the system the difference between AC and DC was distinct, and directional magnetostriction was studied. Transverse and longitudinal magnetic wave propagation was controlled through a solenoid and rectangular Helmholtz coil, both built in-house. A three-dimensional magnetic field vector sensor was proposed due to the success of the magnetic field sensor, and a design was proposed and initially tested to validate direction as a function of field strength and distance. To summarize, this dissertation explores the first fully distributed magnetic field sensor using DAS based techniques and one of the first multi-material fiber draw processes which can produce consistent single mode fiber up to 1-km. Due to extensive FEA modeling, multiple iterations of the magnetic sensor were fully characterized and an equation describing the relationship between sensor design and strain transfer has been created and validated experimentally. Multi-parameter tests including acoustic and magnetic fields were implemented and an algorithm was developed to separate the mixed signals. Finally, a test was performed to demonstrate the feasibility of sensing magnetic fields directionally. Cumulative results demonstrate a high-quality sensor alternative to current designs which may surpass other magnetic sensors due to innate multi-parameter capabilities, in addition to the inexpensive production cost and extremely long operating lengths.
The on-going AMMON program in EOLE reactor at CEA Cadarache (France) provides experimental results to qualify the HORUS-3D/N neutronics calculation scheme used for the design and safety studies of the new Material Testing Jules Horowitz Reactor (JHR). This paper presents the determination of technological and nuclear data uncertainties on the core reactivity and the propagation of the latter from the AMMON experiment to JHR. The technological uncertainty propagation was performed with a direct perturbation methodology using the 3D French stochastic code TRIPOLI4 and a statistical methodology using the 2D French deterministic code APOLLO2-MOC which leads to a value of 289 pcm (1{sigma}). The Nuclear Data uncertainty propagation relies on a sensitivity study on the main isotopes and the use of a retroactive marginalization method applied to the JEFF 3.1.1 {sup 27}Al evaluation in order to obtain a realistic multi-group covariance matrix associated with the considered evaluation. This nuclear data uncertainty propagation leads to a K{sub eff} uncertainty of 624 pcm for the JHR core and 684 pcm for the AMMON reference configuration core. Finally, transposition and reduction of the prior uncertainty were made using the Representativity method which demonstrates the similarity of the AMMON experiment with JHR (the representativity factor is 0.95). The final impact of JEFF 3.1.1 nuclear data on the Begin Of Life (BOL) JHR reactivity calculated by the HORUS-3D/N V4.0 is a bias of +216 pcm with an associated posterior uncertainty of 304 pcm (1{sigma}). (authors)
In this work, we present a new X-band waveguide (WR90) measurement method that permits the broadband characterization of the complex permittivity for low dielectric loss tangent material specimens with improved accuracy. An electrically long polypropylene specimen that partially fills the cross-section is inserted into the waveguide and the transmitted scattering parameter (S{sub 21}) is measured. The extraction method relies on computational electromagnetic simulations, coupled with a genetic algorithm, to match the experimental S{sub 21} measurement. The sensitivity of the technique to sample length was explored by simulating specimen lengths from 2.54 to 15.24 cm, in 2.54 cm increments. Analysis of our simulated data predicts the technique will have the sensitivity to measure loss tangent values on the order of 10{sup −3} for materials such as polymers with relatively low real permittivity values. The ability to accurately characterize low-loss dielectric material specimens of polypropylene is demonstrated experimentally. The method was validated by excellent agreement with a free-space focused-beam system measurement of a polypropylene sheet. This technique provides the material measurement community with the ability to accurately extract material properties of low-loss material specimen over the entire X-band range. This technique could easily be extended to other frequency bands.
We present images of solar wind electron density structures at distances of 1 AU, extracted from the STEREO/HI-2 data. Collecting the images requires separating the Thomson-scattered signal from the other background/foreground sources that are 10{sup 3} times brighter. Using a combination of techniques, we are able to generate calibrated imaging data of the solar wind with sensitivity of a few x 10{sup -17} B{sub sun}, compared to the background signal of a few x 10{sup -13} B{sub sun}, using only the STEREO/HI-2 Level 1 data as input. These images reveal detailed spatial structure in coronal mass ejections (CMEs) and the solar wind at projected solar distances in excess of 1 AU, at the instrumental motion-blur resolution limit of 1{sup 0}-3{sup 0}. CME features visible in the newly reprocessed data from 2008 December include leading-edge pileup, interior voids, filamentary structure, and rear cusps. 'Quiet' solar wind features include V-shaped structures centered on the heliospheric current sheet, plasmoids, and 'puffs' that correspond to the density fluctuations observed in situ. We compare many of these structures with in situ features detected near 1 AU. The reprocessed data demonstrate that it is possible to perform detailed structural analyses of heliospheric features with visible light imagery, at distances from the Sun of at least 1 AU.
Buildings consume more than 40% of primary energy in the U.S. Malfunctioning sensors, components, and control systems, as well as degrading components in Heating, Ventilating and Air-conditioning (HVAC) and lighting systems are main reasons for energy waste and unsatisfactory indoor environment. Field studies have shown that an energy saving of 5-30% of total building energy consumption and improved indoor air quality can be achieved by simply applying automated fault detection and diagnosis (AFDD), followed by corrections even if these are not done in real time. Extensive research has been made on the development of component level AFDD tools in the past two decades. However, in recent years, the development of method for a whole building level AFDD has received much attention. Here, a whole building fault refers to a fault happening in one subsystem but impact on more than one subsystems, or has a significant impact on building performances, such as building’s energy consumption. Existing component level AFDD tools could fail to detect or give false alarm for faults that trigger abnormalities in multiple subsystems. Isolating such whole building faults, which have impacts on multiple subsystems, is also challenging by simply using component based AFDD solutions. On the other hand, it might be more cost-effective for medium- or small-sized commercial buildings that have subsystems (e.g. primary cooling subsystem, air loop subsystem, heating subsystem, lighting subsystem, etc.) to install one whole building level AFDD tool, rather than many component level AFDD tools, to focus on significant faults. The focus of this project is firstly to provide training opportunities in building AFDD research area for undergraduate students and to develop a workforce pipeline in building sciences. The objective of the proposed research activities is to develop cost-effective and scalable AFDD solutions for whole building level faults. The developed AFDD solution is VOLTTRONTM compatible to further increase its plug-n-play capacity and the market penetration. VOLTTRONTM is an open-source innovative distributed control and sensing software platform developed by the Pacific Northwest National Laboratory. A VOLTTRONTM compatible AFDD tool brings the benefits such as low-cost deployment, and better building to grid integration, etc. The performance of the developed whole building AFDD tools is evaluated using data collected from a mixed-use medium-sized university campus building. Another significant goal of this project is to engage undergraduate students in research activities and expose them to building control and AFDD fields. A demonstration building – Nesbitt Hall at Drexel University is identified for this study. This demonstration building has a typical HVAC system configuration, which includes a water-cooled chiller system, three variable air volume (VAV) air handling unit (AHU) systems, and a hydronic heating system. Faults, that are expected to have a whole building level impact, are artificially implemented in this demonstration building for three different seasons. Building data have been collected in this project, which include fault free building automation system (BAS) data and BAS data that contain system behaviors caused by artificially implemented and naturally occurred faults. These collected data are used to evaluate the developed whole building AFDD tools. A data-driven method, which includes a weather and schedule-based pattern matching (WPM) method and Feature based Principal Component Analysis (FPCA) method, is developed for whole building level fault detection. Parameter sensitivity tests, including snapshot window size, data sample searching pool size, etc., are implemented to evaluate the impacts of various WPM-FPCA parameters. A data-driven and expert knowledge/rule-based method using Bayesian Network (BN) and WPM is developed for whole building level fault diagnosis. The developed WPM-BN method, which includes a two-layer BN structure model and BN parameters, are either learned from baseline data or developed from expert knowledge. The developed whole building AFDD tools are evaluated using BAS data collected from the demonstration building. Using the evaluation data set, the WPM-FPCA fault detection method is evaluated under two different Principle Component (PC) retention rates, i.e., 0.65 retention rate and 0.95 retention rate. It is observed that when using 0.65 PC retention rate, the WPM-FPCA fault detection method achieves a 79% fault detection rate (this rate reaches to 85% when including the six make-up fault test cases discussed in the next bullet), while when using 0.95 PC retention rate, the WPM-FPCA fault detection method achieves 100% fault detection rate (this rate remains to be 100% when including the six make-up fault test cases). Under both PC retention rates, the WPM-FPCA fault detection method demonstrates 0% false alarm rates. Using the evaluation data set, the developed WPM-BN fault diagnosis method has successfully diagnosed thirteen (13) faults out of the fourteen (14) fault test cases. The one mis-diagnosed case exhibits fewer fault symptoms in different subsystems, when compared with other fault test cases. Overall speaking, the developed whole building AFDD solutions demonstrate satisfactory fault detection/diagnosis accuracy with very low false alarm rate. Lastly, a survey and market study has been performed to understand the existing AFDD market, including its gaps and needs.
The present paper deals with the description of the salient features of three independent approaches for estimating uncertainties associated with predictions of complex system codes. The first approach is the 'standard' one and the most used at the industrial level: it is based upon the selection of input uncertain parameters, on assigning related ranges of variations and, possibly, PDF (Probability Density Functions) and on performing a suitable number of code runs to get the combined effect of variation on the results. In the second approach the uncertainty derives from the comparison between relevant measured data and results of corresponding code calculations. The third approach is based on the Bayesian inference technique and on the availability of experimental data by which computer model predictions can be improved and the ranges of variation of (in theory) 'all' input parameters can be characterized. More details are provided in respect with the third approach that has been named CASUALIDAD (Code with the capability of Adjoint Sensitivity and Uncertainty Analysis by Internal Data Adjustment and assimilation). (authors)
This report summarizes the seismic deployment of Lawrence Livermore National Laboratory (LLNL) Geotech GS-13 short-period seismometers at the Newberry Enhanced Geothermal System (EGS) Demonstration site located in Central Oregon. This Department of Energy (DOE) demonstration project is managed by AltaRock Energy Inc. AltaRock Energy had previously deployed Geospace GS-11D geophones at the Newberry EGS Demonstration site, however the quality of the seismic data was somewhat low. The purpose of the LLNL deployment was to install more sensitive sensors which would record higher quality seismic data for use in future seismic studies, such as ambient noise correlation, matched field processing earthquake detection studies, and general EGS microearthquake studies. For the LLNL deployment, seven three-component seismic stations were installed around the proposed AltaRock Energy stimulation well. The LLNL seismic sensors were connected to AltaRock Energy Gueralp CMG-DM24 digitizers, which are powered by AltaRock Energy solar panels and batteries. The deployment took four days in two phases. In phase I, the sites were identified, a cavity approximately 3 feet deep was dug and a flat concrete pad oriented to true North was made for each site. In phase II, we installed three single component GS-13 seismometers at each site, quality controlled the data to ensure that each station was recording data properly, and filled in each cavity with native soil.
Based on the MAJORANA DEMONSTRATOR (MJD) simulations task group calculations, the copper used in the inner shield and detector components require purity levels of <0.3 µBq 238 U/kg Cu and <0.3 µBq 232 Th/kg Cu. The MAJORANA Collaboration is endeavoring to achieve this goal by electroforming copper using ultra-clean materials in facilities at PNNL and SURF. In this document, a broadly accepted U.S. Environmental Protection Agency method is used to evaluate an ion exchange technique, developed at PNNL, for determining sensitivity in the assay of copper for trace levels of thorium and uranium. These data indicate that, in all cases, the assay sensitivity and material limits are being met.
TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with a Transcription Factor (TF)-gene regulatory network (TRN), which is modeled via a Bayesian network (BN). In this paper, we focus on sensitivity analysis of metabolic flux prediction for uncertainty quantification of BN structures for TRN modeling in TRIMER. We propose a computational strategy to construct the uncertainty class of TRN models based on the inferred regulatory order uncertainty given transcriptomic expression data. With that, we analyze the prediction sensitivity of the TRIMER pipeline for the metabolite yields of interest. The obtained sensitivity analyses can guide Optimal Experimental Design (OED) to help acquire new data that can enhance TRN modeling and achieve specific metabolic engineering objectives, including metabolite yield alterations. Here we have performed small- and large-scale simulated experiments, demonstrating the effectiveness of our developed sensitivity analysis strategy for BN structure learning to quantify the edge importance in terms of metabolic flux prediction uncertainty reduction and its potential to effectively guide OED.
With increasing demand on accuracy of criticality calculations, correlations between benchmark experiments due to system parameter uncertainties become of interest in bias determination. The impact of different interpretations of system parameter uncertainties on the calculation of covariances and correlations of k{sub eff} is discussed in this article. Following the suggestion of the OECD/NEA EGUACSA Benchmark phase IV [1], 21 experiments from the ICSBEP international Handbook of Evaluated Criticality Safety Benchmarks [2] are used for this analysis (LEU-COMP-THERM series 07, exp. 01-04 and 39, exp. 01-17). The experiments share certain assembly and fuel features and were carried out in the same lab. Therefore, correlations in the calculation of k{sub eff} appear. Correlation coefficients between experiments due to nuclear data uncertainties are calculated with TSUNAMI [3] and show high values for most experiments. For the correlation analysis due to system parameter uncertainties mainly two scenarios are considered: In scenario A all uncertain parameters are varied mutually for all fuel rods, representing a systematic deviation of the actual experimental setup from the design value. This analysis is performed for all experiments listed above. In scenario E certain parameters like the outer cladding diameter are varied for each fuel rod individually, representing a random scattering of the varied parameter. Scenarios B, C and D represent intermediate scenarios between A and E, which are discussed shortly. Uncertainty and sensitivity calculations of k{sub eff} on the uncertain experimental parameters based on Monte Carlo sampling are presented and discussed. The calculations were performed with SUnCISTT (Sensitivities and Uncertainties in Criticality Inventory and Source Term Tool [4]) and SCALE 6.1.2 [3]. For the 21 EGUACSA proposed experiments the outer cladding diameter is the leading effect for the uncertainty of k{sub eff} for scenario A. In contrast, for scenario E the impact of the cladding diameter on k{sub eff} cancels out due to rod wise variations leaving the fuel diameter as the leading effect. The correlation analysis based on system parameter uncertainties indicates a significant dependence of the correlation coefficients on the interpretation of the uncertainties. It shows high values for scenario A, if the neutronic features are similar (EALF, H/U). For scenario E the overall correlations are significantly smaller and variations between experiments decrease. The impact of the determined correlations on bias calculations of application cases will be discussed by the authors in the accompanying paper 'Impact of correlated data in validation procedures'. (authors)
This submission contains datasets and a final manuscript associated with a project simulating carbon dioxide push-pull into a conjugate fault system modeled after Dixie Valley- sensitivity analysis of significant parameters and uncertainty prediction by data-worth analysis. Datasets include: (1) Forward simulation runs of standard cases (push & pull phases), (2) Local sensitivity analyses (push & pull phases), and (3) Data-worth analysis (push & pull phases).
We present strategies to search for heavy neutral Higgs bosons decaying to top quark pairs, as often occurs at low tan β in type II two Higgs doublet models such as the Higgs sector of the MSSM. The resonant production channel is unsatisfactory due to interference with the SM background. We instead propose to utilize same-sign dilepton signatures arising from the production of heavy Higgs bosons in association with one or two top quarks and subsequent decay to a top pair. We find that for heavier neutral Higgs bosons the production in association with one top quark provides greater sensitivity than production in association with two top quarks. We obtain current limits at the LHC using Run I data at 8 TeV and forecast the sensitivity of a dedicated analysis during Run II at 14 TeV. Then we perform a detailed BDT study for the 14 TeV LHC and a future 100 TeV collider.
DNA repair, in particular, DNA double-strand break (DSB) repair, is essential for the survival of both normal and cancer cells. An elaborate repair mechanism has been developed in cells to efficiently repair the damaged DNA. The pathways predominately involved in DSB repair are homologous recombination and classic nonhomologous end-joining, although the alternative NHEJ pathway, a third DSB repair pathway, could also be important in certain contexts. The protein of BRCA1 encoded by the tumor suppressor gene BRCA1 regulates all DSB repair pathways. Given that DSBs represent the most biologically significant lesions induced by ionizing radiation and that impaired DSB repair leads to radiation sensitivity, it has been expected that cancer patients with BRCA1 mutations should benefit from radiation therapy. However, the clinical data have been conflicting and inconclusive. We provide an overview about the current status of the data regarding BRCA1 deficiency and radiation therapy sensitivity in both experimental models and clinical investigations. In addition, we discuss a strategy to potentiate the effects of radiation therapy by poly(ADP-ribose) polymerase inhibitors, the pharmacologic drugs being investigated as monotherapy for the treatment of patients with BRCA1/2 mutations.