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At least 145 records · Page 8

Automatic Analyte-Ion Recognition and Background Removal for Ambient Mass-Spectrometric Data Based on Cross-Correlation

Ambient mass spectrometry is a powerful approach for rapid, high-throughput, and direct sample analysis. Due to the open-air desorption and ionization processes, random fluctuations of ambient conditions can lead to large variances in mass-spectral signals over time. The mass-spectral data also can be further complicated due to multiple analytes present in the sample, background-ion signals stemming from the desorption/ionization source itself, and other laboratory-specific conditions (e.g., ambient laboratory air, nearby hardware). Thus, background removal and analyte-ion recognition can be quite difficult, particularly in non-targeted analyses. Here, we demonstrate the use of a cross-correlation-based approach to exploit chemical information encoded in the time domain to group/categorize mass-spectral peaks from a single analysis dataset. Ions that originate from ambient (or other) background species were readily flagged and removed from spectra; the result was a decrease in mass-spectral complexity by over 70% due to the removal of these background ions. Meanwhile, analyte ions were differentiated and categorized based on their time-domain profiles. With sufficient mass resolving-power and mass-spectral acquisition rate, isolated mass spectra containing ions from the same species in a sample could be extracted, leading to a reduction in mass-spectral complexity by more than 98% in some cases. The cross-correlation approach was tested with different ionization sources as well as reproducible and irreproducible sample introduction. Software built in-house enabled fully automated data processing, which can be performed within a few seconds. Ultimately, this approach provides an additional dimension of analyte separation in ambient mass-spectrometric analyses with information that is already recorded throughout the analysis. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Documenting 15 Years of Reductions in U.S. Solar Photovoltaic System Costs

The U.S. Department of Energy's (DOE) Solar Energy Technologies Office (SETO) has played a key role in reducing PV system costs by supporting essential and high-impact research, development, and deployment (RD&D) activities. SETO's efforts go beyond improving technology and hardware innovations to tackle soft costs like installation labor, permitting, and customer acquisition. This holistic focus ensures that solar energy remains a viable, scalable solution for combating climate change and achieving the nation's clean energy goals. This National Renewable Energy Laboratory's (NREL) report highlights over a decade of transformative advancements in PV system technology and its cost reductions from 2010 to 2024, documenting a remarkable trajectory in line with the goals set forth by SETO. By analyzing benchmark configurations across different photovoltaic (PV) sectors over years, this work provides industry stakeholders with a comprehensive understanding of cost trends and their impact on Levelized Cost of Energy (LCOE) targets established under the 2010 SunShot Initiative.

14 SOLAR ENERGY↗

Demonstration and Feasibility Analyses of Using the Dual-Purpose Canister Drain Pipe to Support the Filling Process

This work documents experiments that are being used to determine the feasibility of filling dual-purpose canisters (DPCs) using the existing drain pipe. Mercury was identified as a surrogate filler for the initial experiments. Oak Ridge National Laboratory’s Target Test Facility (TTF), which is a full-scale Spallation Neutron Source (SNS) prototypical mercury loop, is being used for the planned pipe experiments using mercury. The pipe experiments were divided into two phases to provide a separate effects approach to the problem and to allow for development of system scalability. The first phase included taking strain measurements in a short length pipe, as well as measurements of flow-induced vibration. The second phase consists of the design and construction of a separated mercury flow loop capable of hosting exchangeable test sections and more localized instrumentation. Data acquisition of Phase I was performed during this work and is presented in the form of strain measurements and vibration frequency.

Dominguez-Ontiveros, Elvis↗

Advancing \textit{otsdaq}: Enhancements for Usability, Accuracy, and Robustness

High-energy physics (HEP) experiments require data acquisition (DAQ) systems that can orchestrate complex detector operations, high data throughput, and responsive, real-time feedback to operators. Traditional DAQ stacks, which are often bespoke, command-line driven and highly specific, impose large learning curves on users. The Off-The-Shelf Data Acquisition (\textit{otsdaq}) framework was created to address these issues by offering a highly customizable and scalable browser-based ’desktop’ environment, in which experiment-specific control and monitoring applications can be easily deployed and integrated. Although the initial development of the \textit{otsdaq} software was aimed at the Fermilab Test Beam Facility, \textit{otsdaq} is now being leveraged for broader deployment, including the upcoming Mu2e experiment, where real-time monitoring of field-programmable gate array (FPGA)-based Data Transfer Controllers (DTCs), Clock and Fanout (CFO) boards, and several other subsystems are critical. We contribute a set of targeted improvements to \textit{otsdaq}: bitmap visualization functionality for configured data, improved and corrected delta-based DTC throughput metrics, version control (VC)-backed source navigation for console messages, custom navigation hooks to eliminate disruptive user interface glitches, and copy-to-clipboard support for macro execution history. These changes improve usability, reduce debugging time, and increase accuracy in performance data as Mu2e moves toward commissioning.

Mohammed, A. [Unlisted, US]↗

Sequential Bayesian Experimental Design for Calibration of Expensive Simulation Models

Simulation models of critical systems often have parameters that need to be calibrated using observed data. For expensive simulation models, calibration is done using an emulator of the simulation model built on simulation output at different parameter settings. Using intelligent and adaptive selection of parameters to build the emulator can drastically improve the efficiency of the calibration process. The article proposes a sequential framework with a novel criterion for parameter selection that targets learning the posterior density of the parameters. The emergent behavior from this criterion is that exploration happens by selecting parameters in uncertain posterior regions while simultaneously exploitation happens by selecting parameters in regions of high posterior density. Furthermore, the advantages of the proposed method are illustrated using several simulation experiments and a nuclear physics reaction model.

97 MATHEMATICS AND COMPUTING↗

Data from: "Snowmelt Timing Regulates Community Composition, Phenology, and Physiological Performance of Alpine Plants"

This archive contains data that were used to support conclusions drawn in “Snowmelt Timing Regulates Community Composition, Phenology, and Physiological Performance of Alpine Plants”, by Winkler et al., 2018. Data were collected throughout the 2009 growing season on Niwot Ridge, Colorado, before the site became part of the Alpine Treeline Warming Experiment (ATWE). Geospatial files are included in this archive to provide additional locational context. The files in this data package consist of five comma-separated-values (.csv) files, one keyhole markup language (.kml) file, and two ESRI shapefiles (.shp). The .csv files can be opened by Microsoft Excel, R, or any simple text-editor software, such as TextEdit (MacOS) or Notepad (Windows). The .kml files can be opened by Google Maps or Google Earth, and the .shp files are compatible with GIS softwares such as ESRI’s ArcGIS suite, and QGIS.------------------------------------------------------------------------------------------------------------------------------------------------------------------------------We asked how plant community composition, phenology, plant water relations, and photosynthetic gas exchange of alpine-restricted and wide-ranging species differ in their responses to a ca. 40-day snowmelt gradient in the Colorado Rocky mountains (Lewisia pygmaea, Sibbaldia procumbens, and Hymenoxys grandiflora were alpine-restricted and Artemisia scopulorum, Carex rupestris, and Geum rossii were wide-ranging species). To do this, we measured percent cover and flowering initiation across 20 plots varying in snowmelt timing and measured net photosynthesis and stomatal conductance in multiple individuals of each target species in these plots in 2009.As hypothesized, species richness and foliar cover increased with earlier snowmelt, due to a greater abundance of wide-ranging species present in earlier melting plots. Flowering initiation occurred earlier with earlier snowmelt for 12 out of 19 species analyzed, while flowering duration was shortened with later snowmelt for six species (all but one were wide ranging species). We observed >50% declines in net photosynthesis from July to September as soil moisture and plant water potentials declined. Early-season stomatal conductance was higher in wide-ranging species, indicating a more competitive strategy for water acquisition when soil moisture is high. Even so, there were no associated differences in photosynthesis or transpiration, suggesting no strong differences between these groups in physiology.

54 ENVIRONMENTAL SCIENCES↗

Key insights from US Department of Energy Better Plants workforce development bootcamps (2022–2025)

This study examines the effectiveness of the US Department of Energy’s Better Plants Program Bootcamps, which are designed to enhance participants’ technical skills in improving energy efficiency and optimizing operations in manufacturing facilities. Through the analysis of survey data collected from 529 participants across 9 bootcamps, the research investigates the motivations, benefits, and demographic trends of attendees. The findings reveal that skill acquisition and improvement are primary drivers for participation, with key benefits including hands-on training on diagnostic equipment and software tools, networking opportunities, and access to technical resources. The analysis shows strong participation from sectors characterized by high energy consumption and employment, such as chemical and transportation equipment manufacturing. Over 50% of participants have job titles that include “EHS” or “Energy” showing their key roles in leading energy efficiency and energy management efforts in manufacturing. Furthermore, the analysis highlights the distribution of participants across managerial, engineering, and technical roles, revealing a higher representation of managers and engineers. This observation suggests a need for targeted outreach to engage technicians, equipment operators, maintenance staff, and floor workers to ensure comprehensive workforce development. The post-bootcamp survey showed that the participants highly valued the opportunities for peer learning and idea exchange, and the benefits they gained from them. This research contributes to the advancement of manufacturing education by demonstrating the efficacy of specialized training in addressing critical industry challenges and fostering a more competent and empowered workforce.

Energy efficiency↗

Heat load measurements for the PIP-II pHB650 cryomodule

Phase-3 testing of the pHB650 cryomodule at the PIP-II Injector Test Facility was conducted to evaluate the effectiveness of heat load mitigations performed after earlier phases of testing and to continue pinpointing any sources of unexpectedly high heat loads.. The programme measured HTTS, LTTS, and 2 K isothermal/non-isothermal loads under "standard", "linac", and "simulated dynamic" operating modes, recording data both inside the cryomodule and across the bayonet can circuits. Thermal-acoustic oscillations were eliminated by replacing the original G10 cooldown-valve stem with a stainless-steel stem fitted with wipers. A newly developed Python script automated acquisition of ACNET data, performed real-time heat-load calculations, and generated plots and tables that were posted to the electronic logbook within minutes, vastly reducing manual effort and accelerating feedback between SRF and cryogenics teams. Analysis showed that JT heat-exchanger effectiveness and temperature stratification in the two-phase and relief piping strongly influence the observed loads and helped isolate sources of excess heat. The campaign demonstrates that rigorous pre-test planning, real-time diagnostics, and automated reporting can improve both accuracy and efficiency, providing a template for future PIP-II cryomodule tests and for implementing targeted heat-load mitigations.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.] (ORCID:↗

Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: - Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS system: i) Achieving sufficient injectivity to support high cross-well flow rates ii) Distributing flow evenly across the wellbore and reservoir to maximize heat mining efficiency, ensure sustained heat transfer, and mitigate thermal breakthrough iii) Overcoming the effects of stress heterogeneity, stress shadowing, and variations in natural fracture properties during the stimulation treatment, leading to a more predictable stimulated reservoir volume and offset well placement - The following activities will be performed: i) Design, plan, and execute a multistage plug-and-perf stimulation treatment at a Fervo site with data acquisition and well testing activities aimed at addressing key technical aspects of the issues above ii) Perform data processing and interpretation of field results to translate the results form the Fervo site to a site-specific design at the Utah FORGE site iii) Design, plan, and execute a multistage plug-and-perf stimulation treatment design at the Utah FORGE site Methods and Approach: - Design a detailed data acquisition plan to maximize learning around: i) DFIT testing ii) Petrophysical logging, image logging iii) Permanent DAS/DTS fiber optic monitoring iv) Deep borehole microseismic monitoring v) Shallow borehole induced seismicity monitoring vi) Injection/production testing (RTA analysis, tracer testing) vii) Integrated numerical modeling and production forecasting

15 GEOTHERMAL ENERGY↗

Leveraging computational genomics to understand the molecular basis of metal homeostasis

Genome-based data is helping to reveal the diverse strategies plants and algae use to maintain metal homeostasis. In addition to acquisition, distribution and storage of metals, acclimating to feast or famine can involve a wealth of genes that we are just now starting to understand. The fast-paced acquisition of genome-based data, however, is far outpacing our ability to experimentally characterize protein function. Computational genomic approaches are needed to fill the gap between what is known and unknown. To avoid misconstruing bioinformatically derived data, which is the root cause of the inaccurate functional annotations that plague databases, functional inferences from diverse sources and contextualization of that evidence with a robust understanding of protein family evolution is needed. Phylogenomic- and comparative-genomic-based studies can aid in the interpretation of experimental data or provide a spark for the discovery of a new function. These analyses not only lead to novel insight into a target protein's function but can generate thought-provoking insights across protein families.

59 BASIC BIOLOGICAL SCIENCES↗

Chemoproteogenomic stratification of the missense variant cysteinome

Abstract Cancer genomes are rife with genetic variants; one key outcome of this variation is widespread gain-of-cysteine mutations. These acquired cysteines can be both driver mutations and sites targeted by precision therapies. However, despite their ubiquity, nearly all acquired cysteines remain unidentified via chemoproteomics; identification is a critical step to enable functional analysis, including assessment of potential druggability and susceptibility to oxidation. Here, we pair cysteine chemoproteomics—a technique that enables proteome-wide pinpointing of functional, redox sensitive, and potentially druggable residues—with genomics to reveal the hidden landscape of cysteine genetic variation. Our chemoproteogenomics platform integrates chemoproteomic, whole exome, and RNA-seq data, with a customized two-stage false discovery rate (FDR) error controlled proteomic search, which is further enhanced with a user-friendly FragPipe interface. Chemoproteogenomics analysis reveals that cysteine acquisition is a ubiquitous feature of both healthy and cancer genomes that is further elevated in the context of decreased DNA repair. Reference cysteines proximal to missense variants are also found to be pervasive, supporting heretofore untapped opportunities for variant-specific chemical probe development campaigns. As chemoproteogenomics is further distinguished by sample-matched combinatorial variant databases and is compatible with redox proteomics and small molecule screening, we expect widespread utility in guiding proteoform-specific biology and therapeutic discovery.

Desai, Heta (ORCID:0000000343621707)↗

MLSPICE: Machine Learning based SPICE Modeling Platform for Power Magnetics

Electrical power converters are critical to a wide range of applications ranging from renewable integration to transportation electrification, and can be a key factor determining the size, weight, and efficiency of energy conversion systems. Magnetic components are typically the largest and least efficient components in power electronics. While there have been major strides in the modeling and analysis of power semiconductor devices and circuit simulations, the necessary advances in the design of power magnetics have lagged. In this project, we have transformed the modeling and design of power magnetics with machine learning enabled methods and catalyze simultaneous disruptive improvements for ML-based power electronics design tools. A fully automated open-source machine learning based magnetics modeling platform – the MagNet project - with innovations in full stack have been developed to greatly accelerate the design process and provide new insights to magnetic material and geometry design. The ARPA-E funded MagNet platform contains three major building blocks: 1) a ML-Integrated Data Acquisition System (MIDAS): a highly automated data acquisition testbed which is capable of measuring a large number of magnetic cores with a wide range of electrical circuit excitations; 2) a ML-integrated Core Loss Model (MICLM): a machine-learning trained modeling method for modeling the core loss and saturation effects of magnetic materials for arbitrary excitation waveforms; 3) ML-guided Magnetics SPICE Simulation Tool (PMSPICE): a fully integrated CAD tool which can simulate the magnetics in SPICE. It can help the designers to quickly model the linear and non-linear characteristics of magnetic components and evaluate their behavior in SPICE simulations. The developed MagNet system has fully demonstrated the proposed performance target and has been open sourced to the entire power electronics community to advance the modeling and design of power magnetics from many different angles.

36 MATERIALS SCIENCE↗

Framework for an adaptive integrated observation system using a hierarchy of machine learning approaches

Focal Area(s): 1. Data acquisition enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, and hardware-related efforts involving AI. 2. Insight gleaned from complex measurements using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI Science Challenge and Rationale: Atmospheric processes are stochastic, occur at scales from the micrometer to many kilometers, and are constantly changing over time. Characterizing these interactions and associated environmental conditions using traditional measurement techniques is difficult and can take years to build statistics on atmospheric phenomena that occurs episodically. Developing new innovative approaches to modify sampling strategies in real-time would enable the routine collection of targeted measurements focused on a specific set of science questions.

54 ENVIRONMENTAL SCIENCES↗

Final Report on the Phase II Physics Proposal for T-1063: The Accelerator Neutrino Neutron Interaction Experiment (ANNIE)

The goal of ANNIE is to make the first detailed measurement of the number of neutrons produced by neutrinos interacting with nuclei. This measurement is important for understanding the results of previous and planned neutrino experiments, as neutrons carry away energy from the neutrino interactions that must be accounted for in determining the energy and neutrino type. This effort is also focused on using a new photodetector technology and key target material enhancements to enable advanced water-based neutrino detectors. The ANNIE detector has been installed in the Booster Neutrino Beam at Fermilab, which provides a pulsed source of neutrinos in the energy range of 300-1200 MeV, which is relevant for the next generation of neutrino experiments. In 2017-2018 measurements of the neutron background in this beam were made with a partially-instrumented ANNIE detector. These measurements guided our design of the upgraded detector now built. The upgrade has been realized by adding Large Area Picosecond Photodetectors (LAPPDs) for the first time, more conventional photomultiplier tubes (PMTs), as well as adding electronics channels to the existing data acquisition system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comprehensive single-shot biophysical cytometry using simultaneous quantitative phase imaging and Brillouin spectroscopy

Abstract Single-cell analysis, or cytometry, is a ubiquitous tool in the biomedical sciences. Whereas most cytometers use fluorescent probes to ascertain the presence or absence of targeted molecules, biophysical parameters such as the cell density, refractive index, and viscosity are difficult to obtain. In this work, we combine two complementary techniques—quantitative phase imaging and Brillouin spectroscopy—into a label-free image cytometry platform capable of measuring more than a dozen biophysical properties of individual cells simultaneously. Using a geometric simplification linked to freshly plated cells, we can acquire the cellular diameter, volume, refractive index, mass density, non-aqueous mass, fluid volume, dry volume, the fractional water content of cells, both by mass and by volume, the Brillouin shift, Brillouin linewidth, longitudinal modulus, longitudinal viscosity, the loss modulus, and the loss tangent, all from a single acquisition, and with no assumptions of underlying parameters. Our methods are validated across three cell populations, including a control population of CHO-K1 cells, cells exposed to tubulin-disrupting nocodazole, and cells under hypoosmotic shock. Our system will unlock new avenues of research in biophysics, cell biology, and medicine.

Steelman, Zachary A.↗

Efforts to enhance reproducibility in a human performance research project

Background: Ensuring the validity of results from funded programs is a critical concern for agencies that sponsor biological research. In recent years, the open science movement has sought to promote reproducibility by encouraging sharing not only of finished manuscripts but also of data and code supporting their findings. While these innovations have lent support to third-party efforts to replicate calculations underlying key results in the scientific literature, fields of inquiry where privacy considerations or other sensitivities preclude the broad distribution of raw data or analysis may require a more targeted approach to promote the quality of research output. Methods: We describe efforts oriented toward this goal that were implemented in one human performance research program, Measuring Biological Aptitude, organized by the Defense Advanced Research Project Agency's Biological Technologies Office. Our team implemented a four-pronged independent verification and validation (IV&V) strategy including 1) a centralized data storage and exchange platform, 2) quality assurance and quality control (QA/QC) of data collection, 3) test and evaluation of performer models, and 4) an archival software and data repository. Results: Our IV&V plan was carried out with assistance from both the funding agency and participating teams of researchers. QA/QC of data acquisition aided in process improvement and the flagging of experimental errors. Holdout validation set tests provided an independent gauge of model performance. Conclusions: In circumstances that do not support a fully open approach to scientific criticism, standing up independent teams to cross-check and validate the results generated by primary investigators can be an important tool to promote reproducibility of results.

59 BASIC BIOLOGICAL SCIENCES↗

Pilot Study for Determining HVAC Fault Prevalence from Fault Monitoring Data

HVAC faults in U.S. commercial buildings are estimated to waste 0.7 quads of energy annually and many companies have deployed software at scale for fault detection and diagnosis (FDD). Yet the lack of comprehensive published data on fault prevalence makes it difficult for researchers, software developers, and building operators to target the most important types of faults and accelerate the widespread deployment of this technology. A multi-lab effort is underway to quantify the prevalence of commercial building HVAC faults. This paper describes initial analysis conducted on over 2-years of FDD data from 12 campus buildings to inform the methodology and data collection strategy of the full study. The analysis found a large variability in fault prevalence across different buildings, pieces of equipment, and fault types, many duplicate fault alarms, and challenges in validating faults with secondary data sources such as manually entered work order data. This paper also discusses the requirements for a successful full study, which necessitates the acquisition of a large, diverse dataset, from buildings that vary in end-use, climate region, and installed FDD software platform, as well as robust validation data easily linked to the FDD data. It is especially important to perform this analysis on data from multiple FDD providers and building owners to ensure that the results are agnostic to the software methodology used and building-specific settings. Future work will present the results of the full study, which will contain data from several different partner organizations, spanning a large proportion of U.S. climate zones.

Newman, Sarah F.↗

Oil and Natural Gas Development near and beneath Uranium Tailings Cells and Other Remediated Sites - 20358

DOE LM is responsible for maintaining remedies at more than 50 remediated sites that require active long-term surveillance and maintenance (LTS and M). Institutional controls (ICs) were established to limit human and environmental exposures to residual contamination by controlling land use, restricting access to potential hazards, and making the public aware of potential dangers from the residual contamination. ICs for each site were developed based on current and foreseeable conditions; however, these controls should evolve to mitigate potential human health and other environmental risks from unanticipated changes in activities or site conditions. Activities conducted beyond the DOE long-term care boundaries by non-DOE parties may impact the effectiveness of ICs or even the long-term stability of disposal cells and groundwater remedies. Several sites that LM manages or that will transfer to LM for LTS and M are in active oil and gas production basins. The sites are associated with uranium ore milling or nuclear test sites and have been remediated or are in the process of remediation and have no ongoing DOE mission. Particularly since 2005, hydraulic fracturing ('fracking') combined with directional drilling has dramatically increased oil and natural gas (oil/gas) production in the United States, now making it the number one hydrocarbon-producing country. Fracking has allowed production from shale and other rocks of low natural permeability that were historically not considered viable oil/gas resources. Also, because wellbores can now be drilled as many as 5 kilometers or more horizontally, hydrocarbons can be recovered from zones without having access to the surface above them. Drilling activity near Rulison, Colorado, the location of an underground nuclear detonation managed by LM, has raised public concerns that remnant radioactivity in the detonation zone could migrate to producing wells and enter the natural gas distribution system. At sites like the Falls City, Texas, Disposal site, transitioned to LM with a split estate, increased production in the region has resulted in wellbores beneath the long-term care boundary of the site. While the DOE license for Falls City was approved by the NRC in 1997 without the acquisition of the subsurface rights, NRC has raised concerns on whether this activity impacts the integrity of the cell and/or groundwater remedies. In Wyoming, LM is anticipating receiving the license for the Bear Creek site and manages the Spook site, both locations of uranium mill tailings disposal cells. These Wyoming sites are in an active region of major oil and gas development. This change in surrounding land use will require LM to work collaboratively with NRC to address these concerns. At several DOE sites radioactive waste, and often intermixed nonradioactive constituents, is permanently isolated in engineered disposal cells. At other sites, residual contamination can be present in groundwater, blast cavities, and infinite amounts within soil. Areas targeted for oil and gas development at the Texas and Wyoming sites range from depths of 2440 to 3350 meters (8000-11000 feet) below ground surface. When most site remedies were designed, oil and gas development was not considered to be an issue within the site boundary. With the more recent uses of directional drilling, fracking, and associated wastewater injections, the evaluative criteria for incoming sites and ICs for managing long-term protectiveness and regulatory compliance are changing. Although DOE surface ownership was previously thought to be a robust IC to prevent surface and subsurface development, particularly at disposal sites, that may no longer be the case. Whereas the subsurface development at Texas and Wyoming sites is currently occurring at thousands of meters beneath the surface, shallower and direct onsite development would be more of a concern for LM. The energy introduced when a well is hydraulically fractured causes microseismic events (magnitude -2 to 1.0) as the fractures propagate but does not directly cause seismic events (earthquakes) of sufficient magnitude to damage surface structures. Additionally, the extent of the hydraulic fractures is limited to the targeted depths, which are far below the surface. However, earthquakes of sufficient magnitude to damage surface structures have been attributed to the injection of wastewater into disposal wells. States that have experienced these effects have enacted regulations that limit the rate and pressures that wastewater can be injected into disposal wells. Items LM may consider are the need for monitoring the volume of water injected into nearby disposal wells and possibly installing seismic stations at sites most susceptible to damage. While the need to demonstrate that no impact from oil and gas extraction activities on a site groundwater remedy or disposal cells will vary from site to site, LM is assessing risk criteria for this activity. Though LM has not experienced an issue yet at a uranium tailings disposal site, it cannot assume that there will be none, and must address NRC concerns. LM is building on past experiences at other sites and beginning to form new processes with the hope that these concepts can be applied for other future sites. (authors)

04 OIL SHALES AND TAR SANDS↗