About

Monique Wheeler is a disaster management and humanitarian assistance subject matter expert with extensive experience in emergency preparedness and mitigation, training and education, project management, engineering, program implementation, and planning. She has worked on the National Level Exercise 2022 and 2024, supporting FEMA in exercise design and development, and was a lead writer for the Homeland Security Exercise and Evaluation Program (HSEEP) 2020 Doctrine revision for the FEMA National Exercise Division. Monique participated in the development of the United States’ first cybersecurity grant via the Invest in America Act, which created a $1 billion grant program for state, local, and tribal governments to enhance their cybersecurity capacity and capability. She spent two years at the Pentagon leading emergency management and writing policy for the US Air Force and has been involved in mitigating climate change at US military installations worldwide. Internationally, Monique led teams to write the after action report for the U.S. response to the 2014 Nepal Earthquake and provided recommendations for a $500 million World Bank development project in Bangladesh. She served as the Assessment Lead in Mongolia, Nepal, Bangladesh, Serbia, and Bosnia-Herzegovina, working with embassy and ministry levels to develop emergency management agencies by identifying areas of improvement, strengths, strategy, and capability gaps. Additionally, she led, coordinated, and participated in bilateral and multilateral engagements across various countries including Georgia, Germany, Indonesia, Cambodia, Vietnam, Thailand, Philippines, Japan, and Guam. Monique also served as the team lead for developing regionalized disaster management and peacekeeping curricula at two peacekeeping training centers in East and West Africa. She is a reviewer for the Journal of Emergency Management and the Journal of Gender Based Violence. She holds an MS in civil and environmental engineering with an emphasis in water resources and an MA in urban and regional planning with an emphasis in disaster management from the University of Hawaii at Manoa. She is currently pursuing a PhD in liberal studies at Georgetown University.

Research topics

• Computer Science
• Mathematical analysis
• Mathematics
• Mathematical optimization
• Artificial Intelligence
• Materials science
• Structural engineering
• Algorithm
• Thermodynamics
• Engineering
• Composite material
• Physics
• Applied mathematics
• Mechanics

Selected publications

• Effective porothermoelastic model and properties for fractured porous media

  2025-06-08

  article

  ABSTRACT: We investigate the impact of fractures on the effective thermomechanical response of porous media using numerical simulation. While dual porosity is a popular numerical model for multiphase flow effective models, research on the macroscale hydro-thermo-mechanical response in the presence of fractures is scarce. This work uses an in-house numerical framework with automated mesh generation, fracture distribution, simulation, and postprocessing for the investigation. The proposed model explores the following effective parameters: drained bulk modulus, drained Poisson ratio, drained Biot coefficient, Skempton B coefficient and drained thermal expansion coefficient. Results indicate that the fracture network is impactful even considering low fracture densities and that using results from laboratory experiments conducted in intact samples may mislead large-scale field interpretations of fractured media. Disregarding the fractures, results in overestimating the effective Biot coefficient and Skempton coefficient B, underestimating the effective drained Bulk Modulus; and overestimating the drained thermal expansion coefficient. Altogether, the macroscopic impact of the fractures is an important strain absorption mechanism for matrix stresses that can be effectively upscaled into field-scale models. Using parameters of a naturally fractured carbonate reservoir, we provide an example where a matrix-based geomechanical model may lead to erroneous interpretations of fracture propagation within the reservoir. Conversely, the effective medium parameters model leads to a smaller stress contrast between the reservoir and the caprock.

  PublisherDOI

• The von Neumann Stability Analysis of the Fixed‐Stress Schemes in Poroelastodynamics

  International Journal for Numerical and Analytical Methods in Geomechanics · 2025-12-16

  articleOpen accessSenior author

  ABSTRACT We investigate splitting schemes based on the fixed‐stress sequential approach for poroelastodynamic problems. To assess numerical stability, we perform the von Neumann stability analysis on several fixed‐stress schemes for poroelastodynamics, including staggered, stabilized, and iterative methods. Our analysis reveals that while the staggered fixed‐stress method is unconditionally stable for poroelastostatics, this unconditional stability does not extend to poroelastodynamics due to the presence of the second‐order time derivative in the geomechanics wave equation. Specifically, the staggered method becomes unstable when the Courant number falls below unity, indicating a lower bound on the time step size required for stability in poroelastodynamic simulations. The stabilized method, which incorporates an additional stabilization term, maintains numerical stability across the full range of Courant numbers. However, it suffers from limited convergence and reduced accuracy, particularly at low Courant numbers. In contrast, the iterative fixed‐stress method consistently converges to the monolithic solution, regardless of the Courant number, provided that full iteration is performed. Numerical tests validate these stability estimates and confirm agreement with the von Neumann stability analysis.

  PublisherDOI

• A phase-field diffraction model for thermo-hydro-mechanical propagating fractures

  International Journal of Heat and Mass Transfer · 2024-12-13 · 9 citations

  article
  PublisherDOI

• The FluidFlower International Benchmark Study: Process, Modeling Results, and Comparison to Experimental Data

  arXiv (Cornell University) · 2023-02-09 · 11 citations

  preprintOpen access

  Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the "FluidFlower"), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations.

  PublisherOA PDFDOI

• A posteriori error estimates for Biot system using a mixed discretization for flow

  Computer Methods in Applied Mechanics and Engineering · 2022-07-04 · 2 citations

  articleOpen access1st author
  PublisherOA PDFDOI

• Local Residual Minimization Smoothing for Improving Convergence Behavior of a Space-Time Domain Decomposition Method

  Lecture notes in computational science and engineering · 2022-01-01 · 2 citations

  book-chapterSenior author
  PublisherDOI

• Space-time geometric multigrid method for nonlinear advection–diffusion problems

  Applicable Analysis · 2022-02-13 · 1 citations

  articleSenior author

  Multigrid methods, algebraic or geometric, commonly suffer from high frequency residuals after prolongation. This paper develops a stable approach to remove high frequency residuals for geometric multigrid methods for solving nonlinear advection–diffusion problems with degenerate coefficients. Here, a local problem is treated by optimization on subdomains with mesh refinements. Newton's method is utilized in the procedure and the iteration is completed when the residual in the subdomain is reduced to the given magnitude, usually set to be the average of residuals in the non-high-frequency domains. An oversampling technique is employed to further improve the stability by providing a definite flow path in regions where coefficients have high contrast and complex structures. Removing high frequency residuals before continuing the global Newton iteration improves global convergence behavior.

  PublisherDOI

• Optimal $$L^2$$ A Priori Error Estimates for the Biot System

  La Matematica · 2022-03-01 · 1 citations

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• Dynamic local coupling for multiphase flow: A compromise between efficiency and stability

  Journal of Computational Physics · 2022-08-17 · 3 citations

  articleSenior author
  PublisherDOI

• Bayesian Optimization for Field-Scale Geological Carbon Storage

  Engineering · 2022-07-25 · 21 citations

  articleOpen access

  We present a framework that couples a high-fidelity compositional reservoir simulator with Bayesian optimization (BO) for injection well scheduling optimization in geological carbon sequestration. This work represents one of the first at tempts to apply BO and high-fidelity physics models to geological carbon storage. The implicit parallel accurate reservoir simulator (IPARS) is utilized to accurately capture the underlying physical processes during CO2 sequestration. IPARS provides a framework for several flow and mechanics models and thus supports both stand-alone and coupled simulations. In this work, we use the compositional flow module to simulate the geological carbon storage process. The compositional flow model, which includes a hysteretic three-phase relative permeability model, accounts for three major CO2 trapping mechanisms: structural trapping, residual gas trapping, and solubility trapping. Furthermore, IPARS is coupled to the International Business Machines (IBM) Corporation Bayesian Optimization Accelerator (BOA) for parallel optimizations of CO2 injection strategies during field-scale CO2 sequestration. BO builds a probabilistic surrogate for the objective function using a Bayesian machine learning algorithm—the Gaussian process regression, and then uses an acquisition function that leverages the uncertainty in the surrogate to decide where to sample. The IBM BOA addresses the three weaknesses of standard BO that limits its scalability in that IBM BOA supports parallel (batch) executions, scales better for high-dimensional problems, and is more robust to initializations. We demonstrate these merits by applying the algorithm in the optimization of the CO2 injection schedule in the Cranfield site in Mississippi, USA, using field data. The optimized injection schedule achieves 16% more gas storage volume and 56% less water/surfactant usage compared with the baseline. The performance of BO is compared with that of a genetic algorithm (GA) and a covariance matrix adaptation (CMA)-evolution strategy (ES). The results demonstrate the superior performance of BO, in that it achieves a competitive objective function value with over 60% fewer forward model evaluations.

  PublisherDOI

Recent grants

• "Collaborative Research"ITR-(ASE+EVS)-dmv+sim):Data Driven Simulation of the Subsurface: Optimization and Uncertainty Estimation

  NSF · $694k · 2004–2008

• Collaborative Research: High-Fidelity Modeling of Poromechanics with Strong Discontinuities

  NSF · $300k · 2019–2023

• BIGDATA: Collaborative Research: IA: F: Fractured Subsurface Characterization using High Performance Computing and Guided by Big Data

  NSF · $823k · 2016–2018

• CDI-Type II: Collaborative Research: Computational Models for Evaluating Long Term CO2 Storage in Saline Aquifers

  NSF · $1.7M · 2008–2014

• CMG "Collaborative Research":"Stochastic Mulstiscale Modeling of Subsurface Flow and Reactive Transport"

  NSF · $275k · 2006–2009

Frequent coauthors

• Jim Douglas

  27 shared

• Lawrence C. Cowsar

  20 shared

• Ivan Yotov

  19 shared

• Jan Mandel

  University of Colorado Denver

  18 shared

• Todd Dupont

  University of Chicago

  14 shared

• Thomas Wick

  Leibniz University Hannover

  13 shared

• Saumik Dana

  12 shared

• Todd Arbogast

  11 shared