Engineering topics
Publications and source records attributed to Vesselinov, Velimir.
Explore the source record for details and available documents.
For effective and equitable outcomes in achieving the national goal of net-zero carbon emissions, communities must be not only included, but even lead the implementation of innovative green-energy technologies. Collaborations with communities should happen through informed decision-making, community-centered research and engagement of stakeholders at the local, state, and regional levels. Community-led research and implementation are fundamental to achieving success. These collaborations include rule makers, environmental regulators, clean energy industries, and technology researchers and developers. Unfortunately, many green infrastructure initiatives still adhere to a top-down and expert-driven process of site selection and design without awareness and acknowledgment of public engagement needs. This can lead to costly delays, including lawsuits, and ultimately less than desired or lacking outcomes as well as missed opportunities1. Geothermal, like many new technologies whose social and economic impacts are not fully understood, often cause disproportionately high adverse effects on disadvantaged communities. These effects can be related to human health, environmental, climate, and other cumulative impacts, as well as the accompanying economic challenges of these impacts. We are focusing our work on the needs of the New Mexico Native American Pueblos and Tribes (NMP&T). To address these needs, we are developing a novel web-based interactive software and user friendly interface called GeoTGO (https://geotgo.com) that provides everything that is needed for communities to better understand and develop their geothermal resources. We will bridge the gap between technology advancements and community needs by facilitating the interactions between the geothermal industry, regulators, stakeholders, and end-users. GeoTGO will merge data, software (including data analysis, text mining, artificial intelligence, and modeling tools), knowledge, expertise, and experience to provide fast processing and dissemination of the latest information about cutting-edge geothermal technologies to users and communities. More information about the project is available at https://envitrace.com/projects/geotgo.html.
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information about SmartTensors can be found at the SmartTensors Github Repository and the SmartTensors page at LANL.gov. Links to these pages are included in this submission. GeoThermalCloud.jl is a repository containing all the data and codes required to demonstrate applications of machine learning methods for geothermal exploration. GeoThermalCloud.jl includes: - site data - simulation scripts - jupyter notebooks - intermediate results - code outputs - summary figures - readme markdown files GeoThermalCloud.jl showcases the machine learning analyses performed for the following geothermal sites: - Brady: geothermal exploration of the Brady geothermal site, Nevada - SWNM: geothermal exploration of the Southwest New Mexico (SWNM) region - GreatBasin: geothermal exploration of the Great Basin region, Nevada Reports, research papers, and presentations summarizing these machine learning analyses are also available and will be posted soon.
Environmental management problems associated with contamination of groundwater resources with heavy metals (such as chromium) typically require complex biogeochemical model simulations and analysis of in situ remediation. Frequently, the in situ remediation is the only viable treatment option. In these cases, a three-dimensional reactive transport model of relevant biogeochemical processes is invaluable. Recently, we have developed a novel unique biogeochemical simulator called CHROTRAN (http://chrotran.lanl.gov; Hansen et al. 2017, Vesselinov et al. 2018a) capable to represent the full three-dimensional dynamics of processes associated with in situ biogeochemical remediation of heavy metals in heterogeneous aquifers. CHROTRAN accounts for spatial and temporal transients of (1) the heavy metal to be remediated, (2) introduced amendments (e.g., through well injection), and (3) biomass growth and decay. The introduced amendments can include (1) an electron donor (e.g., molasses), (2) a nontoxic-conservative bio-inhibitor (e.g., ethanol), and (3) a biocide (e.g., dithionite). In addition, direct abiotic reduction by donor-metal interaction as well as donor-driven biomass growth and bio-reduction are modeled in CHROTRAN. Other critical processes, such as donor sorption, bio-fouling and biomass death are also modeled. CHROTRAN can simulate the groundwater flow dynamics introduced due a series of injection and extraction wells and account for reduction of aquifer permeability near the wells due bio clogging. CHROTRAN is based on the existing PFLOTRAN (http://pflotran.org; Lichtner et al, 2017a) code framework, taking advantage of the reaction interface allowing for implementation of complex model features and leverage other facets of PFLOTRAN, such as multi-component geochemistry and high-performance computing. Here, we present numerical simulations and model analyses related to the Los Alamos National Laboratory (LANL) chromium site. The analyses are performed by coupling of CHROTRAN with MADS (Model Analysis and Decision Support; http://mads.lanl.gov; Vesselinov et al., 2018b). We present analyses related to uncertainty quantification of model predictions, sensitivity of model parameters and remedial decision support. (authors)
Modeling hydrologic flow and transport in the subsurface presents a number of challenges including large datasets that contain limited information about the properties of the subsurface and models with a large number of parameters characterizing the properties of the subsurface and the ambient hydrologic conditions (e.g., groundwater recharge). This, in turn, leads to substantial uncertainty in predictions about quantities of interest (e.g., the concentration of a contaminant at points of compliance). We present a number of methods and tools that have recently been developed to address these problems. The model calibration tools are capable of assimilating large datasets (for example, on the order of 1,000,000 model calibration targets) into numerical models, calibrating models with a large number of model parameters (on the order of 1,000,000), or both. These tools leverage recently developed methods in numerical linear algebra such as matrix-free methods and randomized matrix sketching. The uncertainty quantification tools are highly-parallel and enable us to robustly quantify the uncertainties in model parameters (and therefore uncertainty in quantities of interest). Having these capabilities in model analysis tools enables more informed decision making related to remediation of groundwater contaminants. The model analyses that we present are related to the Los Alamos National Laboratory (LANL) chromium site. The analyses are performed by MADS (Model Analysis and Decision Support; http://mads.lanl.gov). (authors)
A hexavalent chromium plume is present in deep groundwater beneath Los Alamos National Laboratory (LANL or the Laboratory). The plume originated from releases of potassium dichromate from cooling towers from 1956 - 1972. Estimates are that up to 72,000 kg of chromium was released during that period. Data from surface water-balance studies, core-hole and groundwater characterization, geomorphic investigations and geology and geophysics provide the basis for an evolved conceptual model that chromium initially traveled rapidly via an effluent-supported stream for several kilometers, then infiltrated through a stratigraphically complex 275-300 meters thick vadose zone and eventually into a deep (regional) aquifer that is the water supply for the Laboratory and surrounding municipality. The travel time from the release point to the regional aquifer is estimated at 5-10 years based on modeling and contaminant tracers. Monitoring data from two-screen wells and piezometers within the regional aquifer, and data derived from stratified sampling conducted during sonic coring and from analysis of sonic core indicate that the chromium contamination occurs within the upper 23 meters of the highly stratified regional aquifer. Different geologic units at the water table and structural dip of depositional bedding appear to have little effect on chromium migration and plume shape and thickness which instead appear to be a manifestation of multiple breakthrough locations, interconnectedness of preferential hydraulic strata, and a negligible vertical gradient. Recent monitoring data indicate that the down-gradient plume edge (as defined by the New Mexico groundwater standard of 50 μg/L) may be advancing near the Laboratory's boundary with a neighboring Indian reservation. The Laboratory is addressing the increasing concentrations with a regulatory-driven interim measure that uses hydraulic control to manage plume migration. The interim measure involves limited-duration (2-3 years) pumping, treatment, and injection to rapidly establish and maintain the 50 μg/L plume edge within the Laboratory boundary while a final remediation strategy is developed and approved by the State regulator. A final remediation strategy will depend heavily on the ability to cost-effectively access the deep aquifer. (authors)
Pajarito models are developed to perform various types of model analyses related to the LANL-site groundwater contamination problems. Pajarito models include several models representing the LANL Chromium (Cr) and RDX sites. Pajarito models also include a model that is at the scale of the Pajarito Plateau. The models are designed to perform model prediction of groundwater flow and contaminant transport. The models are bundled in repositories. The model repositories include scripts, input control files, and drivers. A detailed description of the various files included in the repositories is provided in electronic form within the repositories.