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At least 793 records · Page 44

Compiled Groundwater Chemistry Data and Identified Mineralogy for the Portland Basin CRBG Aquifer System as part of DDU Feasibility Study

Groundwater Chemistry data for the Portland Basin was compiled from published literature, as well as state and federal groundwater quality reports. Mineralogies were identified based on previous literature, as well as XRD and SEM analysis conducted at Portland State University. Uploaded data sets include the compiled data on Portland and Tualatin Basin hydrogeology, and corresponding hydrogeochemical analyses.

15 GEOTHERMAL ENERGY↗

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗

Small RNA sequencing in cells and exosomes identifies eQTLs and 14q32 as a region of active export

Exosomes are small extracellular vesicles that carry heterogeneous cargo, including RNA, between cells. Increasing evidence suggests that exosomes are important mediators of intercellular communication and biomarkers of disease. Despite this, the variability of exosomal RNA between individuals has not been well quantified. To assess this variability, we sequenced the small RNA of cells and exosomes from a 17-member family. Across individuals, we show that selective export of miRNAs occurs not only at the level of specific transcripts, but that a cluster of 74 mature miRNAs on chromosome 14q32 is massively exported in exosomes while mostly absent from cells. We also observe more interindividual variability between exosomal samples than between cellular ones and identify four miRNA expression quantitative trait loci shared between cells and exosomes. Lastly, our findings indicate that genomically colocated miRNAs can be exported together and highlight the variability in exosomal miRNA levels between individuals as relevant for exosome use as diagnostics.

59 BASIC BIOLOGICAL SCIENCES↗

Identifying rhenium substitute candidate multiprincipal-element alloys from electronic structure and thermodynamic criteria

While rhenium has proven to be an ideal material in fast-cycling high-temperature applications such as rocket nozzles, its prohibitive cost limits its continued use and motivates a search for viable cost-effective substitutes. We show that a simple design principle that trades off average valence electron count and cost considerations proves helpful in identifying a promising pool of candidate substitute alloys: The Mo–Ru–Ta–W quaternary system. We demonstrate how this picture can be combined with a computational thermodynamic model of phase stability, based on high-throughput ab initio calculations, to further narrow down the search and deliver alloys that maintain rhenium’s desirable hcp crystal structure. Here, this thermodynamic model is validated with comparisons to known binary phase diagram sections and corroborated by experimental synthesis and structural characterization demonstrating multiprinciple-element hcp solid-solution samples selected from a promising composition range.

36 MATERIALS SCIENCE↗

Genome, transcriptome and secretome analyses of the antagonistic, yeast-like fungus Aureobasidium pullulans to identify potential biocontrol genes

Aureobasidium pullulans is an extremotolerant, cosmopolitan yeast-like fungus that successfully colonises vastly different ecological niches. The species is widely used in biotechnology and successfully applied as a commercial biocontrol agent against postharvest diseases and fireblight. However, the exact mechanisms that are responsible for its antagonistic activity against diverse plant pathogens are not known at the molecular level. Thus, it is difficult to optimise and improve the biocontrol applications of this species. As a foundation for elucidating biocontrol mechanisms, we have de novo assembled a high-quality reference genome of a strongly antagonistic A. pullulans strain, performed dual RNA-seq experiments, and analysed proteins secreted during the interaction with the plant pathogen Fusarium oxysporum. Based on the genome annotation, potential biocontrol genes were predicted to encode secreted hydrolases or to be part of secondary metabolite clusters (e.g., NRPS-like, NRPS, T1PKS, terpene, and β-lactone clusters). Transcriptome and secretome analyses defined a subset of 79 A. pullulans genes (among the 10,925 annotated genes) that were transcriptionally upregulated or exclusively detected at the protein level during the competition with F. oxysporum. These potential biocontrol genes comprised predicted secreted hydrolases such as glycosylases, esterases, and proteases, as well as genes encoding enzymes, which are predicted to be involved in the synthesis of secondary metabolites. This study highlights the value of a sequential approach starting with genome mining and consecutive transcriptome and secretome analyses in order to identify a limited number of potential target genes for detailed, functional analyses.

transcriptome↗

Peripheral Blood Transcript Signatures after Internal 131 I-mIBG Therapy in Relapsed and Refractory Neuroblastoma Patients Identifies Early and Late Biomarkers of Internal 131 I Exposures

131 I-metaiodobenzylguanidine ( 131 I-mIBG) is a targeted radiation therapy developed for the treatment of advanced neuroblastoma. We have previously shown that this patient cohort can be used to predict absorbed dose associated with early 131 I exposure, 72 h after treatment. We now expand these studies to identify gene expression differences associated with 131 I-mIBG exposure 15 days after treatment. Total RNA from peripheral blood lymphocytes was isolated from 288 whole blood samples representing 59 relapsed or refractory neuroblastoma patients before and after 131 I-mIBG treatment. We found that several transcripts predictive of early exposure returned to baseline levels by day 15, however, selected transcripts did not return to baseline. At 72 h, all 17 selected pathway-specific transcripts were differentially expressed. Transcripts CDKN1A (P < 0.000001), FDXR (P < 0.000001), DDB2 (P < 0.000001), and BBC3 (P < 0.000001) showed the highest up-regulation at 72 h after 131 I-mIBG exposure, with mean log2 fold changes of 2.55, 2.93, 1.86 and 1.85, respectively. At day 15 after 131I-mIBG, 11 of the 17 selected transcripts were differentially expressed, with XPC, STAT5B, PRKDC, MDM2, POLH, IGF1R, and SGK1 displaying significant up-regulation at 72 h and significant down-regulation at day 15. Interestingly, transcripts FDXR (P = 0.01), DDB2 (P = 0.03), BCL2 (P = 0.003), and SESN1 (P < 0.0003) maintained differential expression 15 days after 131 I-mIBG treatment. These results suggest that transcript levels for DNA repair, apoptosis, and ionizing radiation-induced cellular stress are still changing by 15 days after 131 I-mIBG treatment. Our studies showcase the use of biodosimetry gene expression panels as predictive biomarkers following early (72 h) and late (15 days) internal 131 I exposure. Our findings also demonstrate the utility of our transcript panel to differentiate exposed from non-exposed individuals up to 15 days after exposure from internal 131 I.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Identifying Direct SP -Converted Waves Constrains Local Induced Earthquake Depths

Abstract Seismicity in southern Kansas and northern Oklahoma in the past decade has been associated with fluid injections. In southcentral Kansas, the Wellington earthquake catalog is primarily composed of local, low-magnitude events. Approximately 22% of recorded earthquakes over a 2.5 yr period exhibit a seismic phase arriving between the direct P phase and direct S phase with particle motion similar to the P wave. This intermediate phase was identified as an S to P conversion (SP phase) occurring in the sedimentary rocks instead of the hypothesized basement to sedimentary section transition. We exploit the SP-converted phases to improve the depth accuracy of shallow earthquakes and to constrain VP/VS. The revised depth calculations further confirm that these local induced earthquakes are occurring in the shallow crystalline basement, below the sedimentary section in which fluids are injected.

Geochemistry & Geophysics↗

Identifying Downtime Sources in CEBAF SRF Linac Systems for Improving Its Reliability

In this work, we will present some recent analysis of the reliability statistics of the CEBAF SRF linac systems. Based on the data collected by the existing Down Time Manager (DTM), the year-to-year downtime evolution trend of linac zones over the six-year period from FY18 to FY23 is established. An in-depth downtime analysis at a resolution beyond the linac zone level was carried out by introducing a new system hierarchy, consisting of the SRF linac sub-systems and components. This new paradigm was implemented in a pilot downtime study over the two-month period of CEBAF operation from 9/13/23 to 11/13/23, enabling localization of the responsible sub-systems (SRF, HPRF, LLRF, Beamline vacuum, Cryogenics, etc.) and hardware components (cavity, tuner, RF coupler, etc.) in the CEBAF SRF linac systems. Pinpointing downtime sources over long operation periods at the sub-systems and component levels holds the key to improving the CEBAF SRF systems reliability. It also helps identify areas of SRF technology development needed by future high-power high-reliability CW SRF linacs.

Hryhorenko, Oleksandr↗

Use of a New Analytical Model To Match Production Data and Identify Opportunities To Maximize Well Productivity in the Tuscaloosa Marine Shale Reservoir

The low productivity of the oil wells in the Tuscaloosa Marine Shale (TMS) Trend, located in Louisiana and Mississippi, is a mystery. Production data from 55 wells in the TMS Trend were analyzed to identify possible means of enhancing well productivity. The -1/2 slope in a log–log plot for reservoir linear flow (RLF) was observed for some wells, but not all, and the -1 slope for boundary–dominated flow (BDF) has not been seen in the past 5 years of production. The behavior of the TMS wells is attributed to the ultralow permeability of the TMS matrix and the decline of fracture conductivity, both of which delay the BDF. On the basis of the concept of the distance of investigation, derived from the radius–of–investigation concept, the matrix permeability of the seven TMS wells was estimated to be between 34 and 65 nd, with an average of 51 nd. A new mathematical model for production decline of multifractured horizontal wells was developed taking into consideration the time–dependent fracture conductivity during the BDF period. This model fits TMS–well production data, with an average error of 6.12% and an R2 value of 0.96. Assuming constant matrix permeability, fitting the new model to the production data in the BDF period gives a rate of fracture–conductivity decline of between 0.20 and 0.74% per month. The new mathematical model reveals opportunities to optimize well completion to enhance well productivity in the TMS Trend. For a given amount of fracture proppant allocated to a well, the shortest possible fracture spacing should be used to maximize well productivity. If the number of fractures is fixed as a constraint of well completion design, well productivity is inversely proportional to the square root of fracture spacing (i.e., if the fracture spacing is shortened by fourfold, well productivity is expected to double). If the horizontal wellbore length is fixed as a constraint of well completion, well productivity is inversely proportional to fracture spacing (i.e., if the fracture spacing is shortened by 50%, well productivity is expected to double).

Engineering↗

Feasibility Study to Identify Potential Reductions in Energy Use in Tribal Buildings

Under this project, the Confederated Salish and Kootenai Tribes (CSKT) assessed the technical and economic feasibility of energy efficiency improvements to existing Tribally-owned buildings. The feasibility study followed a systematic approach in identifying, selecting, and ranking recommended measures, recognizing that the appropriateness of a measure would depend not only on technical issues but also on institutional and organizational issues, such as financing options and occupant requirements. The completed study provided the Tribes with the information needed to commit necessary resources to reduce the energy use and cost in approximately 40 Tribal buildings, including the changes that may be needed in each facility’s operation and maintenance and personnel requirements. It also presented an economic analysis of energy-efficiency capital improvements and an annotated list of financing options and possible funding sources for implementation and an overall strategy for implementation. This project was located in various Tribal communities located throughout the Flathead Indian Reservation in Western Montana. Notice: The following is a compilation of Annual Program Review Presentations, Award Modifications, and Quarterly Progress Reports submitted to the Department of Energy’s (DOE) Office of Indian Energy Policy and Programs by the Confederated Salish and Kootenai Tribes under agreement DE-EE0005171. This report covers project activities from September 30, 2011 through December 31, 2014 and has been uploaded to OSTI by DOE as a substitute for the required Final Technical Report which was not received by DOE from the project recipient.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Using EMIS to Identify Top Opportunities for Commercial Building Efficiency

Energy Management and Information Systems (EMIS) comprise a broad family of tools and services to manage commercial building energy use. These technologies offer a mix of capabilities to store, display, and analyze energy use and system data, and in some cases, provide control. EMIS technologies enable 10–20 percent site energy savings in best practice implementations. Energy Information System (EIS) and Fault Detection and Diagnosis (FDD) systems are two key technologies in the EMIS family. Energy Information Systems are broadly defined as the web-based software, data acquisition hardware, and communication systems used to analyze and display building energy performance. At a minimum, an EIS provides daily, hourly or sub-hourly interval meter data at the whole-building level, with graphical and analytical capability. Fault Detection and Diagnosis systems automatically identify heating, ventilation, and air-conditioning (HVAC) system or equipment-level performances issues, and in some cases are able to isolate the root causes of the problem. They use computer algorithms to continuously analyze system-level operational data to detect faults and diagnose their causes. Many FDD tools integrate the trend log data from a Building Automation System (BAS) but otherwise are stand-alone software packages; other types of FDD tools are implemented as “on-board” equipment-embedded diagnostics. (This document focuses on the former.) Analysis approaches adopted in FDD technologies span a variety of techniques from rule-based methods to process history-based approaches. FDD tools automate investigations that can be conducted via manual data inspection by someone with expert knowledge, thereby expanding accessibility and breath of analysis opportunity, and also reducing complexity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Milestone Report - M3FT-15OR03120213 - A Literature Survey to Identify Potentially Problematic Volatile Iodine-Bearing Species Present in Off-Gas Streams

Four radionuclides have been identified as being sufficiently volatile in the reprocessing of nuclear fuel that their gaseous release needs to be controlled to meet U.S. regulatory requirements (Jubin et al. 2011, 2012). These radionuclides are 3 H, 14 C, 85 Kr, and 129 I. Of these, 129 I has the longest half-life and potentially highest biological impact. Accordingly, control of the release of 129 I is most critical with respect to U.S. regulations for the release of radioactive material in stack emissions. Current U.S. Environmental Protection Agency regulation governing nuclear facilities (40 CFR 190) states that the total quantity of radioactive materials entering the general environment from the entire uranium fuel cycle, per gigawatt-year of electrical energy produced by the fuel cycle, must contain less than 5 mCi of 129 I. The study of inorganic iodide in off-gas systems has been almost exclusively limited to I 2 , and the focus of organic iodide studies has been CH 3 I.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Curvature Based Analysis to Identify and Categorize Trajectory Segments

Since the attacks carried out against the United States on September 11, 2001, which involved the commandeering of commercial aircraft, interest has increased in performing trajectory analysis of vehicle types not constrained by roadways or railways, i.e., aircraft and watercraft. Anomalous trajectories need to be automatically identified along with other trajectories of interest to flag them for further investigation. There is also interest in analyzing trajectories without a focus on anomaly detection. Various approaches to analyzing these trajectories have been undertaken with useful results to date. In this research, we seek to augment trajectory analysis by carrying out analysis of the trajectory curvature along with other parameters, including distance and total deflection (change in direction). At each point triplet in the ordered sequence of points, these parameters are computed. Adjacent point triplets with similar values are grouped together to form a higher level of semantic categorization. These categorizations are then analyzed to form a yet higher level of categorization which has more specific semantic meaning. This top level of categorization is then summarized for all trajectories under study, allowing for fast identification of trajectories with various semantic characteristics.

42 ENGINEERING↗

Identifying Suspect Instrument Intervals Using Midnight Noise Time Histories

With an intense work ethic, and high levels of devotion to their craft, seismologists continue to battle the elements and wrestle with complex logistics in their efforts to field instrumentation over the entire globe. We are fortunate to see data volumes accelerating in size, and quality continuing to improve; for example, universal timing issues can now be considered rare. However, instrument response issues are still common, and can hinder research that seeks to understand amplitudes of seismic wavefields. We are interested in using the accumulations of seismic data to develop models that will predict high frequency (0.2-20 Hz, and higher) signal amplitudes for explosion monitoring purposes over broad areas, which requires large data sets and extensive quality control. To identify response and station health issues, we have collected noise time histories for global seismic data, focusing on measurements near (but not restricted to) midnight to eliminate diurnal variations, and have manually determined time intervals that appear inconsistent with background behavior. We assign descriptive labels, but do not attempt to diagnose causes. We use these intervals to discard data. To date, we have examined 39,260 channels from 11,105 stations, heavily weighted toward IRIS holdings, dates through 2017 (depending on station, roughly the date we started our manual review), bands between 1 and 8 Hz, finding 24,733 anomalous time intervals. The great majority (90%) of these intervals appear to be shifts of constant offset, often bounded by times of known instrument changes, likely the result of poor documentation of response parameters at one of many stages between the field and the plotter. We hope these results can be of use to our colleagues, and would encourage community efforts to diagnose anomalous behavior, and fix poor responses. We also hope these results will support automation efforts, including application of supervised learning techniques.

47 OTHER INSTRUMENTATION↗

Using EMIS to Identify Top Opportunities for Commercial Building Efficiency

This guide presents an overview of the top energy-savings opportunities in commercial buildings and shows how they can be identified using the type of interval meter analytics offered in energy information system technologies or using the automated analytics offered in fault detection and diagnostics systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Machine learning to identify geologic factors associated with production in geothermal fields: A casestudy using 3D geologic data, Brady geothermal field, Nevada

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in the Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid flow pathways are relatively rare in the subsurface but are critical components of hydrothermal systems like Brady and many other types of fluid flow systems in fractured rock. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of fourteen 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate the macro-scale faults and a local step-over in the fault system preferentially occur along with production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate 1) the specific geologic controls on the Brady hydrothermal system and 2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

15 GEOTHERMAL ENERGY↗

Aging and Lifetimes Milestone 7777, G.C. #4: Assess the ability of MRI to identify chemical and mechanical heterogeneity in polymers at various length scales

Polysiloxane foams utilized for stockpile applications experience changes over time induced by exposure to thermal, radiative, and mechanical stresses. The interplay of these stresses can lead to chemical and/or physical changes in the polymer, such as compression set and material degradation over time. Understanding the mechanisms of material aging and identifying material degradation prior to failure are critical in maintaining the integrity of the nuclear stockpile. Our prior work using solid-state NMR spectroscopy has shown that we can observe signatures of thermal, radiative, and mechanical aging of silicone elastomers using differences in NMR parameters such as relaxation (T1 and T2). However, most of our measurements have been on bulk samples and have only provided an average aging behavior of each sample. Here, we have used magnetic resonance imaging (MRI) to provide relaxation-weighted images that are a metric of structural heterogeneity (cross-link density) in polymers across multiple length scales. In addition, the larger sample size that can be accommodated in animal MRI scanners has the potential to make the technique adaptable to detecting heterogeneities whole parts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗