Bayesian Physics-Informed Neural Network for the Forward and Inverse Simulation of Engineered Nano-particles Mobility in a Contaminated Aquifer

Globally, there are many polluted groundwater sites that need an active remediation plan for the restoration of local ecosystem and environment. Engineered nanoparticles (ENPs) have proven to be an effective reactive agent for the in-situ degradation of pollutants in groundwater. While the performance of these ENPs has been highly promising on the laboratory scale, their application in real field case conditions is still limited. The complex transport and retention mechanisms of ENPs hinder the development of an efficient remediation strategy. Therefore, a predictive tool to comprehend the transport and retention behavior of ENPs is highly required. The existing tools in the literature are dominated with numerical simulators, which have limited flexibility and accuracy in the presence of sparse datasets and the aquifer heterogeneity. This work uses a Bayesian Physics-Informed Neural Network (B-PINN) framework to model the nano-particles mobility within an aquifer. The result from the forward model demonstrates the effective capability of B-PINN in accurately predicting the ENPs mobility and quantifying the uncertainty. The inverse model output is then used to predict the governing parameters for the ENPs mobility in a small-scale aquifer. The research demonstrates the capability of the tool to provide predictive insights for developing an efficient groundwater remediation strategy.Comment: To be submitted to a NeurIPS 2023 workshop. arXiv admin note: substantial text overlap with arXiv:2211.0352

Dynamic weights enabled Physics-Informed Neural Network for simulating the mobility of Engineered Nano-particles in a contaminated aquifer

Numerous polluted groundwater sites across the globe require an active remediation strategy to restore natural environmental conditions and local ecosystem. The Engineered Nano-particles (ENPs) have emerged as an efficient reactive agent for the in-situ degradation of groundwater contaminants. While the performance of these ENPs has been highly promising on the laboratory scale, their application in real field case conditions is still limited. The complex transport and retention mechanisms of ENPs hinder the development of an efficient remediation strategy. Therefore, a predictive tool for understanding the transport and retention behavior of ENPs is highly required. The existing tools in the literature are dominated with numerical simulators, which have limited flexibility and accuracy in the presence of sparse datasets. This work uses a dynamic, weight-enabled Physics-Informed Neural Network (dw-PINN) framework to model the nano-particle behavior within an aquifer. The result from the forward model demonstrates the effective capability of dw-PINN in accurately predicting the ENPs mobility. The model verification step shows that the relative mean square error (MSE) of the predicted ENPs concentration using dw-PINN converges to a minimum value of $1.3{e^{-5}}$. In the subsequent step, the result from the inverse model estimates the governing parameters of ENPs mobility with reasonable accuracy. The research demonstrates the tool's capability to provide predictive insights for developing an efficient groundwater remediation strategy.Comment: 5 pages, 3 Figures, Conference paper accepted in NeurIPS 2022 Workshop: Tackling Climate Change with Machine Learnin

Role of the clay lenses within sandy aquifers in the migration pathway of infiltrating DNAPL plume: A numerical investigation

The use of numerical based multi-phase fluid flow simulation can significantly aid in the development of an effective remediation strategy for groundwater systems contaminated with Dense Non Aqueous Phase Liquid (DNAPL). Incorporating the lithological heterogeneities of the aquifer into the model domain is a crucial aspect in the development of robust numerical simulators. Previous research studies have attempted to incorporate lithological heterogeneities into the domain; however, most of these numerical simulators are based on Finite Volume Method (FVM) and Finite Difference Method (FDM) which have limited applicability in the field-scale aquifers. Finite Element Method (FEM) can be highly useful in developing the field-scale simulation of DNAPL infiltration due to its consistent accuracy on irregular study domain, and the availability of higher orders of basis functions. In this research work, FEM based model has been developed to simulate the DNAPL infiltration in a hypothetical field-scale aquifer. The model results demonstrate the effect of meso-scale heterogeneities, specifically clay lenses, on the migration and accumulation of Dense Non Aqueous Phase Liquid (DNAPL) within the aquifer. Furthermore, this research provides valuable insights for the development of an appropriate remediation strategy for a general contaminated aquifer

End-to-End Integrated Simulation for Predicting the Fate of Contaminant and Remediating Nano-Particles in a Polluted Aquifer

Groundwater contamination caused by Dense Non-Aqueous Phase Liquid (DNAPL) has an adverse impact on human health and environment. Remediation techniques, such as the in-situ injection of nano Zero Valent Iron (nZVI) particles, are widely used in mitigating DNAPL-induced groundwater contamination. However, an effective remediation strategy requires predictive insights and understanding of the physiochemical interaction of nZVI and contamination along with the porous media properties. While several stand-alone models are widely used for predictive modeling, the integration of these models for better scalability and accuracy is still rarely utilized. This study presents an end-to-end integrated modeling framework for the remediation of DNAPL-contaminated aquifers using nZVI. The framework simulates the migration pathway of DNAPL and subsequently its dissolution in groundwater resulting in an aqueous contaminant plume. Additionally, the framework includes simulations of nZVI mobility, transport, and reactive behavior, allowing for the prediction of the radius of influence and efficiency of nZVI for contaminant degradation. The framework has been applied to a hypothetical 2-dimensional and heterogeneous silty sand aquifer, considering trichloroethylene (TCE) as the DNAPL contaminant and carboxymethyl cellulose (CMC) coated nZVI for remediation. The results demonstrate the framework's capability to provide comprehensive insights into the contaminant's behavior and the effectiveness of the remediation strategy. The proposed modeling framework serves as a reference for future studies and can be expanded to incorporate real field data and complex geometries for upscaled applications.Comment: 33 page

Introducción al estudio de la industria lítica pulimentada del "Solsonià" (4500-3500 BC): Estudio de la materia prima y su origen. La "Vall Salina" de Cardona y la minería de la sal

The finding of lithic artefacts of Neolithic age in the Vall Salina (Cardona, NE Spain) has been traditionally related to the ancient salt mining. Despite the sedimentary nature of the geology in this area (siliciclastic and evaporite rocks of Tertiary age), these tools were made up with metapelitic rocks. These lithologies are common in the Catalan Coastal Ranges, especially in the Collserola and Montseny massifs. These rocks also crop out in some areas in the Pyrenees but it is unlikely that recent weathering could carry metapelite clasts into the alluvial Quaternary deposits close to the Vall Salina. In this study, we report the petrographic characterization of these tools as part of an integral project on the Middle Neolithic salt mining in Catalonia. The results point to a connection between the salt exploitation in the Vall Salina and the coastal areas located 60 km southwards.A raíz del estudio de las herramientas líticas pulidas documentadas en la Vall Salina de Cardona, relacionadas con la minería de la sal gema, se comprobó que estas estaban elaboradas en roca metapelítica. En toda la Depresión Central Catalana, no hay afloramientos de metapelíticas. Es en las cordilleras Prelitoral y Litoral situadas al noreste del delta del río Llobregat donde son abundantes, destacando las áreas de Collserola o en el Montseny. Este tipo de rocas también aparecen en el Pirineo axial, pero se descarta la posibilidad que fuesen los ríos Cardener o Aigua d'Ora los principales portadores de materia prima por erosión de esos afloramientos situados al norte del área de estudio. Así pues, por la composición mineralógica, situamos la procedencia de este utillaje del área de Collserola. El trabajo que presentamos forma parte de un proyecto de investigación arqueológica integral relacionado con la explotación de la sal durante el Neolítico medio en Cataluña. Es una introducción al análisis mineralógico, sin descuidar las interpretaciones derivadas de los resultados obtenidos, como la revalorización de la especialización local o regional

Geochemical monitoring in the Hontomín (Burgos, Spain) injection site: preliminary results and perspectives

CO2 capture and storage (CCS) projects are presently developed to reduce the emission of anthropogenic CO2 into the atmosphere. CCS technologies are expected to account for the 20% of the CO2 reduction by 2050. One of the main concerns of CCS is whether CO2 may remain confined within the geological formation into which it is injected since post-injection CO2 migration in the time scale of years, decades and centuries is not well understood. Theoretically, CO2 can be retained at depth i) as a supercritical fluid (physical trapping), ii) as a fluid slowly migrating in an aquifer due to long flow path (hydrodynamic trapping), iii) dissolved into ground waters (solubility trapping) and iv) precipitated secondary carbonates. Carbon dioxide will be injected in the near future (2012) at Hontomín (Burgos, Spain) in the frame of the Compostilla EEPR project, led by the Fundación Ciudad de la Energía (CIUDEN). In order to detect leakage in the operational stage, a pre-injection geochemical baseline is presently being developed. In this work a geochemical monitoring design is presented to provide information about the feasibility of CO2 storage at depth

Sampling strategies using the "accumulation chamber" for monitoring geological storage of CO2

Fundación Ciudad de la Energía (CIUDEN) is carrying out a project of geological storage of CO2, where CO2 injection tests are planned in saline aquifers at a depth of 1500 m for scientific objectives and project demonstration. Before any CO2 is stored, it is necessary to determine the baseline flux of CO2 in order to detect potential leakage during injection and post-injection monitoring. In November 2009 diffuse flux measurements of CO2 using an accumulationchamber were made in the area selected by CIUDEN for geological storage, located in Hontomin province of Burgos (Spain). This paper presents the tests carried out in order to establish the optimum sampling methodology and the geostatistical analyses performed to determine the range, with which future field campaigns will be planned

Systematic Approach for the selection of monitoring technologies in CO2 geological storage projects. Application of multicriteria decision making

Geologic storage of carbon dioxide (CO2) has been proposed as a viable means for reducing anthropogenic CO2 emissions. Once injection begins, a program for measurement, monitoring, and verification (MMV) of CO2 distribution is required in order to: a) research key features, effects and processes needed for risk assessment; b) manage the injection process; c) delineate and identify leakage risk and surface escape; d) provide early warnings of failure near the reservoir; and f) verify storage for accounting and crediting. The selection of the methodology of monitoring (characterization of site and control and verification in the post-injection phase) is influenced by economic and technological variables. Multiple Criteria Decision Making (MCDM) refers to a methodology developed for making decisions in the presence of multiple criteria. MCDM as a discipline has only a relatively short history of 40 years, and it has been closely related to advancements on computer technology. Evaluation methods and multicriteria decisions include the selection of a set of feasible alternatives, the simultaneous optimization of several objective functions, and a decision-making process and evaluation procedures that must be rational and consistent. The application of a mathematical model of decision-making will help to find the best solution, establishing the mechanisms to facilitate the management of information generated by number of disciplines of knowledge. Those problems in which decision alternatives are finite are called Discrete Multicriteria Decision problems. Such problems are most common in reality and this case scenario will be applied in solving the problem of site selection for storing CO2. Discrete MCDM is used to assess and decide on issues that by nature or design support a finite number of alternative solutions. Recently, Multicriteria Decision Analysis has been applied to hierarchy policy incentives for CCS, to assess the role of CCS, and to select potential areas which could be suitable to store. For those reasons, MCDM have been considered in the monitoring phase of CO2 storage, in order to select suitable technologies which could be techno-economical viable. In this paper, we identify techniques of gas measurements in subsurface which are currently applying in the phase of characterization (pre-injection); MCDM will help decision-makers to hierarchy the most suitable technique which fit the purpose to monitor the specific physic-chemical parameter