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Estimation of k-ε parameters using surrogate models and jet-in-crossflow data

We demonstrate a Bayesian method that can be used to calibrate computationally expensive 3D RANS (Reynolds Av- eraged Navier Stokes) models with complex response surfaces. Such calibrations, conditioned on experimental data, can yield turbulence model parameters as probability density functions (PDF), concisely capturing the uncertainty in the parameter estimates. Methods such as Markov chain Monte Carlo (MCMC) estimate the PDF by sampling, with each sample requiring a run of the RANS model. Consequently a quick-running surrogate is used instead to the RANS simulator. The surrogate can be very difficult to design if the model's response i.e., the dependence of the calibration variable (the observable) on the parameter being estimated is complex. We show how the training data used to construct the surrogate can be employed to isolate a promising and physically realistic part of the parameter space, within which the response is well-behaved and easily modeled. We design a classifier, based on treed linear models, to model the "well-behaved region". This classifier serves as a prior in a Bayesian calibration study aimed at estimating 3 k - ε parameters ( C μ , C ε2 , C ε1 ) from experimental data of a transonic jet-in-crossflow interaction. The robustness of the calibration is investigated by checking its predictions of variables not included in the cal- ibration data. We also check the limit of applicability of the calibration by testing at off-calibration flow regimes. We find that calibration yield turbulence model parameters which predict the flowfield far better than when the nomi- nal values of the parameters are used. Substantial improvements are still obtained when we use the calibrated RANS model to predict jet-in-crossflow at Mach numbers and jet strengths quite different from those used to generate the ex- perimental (calibration) data. Thus the primary reason for poor predictive skill of RANS, when using nominal values of the turbulence model parameters, was parametric uncertainty, which was rectified by calibration. Post-calibration, the dominant contribution to model inaccuraries are due to the structural errors in RANS.

97 MATHEMATICS AND COMPUTING↗

Reduced‐Order Modeling of Energetic Materials Using Physics‐Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)

Physics-aware deep learning (PADL) has gained popularity for use in spatiotemporal dynamics simulations, such as those in computational modeling of energetic materials (EM). We show that the challenge PADL methods face while learning complex field evolution problems can be simplified and accelerated by decoupling it into two tasks: learning complex geometric features in evolving fields and modeling dynamics over these features in a lower-dimensional feature space. We build upon our previous work on physics-aware recurrent convolutional neural networks (PARC). PARC embeds knowledge of underlying physics into its neural network architecture for more robust and accurate prediction of evolving physical fields. PARC was shown to effectively learn complex nonlinear features such as the formation of hotspots and coupled shock fronts in various initiation scenarios of EMs, as a function of microstructures, serving effectively as a microstructure-aware burn model. Here, we further accelerate PARC and reduce its computational cost by projecting the original dynamics onto a lower-dimensional invariant manifold, or “latent space.” The projected latent representation encodes the complex geometry of evolving fields (e.g., temperature and pressure) in a set of data-driven features. The reduced dimension of this latent space allows us to learn the dynamics during the initiation of EM with a lighter and more efficient model. We observe a significant decrease in training and inference time while maintaining results comparable to PARC at inference. This work takes steps towards enabling rapid prediction of EM thermomechanics at larger scales and characterization of EM structure–property–performance linkages at a full application scale.

Mathematics and Computing↗

Faster-than-real-time Simulation with Demonstration for Resilient DER Integration

The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. The Faster-than-real-time Simulation with demonstration for Resilient DER Integration project set out to do the following: a. Flatten the voltage profile through the feeders and system for cost saving and voltage stabilization needs. b. Increase the amount of intermittent distributed energy resources (IDERs) that could be deployed on a utility feeder and provide 100% or more energy needed for the demands on that feeder, and c. based on an accurate model (Digital Twin) of the utilities system, be able to detect any abnormalities on the utilities distribution system. To manage the voltage and increase IDER penetration (a,b), Graph Trace Analysis is employed in a time-series, optimal power flow to coordinate the time-varying feedback control setpoints of a distribution feeder’s utility control devices. Under the coordinated control are a Load Tap Changing Transformer, a voltage regulator, and five switched capacitor banks. The feeder serves over 2000 customers, the feeder secondaries are modeled, and the feeder has 2.3 MW of PV generation, corresponding to a 17.4% penetration of PV generation. The feeder model has over 12,000 components, where every customer load bus and PV generator are modeled. The accuracy of the power flow solution is compared against historical meter voltage measurements, the improvement in conservation voltage reduction energy savings as a function of the coordinated control desired voltage profile is investigated, and the increase in PV penetration of the coordinated control over the existing control is presented. To achieve improved control performance while observing system operation constraints, bellwether Advanced Metering Infrastructure (AMI) voltage measurements are used to adjust the desired voltage profile used by the optimal power flow analysis. To detect and alleviate or negate attacks or failures on the distribution and transmission utility grids (c) the grid needs to be resilient and self-healing. In this project software was designed to do just that. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hard-ware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.

Integrated System Model, Graph Trace Analysis, Adv↗

On the road to per cent accuracy – III. Non-linear reaction of the matter power spectrum to massive neutrinos

ABSTRACT We analytically model the non-linear effects induced by massive neutrinos on the total matter power spectrum using the halo model reaction framework of Cataneo et al. In this approach, the halo model is used to determine the relative change to the matter power spectrum caused by new physics beyond the concordance cosmology. Using standard fitting functions for the halo abundance and the halo mass–concentration relation, the total matter power spectrum in the presence of massive neutrinos is predicted to per cent-level accuracy, out to $k=10 \,{ h}\,{\rm Mpc}^{-1}$. We find that refining the prescriptions for the halo properties using N-body simulations improves the recovered accuracy to better than 1 per cent. This paper serves as another demonstration for how the halo model reaction framework, in combination with a single suite of standard Λ cold dark matter (ΛCDM) simulations, can recover per cent-level accurate predictions for beyond ΛCDM matter power spectra, well into the non-linear regime.

79 ASTRONOMY AND ASTROPHYSICS↗

Flow matching meets biology and life science: a survey

Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological research and discovery, enabling breakthroughs in molecule design, protein generation, catalysis discovery, drug discovery, and beyond. At the same time, biological applications have served as valuable testbeds for evaluating the capabilities of generative models. Recently, flow matching has emerged as a powerful and efficient alternative to diffusion-based generative modeling, with growing interest in its application to problems in biology and life sciences. This paper presents the first comprehensive survey of recent developments in flow matching and its applications in biological domains. We begin by systematically reviewing the foundations and variants of flow matching, and then categorize its applications into three major areas: biological sequence modeling, molecule generation and design, and peptide and protein generation. For each, we provide an in-depth review of recent progress. We also summarize commonly used datasets and software tools, and conclude with a discussion of potential future directions.

59 BASIC BIOLOGICAL SCIENCES↗

Active Measurement of Plasma Parameters in Over-Dense MFE Reactor Plasma Using High Frequency Beat-Wave Resonantly Generated Thermal Bernstein Waves

UC Davis was funded to explore the combination of beat-wave excitation and laser scattering to make completely non-invasive determination of local plasma conditions. This involves the use of two high frequency mm-wave sources of differing frequencies (the pump waves) to excite plasma waves at the difference of the frequencies, which is known as the beat frequency. The difference frequency or the frequency of the beat wave is chosen so that we produce plasma waves whose fluctuating electron density is a sensitive function of plasma parameters at the location where the source waves overlap. This fluctuation can be detected from outside the plasma, by measuring the deflection of a probe beam directed at the overlap region between the two pump waves (i.e., collective scattering). This work is an extension of mm-wave frequencies of a 10 GHz beat-wave experiment conducted on the DDT toroidal device (see Fig. 1) in a magnetized plasma where the excited Langmuir wave is replaced by the magnetized upper hybrid wave. Here, two high power (> 1 kW) ~94 GHz pump sources will be employed to match the upper hybrid resonance. The primary envisioned experiment is to drive the electron Bernstein wave (EBW) in the interior of a magnetized plasma. The EBW is a hot-plasma electrostatic wave, which cannot propagate in vacuum. Roots of the EBW dispersion relation occur at frequencies slightly higher than harmonics of the electron cyclotron frequency. Use of the EBW has particular advantages for measuring plasma magnetic field in plasmas with relatively high density and low magnetic field, as is the case in spherical tokamaks. This is the “over dense” condition of future efficient high beta magnetic confinement fusion reactors such as the spherical tokamak (STs). The overarching goal of the proposed project is to demonstrate beat wave EBW excitation in low density and temperature parameters that are directly scalable to over-dense spherical tokamaks such as NSTX or MAST, where measurement of magnetic field by electron cyclotron emission (ECE) is experimentally complex, and requires models of plasma profiles in order to interpret results. In such experiments, availability of point measurements of magnetic field strength provided by a beat-wave diagnostic would serve as a powerful independent check on the ECE results, serving to validate the assumed profiles and wave-propagation models used. The first step was to assemble/modify the target chamber in which the beat-wave plasma experiments will take place. Here, the target chamber of the CTIX compact-toroid (spheromak) injector was chosen. At the time that the proposal was submitted, the aim was to conduct the experiments in the CTIX experimental facilities located at the Livermore campus of UC Davis using microwave/mm-wave equipment brought from the main campus., However, by the time DoE funds for this project were awarded, the CTIX experimental facilities located at the Livermore campus of UC Davis were in the process of being shut down due to the closure of the Livermore campus by Lawrence Livermore National Laboratory (LLNL). Consequently, the equipment needed for this project was crated up and shipped from Livermore to Davis as part of the laboratory shutdown after space on campus was secured and College of Engineering approval secured. Once it arrived in Davis on December 20, 2018, work on the project began in earnest with the initial efforts directed toward developing a new plasma target source. Because of the shutdown of the CTIX facility, the scope of the project thus had to be reduced due to the abbreviated amount of time allocated to the project once the shutdown/move had been completed. Chamber modifications have been completed, including the fabrication and installation of a 38 GHz interferometer, as described in Sec. 3. The thermionic plasma source has been tested and characterized. The magnetic field required for the EBW experiments will be generated by permanent magnets mounted on plates positioned above and below the chamber. Magnetic simulations have been performed, and show that a 3-ring magnet arrangement on each plate, with a plate separation of 50 cm, is required to achieve the ~100 G uniform magnetic field in the interaction region that we feel is necessary to ensure good EBW coupling. We proved unable to successfully revive either of Prof. Luhmann’s two high power (≥20 kW) 94 GHz millimeter-wave sources after their extended time in storage and decided to postpone further efforts and concentrate on slightly lower power sources. Consequently, we were successful in reviving a ~2 kW extended klystron amplifier (EIK), which together with a ~2 kW extended interaction oscillator (EIO) will provide the two pump sources required for the project. Safe operation of the EIO requires extensive modifications to one of Prof. Luhmann’s pulse modulators - these modulator modifications are ongoing, which has unfortunately delayed the planned beat-wave experiments. Details of this work are provided in Sec. 3. Even though project funding has now ended, we still plan to proceed to complete the EIO pulse modulator modifications, install the two ~94 GHz pump wave sources on the target chamber, and conduct unmagnetized tests of the beat-wave concept which involve coupling to unmagnetized electron plasma waves rather than magnetized EBWs. Should these experiments prove successful, we plan to submit a follow-up proposal for additional funding which would allow us to undertake the magnetized EBW experiments.

42 ENGINEERING↗

Gas Bubble Evolution in Polycrystalline UMo Fuels Under Elastic-Plastic Deformation: A Phase-Field Model With Crystal-Plasticity

In monolithic UMo fuels, the interaction between the Al cladding and large gas bubble volumetric swelling causes both elastic-plastic and creep deformation. In this work, a phase-field model of gas bubble evolution in polycrystalline UMo under elastic-plastic deformation was developed for studying the dynamic interaction between evolving gas bubble/voids and deformation. A crystal plasticity model, which assumes that the plastic strain rate is proportional to resolved shear stresses of dislocation slip systems on their slip planes, was used to describe plastic deformation in polycrystalline UMo. Xe diffusion and gas bubble evolution are driven by the minimization of chemical and deformation energies in the phase-field model, while evolving gas bubble structure was used to update the mechanical properties in the crystal plasticity model. With the developed model, we simulated the effect of gas bubble structures (different volume fractions and internal gas pressures) on stress-strain curves and the effect of local stresses on gas bubble evolution. The results show that 1) the effective Young’s modulus and yield stress decrease with the increase of gas bubble volume fraction; 2) the hardening coefficient increases with the increase of gas bubble volume fraction, especially for gas bubbles with higher internal pressure; and 3) the pressure dependence of Xe thermodynamic and kinetic properties in addition to the local stress state determine gas bubble growth or shrinkage. The simulated results can serve as a guide to improve material property models for macroscale fuel performance modeling.

36 MATERIALS SCIENCE↗

Terra-Populus v0.1: A Python Library for LandScan High-Definition Population Analysis and Modeling

The terra-populus library is designed for use by the LandScan HD technical team, offering a streamlined set of tools for generating and updating LandScan HD datasets from foundational building-level data, referred to as 'molecules,' provided by the building-level attribution team. This document serves as the primary technical documentation for terra-populus. Version 0.1 of the library includes the core modeling components necessary for LandScan HD production. It enables the generation of the LandScan HD Baseline dataset as well as corresponding confidence measures for the occupancy rates used. Parameters have been included for incorporating damaged building indicators and changes in population, to faciliate the creation of rapid updates for LandScan HD. Future iterations of terra-populus will introduce tools for creating a confidence index, and quantifying and propagating uncertainty, facilitating the creation of probabilistic LandScan HD outputs. This report provides an overview of the tools available in the library and the corresponding code implementations. One of the key advancements implemented in terra-populus is a redefinition of the atomic modeling unit for LandScan HD. Traditionally, the LandScan HD vector analytical framework has generated population estimates at the building sub-component (molecule) level. However, terra-populus adopts a building-level modeling approach. This shift is an operational decision aimed at aligning LandScan HD outputs with confidence measures, which are computed and validated at the building level (confidence measures are not included in this version of terra-populus, aside from those associated with the occupancy rates). Additional advancements to the LandScan HD modeling, as implemented by terra-populus, include a minimum population value parameter and an auto assignment of building floor counts. The population minimum value was implemented to prevent buildings and subsequent LandScan HD pixels that contained small values that may not rasterize in production. An 'auto' value has been included as a method for dealing with buildings lacking floor count information, where it is the average floor count of all other buildings with a residential building use type tag. The logic behind this is to remain consistent with the current logic employed for dealing with building use type null instances, where a null use type is defaulted to residential since it is the most common building type. The auto logic is intended to apply the most common building floor count of the most common type of buildings. The tools provided in terra-populus represent a significant step forward in improving the efficiency, reproducibility, and transparency of the LandScan HD modeling process. As the library evolves, it will continue to serve as a foundational resource for high-resolution population modeling.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

The ezSpectra suite: An easy‐to‐use toolkit for spectroscopy modeling

Abstract A molecule's spectrum encodes information about its structure and electronic properties. It is a unique fingerprint that can serve as a molecular ID. Quantum chemistry calculations provide key ingredients for interpreting spectra, but modeling the spectra rarely ends there; it requires additional steps that entail combined treatments of electronic and nuclear degrees of freedom and account for specifics of the experimental setup (light energy, polarization, averaging over molecular orientations, temperature, etc.). This Software Focus article describes the ezSpectra suite, which currently comprises two stand‐alone open‐source codes: ezFCF and ezDyson . ezFCF calculates Franck–Condon factors, which yield vibrational progressions for polyatomic molecules, within the double‐harmonic approximation. ezDyson calculates absolute cross‐sections for photodetachment/photoionization processes and photoelectron angular distributions using Dyson orbitals computed by a quantum chemistry program. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Theoretical and Physical Chemistry > Spectroscopy Software > Simulation Methods

Gozem, Samer↗

WE-G-BRD-01: A Data-Driven 4D-MRI Motion Model to Estimate Full Field-Of-View Abdominal Motion From 2D Image Navigators During MR-Linac Treatment

Purpose: To estimate full field-of-view abdominal respiratory motion from fast 2D image navigators using a 4D-MRI based motion model. This will allow for radiation dose accumulation mapping during MR-Linac treatment. Methods: Experiments were conducted on a Philips Ingenia 1.5T MRI. First, a retrospectively ordered 4D-MRI was constructed using 3D transient-bSSFP with radial in-plane sampling. Motion fields were calculated through 3D non-rigid registration. From these motion fields a PCA-based abdominal motion model was constructed and used to warp a 3D reference volume to fast 2D cine-MR image navigators that can be used for real-time tracking. To test this procedure, a time-series consisting of two interleaved orthogonal slices (sagittal and coronal), positioned on the pancreas or kidneys, were acquired for 1m38s (dynamic scan-time=0.196ms), during normal, shallow, or deep breathing. The coronal slices were used to update the optimal weights for the first two PCA components, in order to warp the 3D reference image and construct a dynamic 4D-MRI time-series. The interleaved sagittal slices served as an independent measure to test the model’s accuracy and fit. Spatial maps of the root-mean-squared error (RMSE) and histograms of the motion differences within the pancreas and kidneys were used to evaluate the method. Results: Cranio-caudal motion was accurately calculated within the pancreas using the model for normal and shallow breathing with an RMSE of 1.6mm and 1.5mm and a histogram median and standard deviation below 0.2 and 1.7mm, respectively. For deep-breathing an underestimation of the inhale amplitude was observed (RMSE=4.1mm). Respiratory-induced antero-posterior and lateral motion were correctly mapped (RMSE=0.6/0.5mm). Kidney motion demonstrated good motion estimation with RMSE-values of 0.95 and 2.4mm for the right and left kidney, respectively. Conclusion: We have demonstrated a method that can calculate dynamic 3D abdominal motion in a large volume, while acquiring real-time cine-MR images for MR-guided radiotherapy.

60 APPLIED LIFE SCIENCES↗

TU-F-17A-03: An Analytical Respiratory Perturbation Model for Lung Motion Prediction

Purpose: Breathing irregularity is common, causing unreliable prediction in tumor motion for correlation-based surrogates. Both tidal volume (TV) and breathing pattern (BP=ΔVthorax/TV, where TV=ΔVthorax+ΔVabdomen) affect lung motion in anterior-posterior and superior-inferior directions. We developed a novel respiratory motion perturbation (RMP) model in analytical form to account for changes in TV and BP in motion prediction from simulation to treatment. Methods: The RMP model is an analytical function of patient-specific anatomic and physiologic parameters. It contains a base-motion trajectory d(x,y,z) derived from a 4-dimensional computed tomography (4DCT) at simulation and a perturbation term Δd(ΔTV,ΔBP) accounting for deviation at treatment from simulation. The perturbation is dependent on tumor-specific location and patient-specific anatomy. Eleven patients with simulation and treatment 4DCT images were used to assess the RMP method in motion prediction from 4DCT1 to 4DCT2, and vice versa. For each patient, ten motion trajectories of corresponding points in the lower lobes were measured in both 4DCTs: one served as the base-motion trajectory and the other as the ground truth for comparison. In total, 220 motion trajectory predictions were assessed. The motion discrepancy between two 4DCTs for each patient served as a control. An established 5D motion model was used for comparison. Results: The average absolute error of RMP model prediction in superior-inferior direction is 1.6±1.8 mm, similar to 1.7±1.6 mm from the 5D model (p=0.98). Some uncertainty is associated with limited spatial resolution (2.5mm slice thickness) and temporal resolution (10-phases). Non-corrected motion discrepancy between two 4DCTs is 2.6±2.7mm, with the maximum of ±20mm, and correction is necessary (p=0.01). Conclusion: The analytical motion model predicts lung motion with accuracy similar to the 5D model. The analytical model is based on physical relationships, requires no training, and therefore is potentially more resilient to breathing irregularities. On-going investigation introduces airflow into the RMP model for improvement. This research is in part supported by NIH (U54CA137788/132378). AY would like to thank MSKCC summer medical student research program supported by National Cancer Institute and hosted by Department of Medical Physics at MSKCC.

60 APPLIED LIFE SCIENCES↗

Three-Dimensional Numerical Evaluation of Thermal Performance of Uninsulated Wall Assemblies: Preprint

This study describes a detailed three-dimensional computational fluid dynamics modeling to evaluate the thermal performance of uninsulated wall assemblies accounting for conduction through framing, convection, and radiation. The model allows for material properties variations with temperature. Parameters that were varied in the study include ambient outdoor temperature and cavity surfaceemissivity. Understanding the thermal performance of uninsulated wall cavities is essential for accurate prediction of energy use in residential buildings. The results can serve as input for building energy simulation tools for modeling the temperature dependent energy performance of homes with uninsulated walls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An experimental and kinetic modeling study of cyclopentane and dimethyl ether blends

Cyclopentane is a suitable naphthene, or cycloalkane, in a palette for multi-component gasoline surrogate fuels due to its presence in market fuels and its relevance to alkyl substituted cyclopentanes also present. However, the previous oxidation studies of cyclopentane have primarily focused on neat mixtures. Blending cyclopentane with dimethyl ether in this work therefore serves to inform our understanding of, and improve predictive models for, multi-component mixtures. Here, the auto-ignition of cyclopentane/dimethyl ether blends was studied in a high-pressure shock tube and in a rapid compression machine. A wide range of temperatures (650 – 1350 K) and elevated pressures of 20 and 40 bar were studied at equivalence ratios of 0.5, 1.0 and 2.0 in air for two blending ratios (30/70 and 70/30 mole% cyclopentane/di-methyl ether mixtures). A detailed kinetic model for cyclopentane was revised to capture the measured ignition delay times and apparent heat release rates in this study. Literature ignition delay time, jet-stirred reactor, and laminar burning velocity measurements of neat cyclopentane were used as additional validation. Improvements to the kinetic model were based on recent literature studies related to sub-models including cyclopentene and cyclopentadiene which allowed the removal of previous local rate-constant optimizations. Low temperature reactivity of cyclopentane was found to be controlled by the branching ratio between concerted elimination of HO͘ 2 and the strained formation of Q&#775OOH radicals in agreement with previous studies. In this study, the low branching ratio of Q&#775OOH formation increases the influence of a competing consumption pathway for cyclopentyl-peroxy (CPTO͘ 2 J) radicals. The sensitivity of the simulated ignition delay times to the formation of cyclopentyl hydroperoxide (CPTO 2 H), from CPTO͘ 2 J and HO͘ 2 , is discussed. The current model is used to analyze the influence of dimethyl ether on the reactivity of cyclopentane in the context of previous literature studies of dimethyl ether binary blends with ethanol and toluene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transport coefficient sensitivities in a semi-analytic model for magnetized liner inertial fusion

Performance of magnetized liner inertial fusion (MagLIF) experiments is highly dependent on transport processes including magnetized heat flows and magnetic flux losses. Magnetohydrodynamic simulations used to model these experiments require a choice of model for the transport coefficients, which are the constants of proportionality relating driving terms, such as temperature gradients and currents, to the associated heat and magnetic field transport. The coefficients have been the subject of repeated recalculation using various methods throughout the years. Using a semi-analytic MagLIF model, we compare models for the transport coefficients. The choice of model modifies magnetic-flux losses caused by the Nernst thermoelectric effect and thermal conduction losses. We present simulated results from parameter scans conducted in order to compare the effects of the different models on parameters of interest in MagLIF. In some regions of parameter space, discrepancies of up to 38% are found in integrated quantities like the fusion yield. These results may serve as a guide for experimental validation of the various models, particularly as laser preheat energies and initial axial field strengths are increased on MagLIF experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulation of the 2003 Foss Barge - Point Wells Oil Spill: A Comparison between BLOSOM and GNOME Oil Spill Models

The Department of Energy’s (DOE’s) National Energy Technology Laboratory’s (NETL’s) Blowout and Spill Occurrence Model (BLOSOM), and the National Oceanic and Atmospheric Administration’s (NOAA’s) General NOAA Operational Modeling Environment (GNOME) are compared. Increasingly complex simulations are used to assess similarities and differences between the two models’ components. The simulations presented here are forced by ocean currents from a Finite Volume Community Ocean Model (FVCOM) implementation that has excellent skill in representing tidal motion, and with observed wind data that compensates for a coarse vertical ocean model resolution. The comprehensive comparison between GNOME and BLOSOM presented here, should aid modelers in interpreting their results. Beyond many similarities, aspects where both models are distinct are highlighted. Some suggestions for improvement are included, e.g., the inclusion of temporal interpolation of the forcing fields (BLOSOM) or the inclusion of a deflection angle option when parameterizing wind-driven processes (GNOME). Overall, GNOME and BLOSOM perform similarly, and are found to be complementary oil spill models. This paper also sheds light on what drove the historical Point Wells spill, and serves the additional purpose of being a learning resource for those interested in oil spill modeling. The increasingly complex approach used for the comparison is also used, in parallel, to illustrate the approach an oil spill modeler would typically follow when trying to hindcast or forecast an oil spill, including detailed technical information on basic aspects, like choosing a computational time step. We discuss our successful hindcast of the 2003 Point Wells oil spill that, to our knowledge, had remained unexplained. The oil spill models’ solutions are compared to the historical Point Wells’ oil trajectory, in time and space, as determined from overflight information. Our hindcast broadly replicates the correct locations at the correct times, using accurate tide and wind forcing. While the choice of wind coefficient we use is unconventional, a simplified analytic model supported by observations, suggests that it is justified under this study’s circumstances. We highlight some of the key oceanographic findings as they may relate to other oil spills, and to the regional oceanography of the Salish Sea, including recommendations for future studies.

42 ENGINEERING↗

A system identification approach for non-intrusive reduced order modeling of radiation-induced photocurrents

In this study, development of compact photocurrent models is currently dominated by analytical techniques that rely on physical assumptions to render the governing equations solvable in a closed form. Violation of these assumptions can reduce the accuracy of the models and/or limit their scope. In this paper we show that system identification of nonlinear state-space systems can serve as an alternative numerical basis for non-intrusive reduced order modeling of photocurrent effects. To that end we develop a compact gray box photocurrent model (GBPM) by using a state-space representation with a low-dimensional latent state equation that mimics a mathematical model for the response of an idealized class of devices to ionizing radiation. In so doing we obtain a model that learns the dynamics of a quantity of interest directly from its measurements without requiring snapshots of the internal device state or its discretized model, and can be inferred from very small data sets. To demonstrate the approach we train the GBPM using a small experimental data set for a Z5236 Zener diode and a small synthetic data set obtained by simulating a synthetic pn-junction device. We then compare the GBPMs with black box models trained on the same data and show that performance of the latter is limited by the size of the data set, while the former are able to achieve excellent performance in both the reproductive and the predictive regimes.

97 MATHEMATICS AND COMPUTING↗

Strain Measurement of Geological Samples Subjected to Triaxial Stresses Experienced During Hydraulic Loading

Understanding stress and strain relationships and having the ability to predict these quantities for known load conditions is crucial to all geomechanical and, in some instances, reservoir flow applications. The constitutive equations governing the deformation of geological materials are typically adequate for bulk or large scale deformation and stress analyses. However, these rules are generally less precise in their ability to make accurate predictions in physical processes where highly localized material heterogeneity exists or where the presence of geometric irregularities such as micro-cracks may be present. This is especially relevant to EGS where hydraulic fracture propagation models are needed to develop optimal reservoir creation strategies and where fracture permeability is significantly influenced by regional stress states and may affect reservoir operation strategies. The deficiencies of the models used to describe these physical processes are a practical reality necessitated by the manner in which rock properties must be obtained. Conventional rock mechanics tests subject samples to controlled load conditions and measure bulk deformations of the sample or more localized deformations only on exposed surfaces of the sample. They are currently unable to comprehensively map the deformation state within the sample. For processes such as fracture, however, the state of a particular region within the rock drives the overall failure behavior of the sample. The authors believe that possessing a means to measure strains within samples subjected to hydraulic fracture loading conditions will provide a useful tool for understanding the localized effects not captured by conventional techniques and may serve as a method for improving hydraulic fracture models. An ongoing effort at Oak Ridge National Laboratory endeavors to develop a neutron diffraction based strain measurement capability to interrogate the strain state of a geological sample, at arbitrary internal locations, subjected to a triaxial stress state. The basis of the method and initial results for simple load conditions were reported at last year s Stanford Geothermal Workshop. This work will report results from recent neutron diffraction strain measurement experiments in which marble samples were subjected to load conditions more representative of hydraulic fracturing operations within a pressure cell specially designed for the reported strain measurement technique.

An, Ke↗

Cosmological constraints from DES Y1 cluster abundances and SPT multiwavelength data

We perform a joint analysis of the counts of redMaPPer clusters selected from the Dark Energy Survey (DES) year 1 data and multiwavelength follow-up data collected within the 2500 deg2 South Pole Telescope (SPT) Sunyaev-Zel’dovich (SZ) survey. The SPT follow-up data, calibrating the richness-mass relation of the optically selected redMaPPer catalog, enable the cosmological exploitation of the DES cluster abundance data. To explore possible systematics related to the modeling of projection effects, we consider two calibrations of the observational scatter on richness estimates: a simple Gaussian model which account only for the background contamination (BKG), and a model which further includes contamination and incompleteness due to projection effects (PRJ). Assuming either a ΛCDM+∑mν or wCDM+∑mν cosmology, and for both scatter models, we derive cosmological constraints consistent with multiple cosmological probes of the low and high redshift Universe, and in particular with the SPT cluster abundance data. This result demonstrates that the DES Y1 and SPT cluster counts provide consistent cosmological constraints, if the same mass calibration data set is adopted. It thus supports the conclusion of the DES Y1 cluster cosmology analysis which interprets the tension observed with other cosmological probes in terms of systematics affecting the stacked weak lensing analysis of optically selected low–richness clusters. Finally, we analyze the first combined optically SZ selected cluster catalog obtained by including the SPT sample above the maximum redshift probed by the DES Y1 redMaPPer sample (z=0.65). Besides providing a mild improvement of the cosmological constraints, this data combination serves as a stricter test of our scatter models: the PRJ model, providing scaling relations consistent between the two abundance and multiwavelength follow-up data, is favored over the BKG model.

79 ASTRONOMY AND ASTROPHYSICS↗