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A high gain, low noise corrugated feedhorn was designed and developed by JPL for use in Very Large Array (VLA) antennas, near Soccoro, New Mexico. The new feedhorn will enable the VLA to support the Voyager encounter of Neptune in August of 1989. This will significantly enhance the receiving capability of the United States for that historic event.
The U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA), Los Alamos Field Office (Field Office), has prepared final documentation for the resolution of adverse effects to Building 306 in Technical Area (TA) 16 at Los Alamos National Laboratory (LANL or the Laboratory). This documentation is being submitted to the New Mexico State Historic Preservation Officer (SHPO). TA-16-306 was determined eligible for listing in the National Register of Historic Places (Register) in 1995 in the report, TA-16 Heating System Replacement (LA-CP-95-0180). TA-16- 306 was identified as an excess property to be decontaminated, decommissioned, and demolished by the LANL Footprint Reduction Program in fiscal year 2021, an adverse effect to Register eligible building 16-306 requiring mitigation. To bring a resolution to the adverse effects to Building TA-16-306, the Field Office initiated consultation with the SHPO on December 4, 2017. The New Mexico Historic Preservation Division concurred with the mitigation actions outlined in the Programmatic Agreement among the U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office, the New Mexico State Historic Preservation Office, and the Advisory Council on Historic Preservation Concerning Management of Historic Properties of Los Alamos National Laboratory, Los Alamos, New Mexico (PA) in correspondence dated January 30, 2018. The PA states in Appendix D.2.A that adverse effects to Register-eligible buildings and structures will be resolved according to the procedures defined in A Plan for the Management of the Cultural Heritage at Los Alamos National Laboratory, New Mexico (CRMP) (LA-UR-19-21590, formerly LA-UR-15-27624) and within the PA itself. Volume 2 contains a collection of photos of building TA-16-306 with index.
The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.
The U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office (NA-LA), documented and evaluated seven structures in the Technical Area 60 (TA-60) Rack Assembly and Alignment Complex (RAAC) legacy storage yard at Los Alamos National Laboratory (LANL or Laboratory) for listing in the National Register of Historic Places (National Register). This documentation and evaluation was conducted in compliance with Section 106 of the National Historic Preservation Act of 1966, as amended; the Code of Federal Regulations (36 CFR 800); the Programmatic Agreement among the U.S. Department of Energy, National Nuclear Security Administration, Los Alamos Field Office, the New Mexico State Historic Preservation Office and the Advisory Council on Historic Preservation Concerning Management of the Historic Properties at Los Alamos National Laboratory, Los Alamos New Mexico (PA)1; and A Plan for the Management of the Cultural Heritage at Los Alamos National Laboratory, New Mexico (LANL’s Cultural Resources Management Plan (2017). NA-LA makes the following National Register eligibility determinations: la cuna; the rack transporter (jeep, rack trailer, and steering dolly); the Mexia diagnostic rack; the Mexia device canister; the Mexia device mounting stand; and the Mexia target stand are eligible for listing in the National Register, and the second steering dolly is not eligible for listing in the National Register. This National Register evaluation was completed because LANL proposes to develop a consolidated waste facility in TA-60 next to the former RAAC. Across 3.56 acres, LANL proposes to construct an 8,000-square-foot, pre-engineered waste storage building; a 1,500-square-foot office/warehouse building; and 28,500 square feet of covered storage. The development will also include access control features and fencing, parking spaces, and utilities. Additionally, the Laboratory will continue to use the southern part of TA-60-0017 and reuse TA-60-0086 and TA-60-0324 in the development. The consolidated waste facility will operate as a central accumulation area—storing universal waste, mixed low-level (radioactive) waste, hazardous chemicals, and New Mexico special waste—until the waste can be shipped off site.
Pursuant to Section 20.6.2.3104 of the New Mexico Administrative Code (NMAC), the U.S. Department of Energy/National Nuclear Security Administration/Sandia Field Office (DOE/NNSA/SFO) as owner and National Technology & Engineering Solutions of Sandia, LLC (NTESS) as operator are submitting this annual monitoring and discharge report for calendar year (CY) 2022 as required in Discharge Permit 530 (DP-530), issued by the New Mexico Environment Department (NMED) for the Pulsed Power Development Facilities Evaporation Lagoons located at Sandia National Laboratories/New Mexico (SNL/NM) Technical Area IV (TA-IV).
Environmental data is often complex, and it can be difficult to provide proper context to fully understand and comprehensively analyze the data. One tool identified to better present complicated data is the use of web-based Geographic Information Systems (GIS). Web-based GIS provides much-needed visual context to the complex data collected at Los Alamos National Laboratory (LANL). By overlaying environmental data atop relevant geographical features, such as topography, surface or subsurface geology, hydrogeological features, buildings, roads, and technical areas, LANL's diverse group of stakeholders are better able to understand environmental data collected at the LANL site within the framework of the surrounding geography. Since 2012, Los Alamos has utilized a web-based GIS module in the Intellus New Mexico data-sharing web site. This web site provides unfettered public access to LANL and New Mexico Environment Department (NMED) - Department of Energy (DOE) Oversight Bureau environmental data. Through the past five years of real world experience, LANL identified areas where questions and confusion arose, particularly for those not directly associated with the site's environmental cleanup mission. In order to query the millions of records in Intellus in a meaningful way, users had to have substantial knowledge of the data organization and nomenclature ahead of time. While this was not a challenge for LANL and NMED environmental scientists, it proved to be a substantial barrier for members of the general public to utilize Intellus. In 2017, LANL initiated an Intellus redesign with the goal of deconstructing the type of questions people asked and identifying the types of user personas accessing the site to engineer a simpler path to desired data sets. Greatly simplified click paths ('Quick Paths') were created that walk the user through the basics with a minimum of jargon and a strong reliance on mapping results for easy visualization. The improved mapping was enabled by an upgraded online GIS functionality that allowed LANL to easily integrate their own base-maps to provide users the most up to date views of their data. The integrated Intellus GIS was enhanced to assimilate with LANL's dynamic base maps and site information in relation to data collection activities, to avoid outdated presentations. A simplified user interface (UI) was added and easier data querying was designed. A more robust visual presentation was created that allowed better viewing of spatial data. All data queries in the new simplified 'Quick Path' give the users the option to map the results and save their results to their optional accounts. This brings the power of GIS visualization to all users without the need for GIS knowledge or extensive training. By integrating with Esri{sup R} technologies, base-map layers in ArcGIS Online{sup R} can be updated by LANL or other data providers at any time and reflected immediately in the Intellus mapping application called GIS+ 1. Users can even load additional map layers to GIS+ that contain their own spatial data or information shared from over a million users on ArcGIS Online{sup R}, such as ecological information from the Fish and Wildlife Service, or geology layers from the USGS. The results from the improved quick path search in Intellus can be viewed in GIS+ and analyzed using Esri's{sup R} Smart Mapping technology, which makes it easy to classify results with its visual representation of the results in an interactive histogram, where sliders can be dragged to look at various intervals for each color range for that query. With enhanced GIS+, Los Alamos National Laboratory is able to observe improve Stakeholder engagement and positive Stakeholder interactions within its public environmental database, Intellus New Mexico. (authors)
The 7 th Summer Physics Camp for Young Women was successfully held in person in 2023 from June 5 th to 16 th at the New Mexico School for the Arts in Santa Fe, NM at Hilo Intermediate School in Hawaii. This year’s camp was dedicated to the topic of Energy Security and was made possible thanks to the strong collaboration of Los Alamos, Sandia and Hawaii teams and the logistical and financial support of Los Alamos and Sandia National Laboratories, New Mexico Consortium, SAGE- Moore Foundation, LANL Foundation, ACS, IEE, APS four corners, N3B, Hawaii Museum of Science and Technology, New Mexico School for the Arts (NMSA) and Tech Source. The camp mobilized more than 120 volunteers who made the camp a success. The camp is free of charge to the students and included free lunch and snacks for the busy brains to have plenty of energy, also included all materials needed for the hands-on activities (like drone building, crystal structure, solar panels, wind turbine fabrication, soldering, coding etc) and also a stipend for students who attended for the full two weeks and for two educators and two student mentors in NM. The camp offered 32 high school students from New Mexico and 8 from Hawaii a unique opportunity to explore science topics and meet a broad range of role model professionals across STEM fields including astrophysics, cybersecurity, Energy fields, space science, engineering, biophysics, environmental science, robotics, computer science, nuclear engineering, radiological science, physics and chemistry. With nearly 120 volunteers who came mainly from Los Alamos National Laboratory (66%) and Sandia national laboratories (18%), two funded educators from NM, Dr. Weldon Beauchamp and Dr. Ellee Cook, and two educators from Hilo, Dr. Pascale Creek Pinner and LeAnn Ragasa, the camp was educationally sound and extremely varied. The collaboration with school educators is critical for the goal of this camp to not only impact students' lives but also improve STEM education in NM and Hawaii. The ultimate goal of the camp is to increase higher education aspirations of students, empower them to consider careers in STEM and learn more about the opportunities available to them in our local colleges and DOE National Laboratories. In addition, the camp also hired 2 past students as student mentors, Megan Odom and Elisea Jackson, who currently attend NMSA and were students at the camp in 2022 when it was virtual. The in-person camp which aims at empowering under-represented minorities in STEM in our community received more than 52 applications this year from all over NM and 8 applications from Hawaii. Our selection criteria are based on diversity, equity and inclusion, and students for whom the camp can be a life-changing opportunity are given a chance to attend the camp. During COVID, the camp was held virtually and gave the opportunity to students from remote areas in NM and Hawaii to attend from their homes. This year, fantastic families supported students everyday even when home was in remote areas in NM like Lea county, Sandoval county, Bernalillo or Mora county. The organizers hope next year they can offer a residential option for students from remote areas.
Sandia National Laboratories/New Mexico is located in Albuquerque, New Mexico, primarily on Department of Energy (DOE) permitted land on approximately 2,800 acres of Kirtland Air Force Base. There are approximately 5.5 million square feet of buildings, with a workforce of approximately 9200 personnel. Sandia National Laboratories Materials Sustainability and Pollution Prevention (MSP2) program adopted in 2008 an internal team goal for New Mexico site operations for Zero Waste to Landfill by 2025. Sandia solicited a consultant to assist in the development of a Zero Waste Strategic Plan. The Zero Waste Consultant Team selected is a partnership of SBM Management Services and Gary Liss & Associates. The scope of this Plan is non-hazardous solid waste and covers the life cycle of material purchases to the use and final disposal of the items at the end of their life cycle.
Sandia National Laboratories/New Mexico is located in Albuquerque, New Mexico, primarily on Department of Energy (DOE) permitted land on approximately 2,800 acres of Kirtland Air Force Base. There are approximately 5.5 million square feet of buildings, with a workforce of approximately 9200 personnel. Sandia National Laboratories Materials Sustainability and Pollution Prevention (MSP2) program adopted in 2008 an internal team goal for New Mexico site operations for Zero Waste to LandfilI by 2025. Sandia solicited a consultant to assist in the development of a Zero Waste Strategic Plan. The Zero Waste Consultant Team selected is a partnership of SBM Management Services and Gary Liss & Associates. The scope of this Plan is non-hazardous solid waste and covers the life cycle of material purchases to the use and final disposal of the items at the end of their life cycle.
Native species are plants and animals that continually occupy a natural range without direct or indirect introduction and/or care by humans. They are adapted to the environmental conditions and processes of the ecosystem in which they reside. A species introduced into a novel ecosystem can either exploit that ecosystem and thrive or be unable to survive in that ecosystem (Hobbs et al. 2006). Alien or non-native species are species that are intentionally or accidentally introduced into a novel ecosystem and are capable of living and propagating within the physical parameters of that ecosystem. Invasive species is a species that is non-native (or alien) to the ecosystem under consideration and a noxious species are those whose introduction causes or is likely to cause economic or environmental harm. The term invasive species is applicable to plants and animals alike; however, this invasive species management plan currently focuses on invasive vegetation. Invasive plant species are usually capable of rapid colonization of disturbed ground, such as after a change in wildfire regime intensity and frequency (Reilly et al. 2020) or anthropogenic ground disturbance (Burke and Grime 1996; Hobbs and Huenneke 1992). Climate change facilitates the spread and establishment of many alien species and creates new opportunities for them to become invasive (Turbelin and Catford 2021). As climate change impacts increase in the coming decades, we may see in an increase in invasive species establishment. See a list of definitions of terms pertinent to this document in Appendix A: Definitions. Los Alamos National Laboratory (LANL) hosts populations of non-native and invasive species all typical of the northern New Mexico region (Martin 2004; NMDA 2020). By implementing an invasive species management plan, LANL will have readily accessible management strategies for invasive species that are found on-site. The benefits of managing invasive species include a decrease in wildland fire risks, an increase in soil productivity, an increase in (productive or beneficial) wildlife habitat, an increase in water quantity and quality, and the restoration of impacted areas (Burke and Grime 1996; Hobbs and Huenneke 1992; D’Antonio and Hobbie 2005; MacDougall et al. 2013; Reilly et al. 2020). The aforementioned benefits from invasive species management directly enable the LANL mission by ensuring compliance requirements are met and site-wide programs, such as the Vulnerability Assessment and Resilience Plan, are supported for a mutually beneficial outcome. An example for the LANL site specifically, controlling non-native annual plant species, for example, could reduce the costs associated with stabilizing soils during the stormwater pollution prevention compliance process. Roadway and utility right-of-way areas are another place where an integrated vegetation management strategy would promote low growing perennial plants in a way that is mutually beneficial to habitat and the institution through lowered maintenance costs. There is also an economic benefit to managing invasive species. In one nationwide study, invasive plants had an estimated impact cost of $190.45 billion (Fantel-Lepczyk et al. 2022). Investing in preventative measures and surveillance could help to offset future control and management costs of invasive species that have the potential to become established. The State of New Mexico has developed plant species lists and recommendations through the New Mexico Department of Agriculture’s Noxious Weeds Management Act, Article 7D (NM Statute § 76-7D-4 2021); however, effective invasive species management must rely on local knowledge of the site and region. Los Alamos County (LAC) has already compiled a target invasive plant species list and species-specific management objectives (Martin 2004). Therefore, the New Mexico Noxious Weed List and the LAC invasive plant species list, as well as management objectives from those documents, are integrated into LANL’s invasive plant species management plan.
Southeastern New Mexico (SENM) is rich in mineral resources, including oil and gas. Produced water is a byproduct from oil and gas recovery operations. SENM generates approximately 400 million barrels per year of produced water with total dissolved solids (TDS) as high as ~ 200,000 ppm. Typically, produced water is disposed of by transporting it to injection wells or disposal ponds, costing around $\$$1.2 billion per year with an estimated use of 0.3 million barrels of transportation fuel. New Mexico ranks first among U.S. states in potash production. Nationally, more than 85% of all potash produced comes from the Carlsbad potash district in SENM. Potash manufacturing processes use large quantities of water, including fresh water, for solution mining. If the produced water from oilfield operations can be treated and used economically in the potash industry, it will provide a beneficial use for the produced water as well as preserve valuable water resources in an area where fresh water is scarce. The goal of this current research was to develop a prototype desalination system that economically treats produced water from oil and/or natural gas operations for the beneficial use of industries located in southeastern New Mexico. Up until now, most water cleaning technologies have been developed for treating water with much lower quantities of TDS. Seawater with TDS of around 30,000 ppm is the highest concentration that has been seriously studied by researchers. Reverse osmosis (RO) technology is widely used; however the cost remains high due to high-energy consumption. Higher water fluxes and recoveries are possible with a properly designed Forward Osmosis (FO) process as large driving forces can be induced with properly chosen membranes and draw solution. Membrane fouling and breakdown is a frequent and costly problem that drives the cost of desalination very high. The technology developed by New Mexico Tech (NMT) researchers not only protects the membrane, but has also proven to generate higher water flux, based on the series of experiments conducted. Laboratory tests at NMT demonstrated that an unprecedented water flux of 1300 l/m2/hr (where typical flux is on the order of 0-3 l/m 2 /hr) can be achieved from a properly designed membrane module. The patent pending NMT system, which was designed and developed at NMT was successful in reducing the possibility for concentration polarization and thereby increasing the permeate water flux, while still maintaining a high salt rejection rate of 96% or greater. For feed solutions having a dissolved contaminant concentration greater than 10,000 ppm, preliminary economic analysis demonstrates that a well-designed FO process will outperform an RO process. Most produced water generated in SENM has TDS higher than 10,000 ppm. Therefore, it is logical to use FO to desalinate the water. Since the issues associated with concentration polarization has only recently been solved by our mechanically enhanced membrane module, the level of system maturity is not at the same level as that for RO. Our efforts going forward will be directed at taking the technology to a higher level of system maturity. With the superior cost effectiveness for FO, it is imperative that this technology reach a point that is competitive with RO in order to meet the expanding need for water for industries in SENM. NMT seeks to demonstrate the greater cost effectiveness by proving the process through a scaled up model. To ensure success, NMT feels it is important to demonstrate this technology in a larger system, (~ 100,000 GPD), before venturing to the commercial scale. This will build confidence in the process with the commercial sector. In addition, it will be possible to develop some of the operational processes around renewable energy sources for the scaled up model. This will further lower the operating costs and enhance the environmentally clean aspect of the process.
The 2017 – 2018 Los Alamos National Laboratory Math and Science Academy Ir-Rational Number Institute (IrRNI) six-all-day sessions were held on Northern New Mexico College campus (NNMC) between September 2017 and March 2018. The IrRNI included 7 Northern New Mexico school districts (Bloomfield Public Schools, Cuba Independent Schools, Española Public Schools, Los Alamos Public Schools, Pojoaque Valley School District, Pecos Independent School District and Santa Fe Public Schools) and one Bureau of Indian Education school district, Jemez Day School, located in Jemez Pueblo. Twenty-nine teachers of mathematics, kindergarten through eighth grade, 2 principals, 1 STEM Coordinator, and 1 New Mexico Public Education Math and Science Bureau staffer* attended regularly and were eligible for a Certificate of Completion or Certificate of Engagement on the last day of instruction ( 20 participants were new to the IrRNI and 13 were returnees from the previous year or the MSA Summer Institute).
New mapping results are reported from a 30 km X 250 km transect.
The 2018 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 18 to August 2, 2018. NOMAD brings together participants with diverse technical backgrounds to work in small teams to cultivate new ideas and approaches in engineering mechanics and dynamics research. NOMAD provides an opportunity for researchers -- especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 17 students came to Albuquerque, New Mexico to participate in the seven-week long program held at the Mechanical Engineering building on the University of New Mexico campus. The students collaborated on one of six research projects that were developed by various mentors from Sandia National Laboratories, University of New Mexico, and academic institutions. In addition to the research activities, the students attended weekly technical seminars, various tours, and socialized at various off-hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation on their research findings. Many of the research discoveries made at NOMAD are published as proceedings at technical conferences and have direct alignment with the critical mission work performed at Sandia.
The 2019 Nonlinear Mechanics and Dynamics (NOMAD) Research Institute was successfully held from June 17 to August 1, 2019. NOMAD brings together participants with diverse technical backgrounds to work in small teams to cultivate new ideas and approaches in engineering mechanics and dynamics research. NOMAD provides an opportunity for researchers especially early career researchers - to develop lasting collaborations that go beyond what can be established from the limited interactions at their institutions or at annual conferences. A total of 20 students came to Albuquerque, New Mexico to participate in the seven-week long program held at the Mechanical Engineering building on the University of New Mexico campus. The students collaborated on one of seven research projects that were developed by various mentors from Sandia National Laboratories, the University of New Mexico, and academic institutions. In addition to the research activities, the students attended weekly technical seminars, various tours, and socialized at various off-hour events including an Albuquerque Isotopes baseball game. At the end of the summer, the students gave a final technical presentation on their research findings. Many of the research discoveries made at NOMAD are published as proceedings at technical conferences and have direct alignment with the critical mission work performed at Sandia.
The genus Monosporascus represents an enigmatic group of fungi important in agriculture and widely distributed in natural arid ecosystems. Of the nine described species, two (M. cannonballus and M. eutypoides) are important pathogens on the roots of members of Cucurbitaceae in agricultural settings. The remaining seven species are capable of colonizing roots from a diverse host range without causing obvious disease symptoms. Recent molecular and culture studies have shown that members of the genus are nearly ubiquitous as root endophytes in arid environments of the Southwestern United States. Isolates have been obtained from apparently healthy roots of grasses, shrubs and herbaceous plants located in central New Mexico and other regions of the Southwest. Phylogenetic and genomic analyses reveal substantial diversity in these isolates. The New Mexico isolates include close relatives of M. cannonballus and M. ibericus, as well as isolates that represent previously unrecognized lineages. To explore evolutionary relationships within the genus and gain insights into potential ecological functions, we sequenced and assembled the genomes of three M. cannonballus isolates, one M. ibericus isolate, and six diverse New Mexico isolates. The assembled genomes were significantly larger than what is typical for the Sordariomycetes despite having predicted gene numbers similar to other members of the class. Differences in predicted genome content and organization were observed between endophytic and pathogenic lineages of Monosporascus. Several Monosporascus isolates appear to form associations with members of the bacterial genus Ralstonia (Burkholdariaceae).
Trichloroethene (TCE) and nitrate have been identified as constituents of concern in groundwater at the Sandia National Laboratories, New Mexico (SNL/NM) Technical Area (TA)-V Groundwater (TAVG) Area of Concern (AOC) based on detections above the U.S. Environmental Protection Agency (EPA) maximum contaminant levels in samples collected from monitoring wells. The maximum contaminant levels and the State of New Mexico drinking water standards, as specified in 20.6.2.3103 New Mexico Administrative Code (NMAC) for TCE and nitrate (as nitrogen) are 5 micrograms per liter (p,g/L) and 10 milligrams per liter (mg/L), respectively.
Hazardous waste management activities are regulated by the New Mexico Environment Department (NMED) pursuant to New Mexico Hazardous Waste Act (HWA; Chapter 74, Article 4 NMSA 1978) and regulations under the Act. In 1989, NMED issued the Hazardous Waste Facility Permit (EPA ID Number NM0890010515- 1) that established standards for the Laboratory to manage, store, and treat hazardous wastes on-site and to undertake the closure and post closure care of permitted waste management units.