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Skills and Knowledge for Data-Intensive Environmental Research

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap.

54 ENVIRONMENTAL SCIENCES↗

Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems

Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.

Preconditioner, Nonlinear, Porous media, Multiphas↗

SU-E-T-50: A Multi-Institutional Study of Independent Dose Verification Software Program for Lung SBRT

Purpose: The accuracy of dose distribution depends on treatment planning system especially in heterogeneity-region. The tolerance level (TL) of the secondary check using the independent dose verification may be variable in lung SBRT plans. We conducted a multi-institutional study to evaluate the tolerance level of lung SBRT plans shown in the AAPM TG114. Methods: Five institutes in Japan participated in this study. All of the institutes used a same independent dose verification software program (Simple MU Analysis: SMU, Triangle Product, Ishikawa, JP), which is Clarkson-based and CT images were used to compute radiological path length. Analytical Anisotropic Algorithm (AAA), Pencil Beam Convolution with modified Batho-method (PBC-B) and Adaptive Convolve (AC) were used for lung SBRT planning. A measurement using an ion-chamber was performed in a heterogeneous phantom to compare doses from the three different algorithms and the SMU to the measured dose. In addition to it, a retrospective analysis using clinical lung SBRT plans (547 beams from 77 patients) was conducted to evaluate the confidence limit (CL, Average±2SD) in dose between the three algorithms and the SMU. Results: Compared to the measurement, the AAA showed the larger systematic dose error of 2.9±3.2% than PBC-B and AC. The Clarkson-based SMU showed larger error of 5.8±3.8%. The CLs for clinical plans were 7.7±6.0 % (AAA), 5.3±3.3 % (AC), 5.7±3.4 % (PBC -B), respectively. Conclusion: The TLs from the CLs were evaluated. A Clarkson-based system shows a large systematic variation because of inhomogeneous correction. The AAA showed a significant variation. Thus, we must consider the difference of inhomogeneous correction as well as the dependence of dose calculation engine.

60 APPLIED LIFE SCIENCES↗

Direct Observations of Solute Dispersion in Rocks With Distinct Degree of Sub‐Micron Porosity

Abstract The transport of chemical species in rocks is affected by their structural heterogeneity to yield a wide spectrum of local solute concentrations. To quantify such imperfect mixing, advanced methodologies are needed that augment the traditional breakthrough curve analysis by probing solute concentration within the fluids locally. Here, we demonstrate the application of asynchronous, multimodality imaging by X‐ray computed tomography (XCT) and positron emission tomography (PET) to the study of passive tracer experiments in laboratory rock cores. The four‐dimensional concentration maps measured by PET reveal specific signatures of the transport process, which we have quantified using fundamental measures of mixing and spreading. We observe that the extent of solute spreading correlate strongly with the strength of subcore‐scale porosity heterogeneity measured by XCT, while dilution is enhanced in rocks containing substantial sub‐micron porosity. We observe that the analysis of different metrics is necessary, as they can differ in their sensitivity to the strength and forms of heterogeneity. The multimodality imaging approach is uniquely suited to probe the fundamental difference between spreading and mixing in heterogeneous media. We propose that when multi‐dimensional data is available, mixing and spreading can be independently quantified using the same metric. We also demonstrate that one‐dimensional transport models have limited predictive ability toward the internal evolution of the solute concentration, when the model is solely calibrated against the effluent breakthrough curves. The data set generated in this study can be used to build realistic digital rock models and to benchmark transport simulations that account deterministically for rock property heterogeneity.

Kurotori, Takeshi [Department of Chemical Engineer↗

Dynamic earthquake rupture simulations on nonplanar faults embedded in 3D geometrically complex, heterogeneous elastic solids

Dynamic propagation of shear ruptures on a frictional interface in an elastic solid is a useful idealization of natural earthquakes. The conditions relating discontinuities in particle velocities across fault zones and tractions acting on the fault are often expressed as nonlinear friction laws. The corresponding initial boundary value problems are both numerically and computationally challenging. In addition, seismic waves generated by earthquake ruptures must be propagated for many wavelengths away from the fault. Therefore, reliable and efficient numerical simulations require both provably stable and high order accurate numerical methods. We present a high order accurate finite difference method for: a) enforcing nonlinear friction laws, in a consistent and provably stable manner, suitable for efficient explicit time integration; b) dynamic propagation of earthquake ruptures along nonplanar faults; and c) accurate propagation of seismic waves in heterogeneous media with free surface topography. We solve the first order form of the 3D elastic wave equation on a boundary-conforming curvilinear mesh, in terms of particle velocities and stresses that are collocated in space and time, using summation-by-parts (SBP) finite difference operators in space. Boundary and interface conditions are imposed weakly using penalties. By deriving semi-discrete energy estimates analogous to the continuous energy estimates we prove numerical stability. The finite difference stencils used in this paper are sixth order accurate in the interior and third order accurate close to the boundaries. However, the method is applicable to any spatial operator with a diagonal norm satisfying the SBP property. Time stepping is performed with a 4th order accurate explicit low storage Runge–Kutta scheme, thus yielding a globally fourth order accurate method in both space and time. We show numerical simulations on band limited self-similar fractal faults revealing the complexity of rupture dynamics on rough faults.

58 GEOSCIENCES↗

In silico trials predict that combination strategies for enhancing vesicular stomatitis oncolytic virus are determined by tumor aggressivity

Background Immunotherapies, driven by immune-mediated antitumorigenicity, offer the potential for significant improvements to the treatment of multiple cancer types. Identifying therapeutic strategies that bolster antitumor immunity while limiting immune suppression is critical to selecting treatment combinations and schedules that offer durable therapeutic benefits. Combination oncolytic virus (OV) therapy, wherein complementary OVs are administered in succession, offer such promise, yet their translation from preclinical studies to clinical implementation is a major challenge. Overcoming this obstacle requires answering fundamental questions about how to effectively design and tailor schedules to provide the most benefit to patients. Methods We developed a computational biology model of combined oncolytic vaccinia (an enhancer virus) and vesicular stomatitis virus (VSV) calibrated to and validated against multiple data sources. We then optimized protocols in a cohort of heterogeneous virtual individuals by leveraging this model and our previously established in silico clinical trial platform. Results Enhancer multiplicity was shown to have little to no impact on the average response to therapy. However, the duration of the VSV injection lag was found to be determinant for survival outcomes. Importantly, through treatment individualization, we found that optimal combination schedules are closely linked to tumor aggressivity. We predicted that patients with aggressively growing tumors required a single enhancer followed by a VSV injection 1 day later, whereas a small subset of patients with the slowest growing tumors needed multiple enhancers followed by a longer VSV delay of 15 days, suggesting that intrinsic tumor growth rates could inform the segregation of patients into clinical trials and ultimately determine patient survival. These results were validated in entirely new cohorts of virtual individuals with aggressive or non-aggressive subtypes. Conclusions Based on our results, improved therapeutic schedules for combinations with enhancer OVs can be studied and implemented. Our results further underline the impact of interdisciplinary approaches to preclinical planning and the importance of computational approaches to drug discovery and development.

60 APPLIED LIFE SCIENCES↗

SU-C-BRE-02: BED Vs. Local Control: Radiobiological Effect of Tumor Volume in Monte Carlo (MC) Lung SBRT Planning

Purpose: SBRT with hypofractionated dose schemata has emerged a compelling treatment modality for medically inoperable early stage lung cancer patients. It requires more accurate dose calculation and treatment delivery technique. This report presents the relationship between tumor control probability(TCP) and size-adjusted biological effective dose(sBED) of tumor volume for MC lung SBRT patients. Methods: Fifteen patients who were treated with MC-based lung SBRT to 50Gy in 5 fractions to PTVV100%=95% were studied. ITVs were delineated on MIP images of 4DCT-scans. PTVs diameter(ITV+5mm margins) ranged from 2.7–4.9cm (mean 3.7cm). Plans were generated using non-coplanar conformal arcs/beams using iPlan XVMC algorithm (BrainLABiPlan ver.4.1.2) for Novalis-TX with HD-MLCs and 6MVSRS(1000MU/min) mode, following RTOG-0813 dosimetric guidelines. To understand the known uncertainties of conventional heterogeneities-corrected/uncorrected pencil beam (PBhete/ PB-homo) algorithms, dose distributions were re-calculated with PBhete/ PB-homo using same beam configurations, MLCs and monitor units. Biologically effective dose(BED10) was computed using LQ-model with α/β=10Gy for meanPTV and meanITV. BED10-c*L, gave size-adjusted BED(sBED), where c=10Gy/cm and L=PTV diameter in centimeter. The TCP model was adopted from Ohri et al.(IJROBP, 2012): TCP = exp[sBEDTCD50]/ k /(1.0 + exp[sBED-TCD50]/k), where k=31Gy corresponding to TCD50=0Gy; and more realistic MC-based TCP was computed for PTV(V99%). Results: Mean PTV PB-hete TCP value was 6% higher, but, mean PTV PB-homo TCP value was 4% lower compared to mean PTV MC TCP. Mean ITV PB-hete/PB-homo TCP values were comparable (within ±3.0%) to mean ITV MC TCP. The mean PTV(V99%)had BED10=90.9±3.7%(median=92.2%),sBED=54.1±8.2%(median=53.5%) corresponding to mean MC TCP value of 84.8±3.3%(median=84.9%) at 2- year local control. Conclusion: The TCP model which incorporates BED10 and tumor diameter indicates that radiobiological effect of target volume and dose calculation algorithm significantly affects TCP for lung SBRT patients. Dose calculation using MC-based algorithm is more realistic with tissue heterogeneities and is routinely performed in our clinic. Patients will be followed up to determine whether TCP prediction correlate clinical outcomes.

60 APPLIED LIFE SCIENCES↗

Colloidal nanocrystals for heterogeneous catalysis

Catalytic materials are an essential component of the chemical industry. They find applications in everything from fine chemical manufacturing to greenhouse gas mitigation. They are indispensable for developing a sustainable future. Their development has been continuous, from early trial and error efforts to the first fundamental insights gained through surface science, to modern in-situ characterization and computational predictions. The accumulation of knowledge on the working principles of catalytic surfaces allowed designing and producing better systems with improved performance. Even though tremendous progress has been made thanks to surface science techniques, these studies are usually performed under ultra-high vacuum and are therefore limited in their applicability to more relevant industrial conditions. The control over size, shape and composition in colloidal nanocrystals makes them formidable precursors for model heterogeneous catalysts. These model systems enable linking the insights from surface science studies via in-situ and operando studies to realistic catalytic reaction conditions. In this review, colloidal nanocrystals are presented as powerful building blocks for catalytic materials in the quest for fundamental understanding. A review of the principal methods to produce colloidal nanocrystals with a high level of control is reported, complemented by procedures for how to prepare active catalysts from these particles. Examples and guidelines for the catalytic applications of these materials revolve around the three guiding objectives in catalysis science: activity, selectivity and stability. This work will be limited to examples of this colloidal approach in the areas of thermal, electro- and photocatalysis. In conclusion, the exposed approaches can be used and extended to many other areas of catalysis science, thus providing a new avenue to explore fundamentals and applications of catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Serpentine: Finite Difference Methods for Wave Propagation in Second Order Formulation

Wave propagation phenomena are important in many DOE applications such as nuclear explosion monitoring, geophysical exploration, estimating ground motion hazards and damage due to earthquakes, non-destructive testing, underground facilities detection, and acoustic noise propagation. There are also future applications that would benefit from simulating wave propagation, such as geothermal energy applications and monitoring sites for carbon storage via seismic reflection techniques. In acoustics and seismology, it is of great interest to increase the frequency bandwidth in simulations. In seismic exploration, greater frequency resolution enables shorter wave lengths to be included in the simulations, allowing for better resolution in the seismic imaging. In nuclear explosion monitoring, higher frequency seismic waves are essential for accurate discrimination between explosions and earthquakes. When simulating earthquake induced motion of large structures, such as nuclear power plants or dams, increased frequency resolution is essential for realistic damage predictions. Another example is simulations of micro-seismic activity near geothermal energy plants. Here, hydro-fracturing induces many small earthquakes and the time scale of each event is proportional to the square root of the moment magnitude. As a result, the motion is dominated by higher frequencies for smaller seismic events. The above wave propagation problems are all governed by systems of hyperbolic partial differential equations in second order differential form, i.e., they contain second order partial derivatives of the dependent variables. Our general research theme in this project has been to develop numerical methods that directly discretize the wave equations in second order differential form. The obvious advantage of working with hyperbolic systems in second order differential form, as opposed to rewriting them as first order hyperbolic systems, is that the number of differential equations in the second order system is significantly smaller. Another issue with re-writing a second order system into first order form is that compatibility conditions often must be imposed on the first order form. These (Saint-Venant) conditions ensure that the solution of the first order system also satisfies the original second order system. However, such conditions can be difficult to enforce on the discretized equations, without introducing additional modeling errors. This project has previously developed robust and memory efficient algorithms for wave propagation including effects of curved boundaries, heterogeneous isotropic, and viscoelastic materials. Partially supported by internal funding from Lawrence Livermore National Laboratory, many of these methods have been implemented in the open source software WPP, which is geared towards 3-D seismic wave propagation applications. This code has shown excellent scaling on up to 32,768 processors and has enabled seismic wave calculations with up to 26 Billion grid points. The WPP calculations have resulted in several publications in the field of computational seismology, e.g.. All of our current methods are second order accurate in both space and time. The benefits of higher order accurate schemes for wave propagation have been known for a long time, but have mostly been developed for first order hyperbolic systems. For second order hyperbolic systems, it has not been known how to make finite difference schemes stable with free surface boundary conditions, heterogeneous material properties, and curvilinear coordinates. The importance of higher order accurate methods is not necessarily to make the numerical solution more accurate, but to reduce the computational cost for obtaining a solution within an acceptable error tolerance. This is because the accuracy in the solution can always be improved by reducing the grid size h. However, in practice, the available computational resources might not be large enough to solve the problem with a low order method.

15 GEOTHERMAL ENERGY↗

Influence of grid resolution, parcel size and drag models on bubbling fluidized bed simulation

Here in this paper, a bubbling fluidized bed is simulated with different numerical parameters, such as grid resolution and parcel size. We examined also the effect of using two homogeneous drag correlations and a heterogeneous drag based on the energy minimization method. A fast and reliable bubble detection algorithm was developed based on the connected component labeling. The radial and axial solids volume fraction profiles are compared with experiment data and previous simulation results. These results show a significant influence of drag models on bubble size and voidage distributions and a much less dependence on numerical parameters. With a heterogeneous drag model that accounts for sub-scale structures, the void fraction in the bubbling fluidized bed can be well captured with coarse grid and large computation parcels. Refining the CFD grid and reducing the parcel size can improve the simulation results but with a large increase in computation cost.

97 MATHEMATICS AND COMPUTING↗