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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-C-BRD-03: Analysis of Accelerator Generated Text Logs for Preemptive Maintenance

Purpose: To develop a model to analyze medical accelerator generated parameter and performance data that will provide an early warning of performance degradation and impending component failure. Methods: A robust 6 MV VMAT quality assurance treatment delivery was used to test the constancy of accelerator performance. The generated text log files were decoded and analyzed using statistical process control (SPC) methodology. The text file data is a single snapshot of energy specific and overall systems parameters. A total of 36 system parameters were monitored which include RF generation, electron gun control, energy control, beam uniformity control, DC voltage generation, and cooling systems. The parameters were analyzed using Individual and Moving Range (I/MR) charts. The chart limits were calculated using a hybrid technique that included the use of the standard 3σ limits and the parameter/system specification. Synthetic errors/changes were introduced to determine the initial effectiveness of I/MR charts in detecting relevant changes in operating parameters. The magnitude of the synthetic errors/changes was based on: the value of 1 standard deviation from the mean operating parameter of 483 TB systems, a small fraction (≤ 5%) of the operating range, or a fraction of the minor fault deviation. Results: There were 34 parameters in which synthetic errors were introduced. There were 2 parameters (radial position steering coil, and positive 24V DC) in which the errors did not exceed the limit of the I/MR chart. The I chart limit was exceeded for all of the remaining parameters (94.2%). The MR chart limit was exceeded in 29 of the 32 parameters (85.3%) in which the I chart limit was exceeded. Conclusion: Statistical process control I/MR evaluation of text log file parameters may be effective in providing an early warning of performance degradation or component failure for digital medical accelerator systems. Research is Supported by Varian Medical Systems, Inc.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Simultaneous 3D–2D image registration and C-arm calibration: Application to endovascular image-guided interventions

Purpose: Three-dimensional to two-dimensional (3D–2D) image registration is a key to fusion and simultaneous visualization of valuable information contained in 3D pre-interventional and 2D intra-interventional images with the final goal of image guidance of a procedure. In this paper, the authors focus on 3D–2D image registration within the context of intracranial endovascular image-guided interventions (EIGIs), where the 3D and 2D images are generally acquired with the same C-arm system. The accuracy and robustness of any 3D–2D registration method, to be used in a clinical setting, is influenced by (1) the method itself, (2) uncertainty of initial pose of the 3D image from which registration starts, (3) uncertainty of C-arm’s geometry and pose, and (4) the number of 2D intra-interventional images used for registration, which is generally one and at most two. The study of these influences requires rigorous and objective validation of any 3D–2D registration method against a highly accurate reference or “gold standard” registration, performed on clinical image datasets acquired in the context of the intervention. Methods: The registration process is split into two sequential, i.e., initial and final, registration stages. The initial stage is either machine-based or template matching. The latter aims to reduce possibly large in-plane translation errors by matching a projection of the 3D vessel model and 2D image. In the final registration stage, four state-of-the-art intrinsic image-based 3D–2D registration methods, which involve simultaneous refinement of rigid-body and C-arm parameters, are evaluated. For objective validation, the authors acquired an image database of 15 patients undergoing cerebral EIGI, for which accurate gold standard registrations were established by fiducial marker coregistration. Results: Based on target registration error, the obtained success rates of 3D to a single 2D image registration after initial machine-based and template matching and final registration involving C-arm calibration were 36%, 73%, and 93%, respectively, while registration accuracy of 0.59 mm was the best after final registration. By compensating in-plane translation errors by initial template matching, the success rates achieved after the final stage improved consistently for all methods, especially if C-arm calibration was performed simultaneously with the 3D–2D image registration. Conclusions: Because the tested methods perform simultaneous C-arm calibration and 3D–2D registration based solely on anatomical information, they have a high potential for automation and thus for an immediate integration into current interventional workflow. One of the authors’ main contributions is also comprehensive and representative validation performed under realistic conditions as encountered during cerebral EIGI.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Addressing Issues with Working Memory in Video Object Segmentation

Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the internal memory state of the initial image-mask pair and past image-masks as a working memory buffer. While the current state of the art models perform very well on clean video data, their reliance on a working memory of previous frames leaves room for error. Affinity-based algorithms include the inductive bias that there is temporal continuity between consecutive frames. To account for inconsistent camera views of the desired object, working memory models need an algorithmic modification that regulates the memory updates and avoid writing irrelevant frames into working memory. A simple algorithmic change is proposed that can be applied to any existing working memory-based VOS model to improve performance on inconsistent views, such as sudden camera cuts, frame interjections, and extreme context changes. The resulting model performances show significant improvement on video data with these frame interjections over the same model without the algorithmic addition. Our contribution is a simple decision function that determines whether working memory should be updated based on the detection of sudden, extreme changes and the assumption that the object is no longer in frame. By implementing algorithmic changes, such as this, we can increase the real-world applicability of current VOS models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-T-798: Verification of 3DVH Dose Distribution Before Clinical Implementation for Patient-Specific IMRT QA

Purpose: In recent years patient-specific IMRT QA has transitioned from film and chamber measurements to beam-by-beam 2D array measurements. 3DVH takes this transition a step further by estimating the 3D dose distribution delivered using 2D per beam diode array measurements. In this study, the 3D dose distribution generated by 3DVH is compared to film and chamber measurements. In addition, the accuracy ROI volume and error detection is investigated. Methods: Composite film and ion chamber measurements in a solid water phantom were performed for 9 IMRT PINNACLE patient plans for 4 treatment sites. The film and chamber measurements were compared to the dose distribution predicted by 3DVH using MAPCHECK2 per beam measurements. The absolute point dose measurement (CAX) was extracted from the predicted 3DVH and PINNACLE dose distribution and was compared by taking the ratio of measured to predicted doses. The dose distribution measured with film was compared to the distribution in the corresponding plane (AX, SAG, COR) extracted from predicted dose distribution by 3DVH and PINNACLE using a 2D gamma analysis. Gamma analysis was performed with 2% dose, 2 mm DTA, 20% threshold, and global normalization. In addition, the percent difference between 3DVH and PINNACLE ROI volumes was calculated. Results: The average ratio of the measured point dose vs the 3DVH predicted dose was 1.017 (σ=0.011). The average gamma passing rate for measured vs 3DVH dose distributions was 95.1% (σ=2.53%). The average percent difference of 3DVH vs PINNACLE ROI volume was 2.29% (σ=2.5%). Conclusion: The dose distributions predicted by 3DVH using MAPCHECK2 measurements are the same as the distributions that would have been obtained using film and chamber. The ROI volumes used in 3DVH are not an exact match to those in PINNACLE; the effect requires more investigation. The accuracy of error detection by 3DVH is currently being investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Dynamic tumor tracking using the Elekta Agility MLC

Purpose: To evaluate the performance of the Elekta Agility multileaf collimator (MLC) for dynamic real-time tumor tracking. Methods: The authors have developed a new control software which interfaces to the Agility MLC to dynamically program the movement of individual leaves, the dynamic leaf guides (DLGs), and the Y collimators (“jaws”) based on the actual target trajectory. A motion platform was used to perform dynamic tracking experiments with sinusoidal trajectories. The actual target positions reported by the motion platform at 20, 30, or 40 Hz were used as shift vectors for the MLC in beams-eye-view. The system latency of the MLC (i.e., the average latency comprising target device reporting latencies and MLC adjustment latency) and the geometric tracking accuracy were extracted from a sequence of MV portal images acquired during irradiation for the following treatment scenarios: leaf-only motion, jaw + leaf motion, and DLG + leaf motion. Results: The portal imager measurements indicated a clear dependence of the system latency on the target position reporting frequency. Deducting the effect of the target frequency, the leaf adjustment latency was measured to be 38 ± 3 ms for a maximum target speed v of 13 mm/s. The jaw + leaf adjustment latency was 53 ± 3 at a similar speed. The system latency at a target position frequency of 30 Hz was in the range of 56–61 ms for the leaves (v ≤ 31 mm/s), 71–78 ms for the jaw + leaf motion (v ≤ 25 mm/s), and 58–72 ms for the DLG + leaf motion (v ≤ 59 mm/s). The tracking accuracy showed a similar dependency on the target position frequency and the maximum target speed. For the leaves, the root-mean-squared error (RMSE) was between 0.6–1.5 mm depending on the maximum target speed. For the jaw + leaf (DLG + leaf) motion, the RMSE was between 0.7–1.5 mm (1.9–3.4 mm). Conclusions: The authors have measured the latency and geometric accuracy of the Agility MLC, facilitating its future use for clinical tracking applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Quantitative comparison of electron temperature fluctuations to nonlinear gyrokinetic simulations in C-Mod Ohmic L-mode discharges

Long wavelength turbulent electron temperature fluctuations (k{sub y}ρ{sub s} < 0.3) are measured in the outer core region (r/a > 0.8) of Ohmic L-mode plasmas at Alcator C-Mod [E. S. Marmar et al., Nucl. Fusion 49, 104014 (2009)] with a correlation electron cyclotron emission diagnostic. The relative amplitude and frequency spectrum of the fluctuations are compared quantitatively with nonlinear gyrokinetic simulations using the GYRO code [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] in two different confinement regimes: linear Ohmic confinement (LOC) regime and saturated Ohmic confinement (SOC) regime. When comparing experiment with nonlinear simulations, it is found that local, electrostatic ion-scale simulations (k{sub y}ρ{sub s} ≲ 1.7) performed at r/a ∼ 0.85 reproduce the experimental ion heat flux levels, electron temperature fluctuation levels, and frequency spectra within experimental error bars. In contrast, the electron heat flux is robustly under-predicted and cannot be recovered by using scans of the simulation inputs within error bars or by using global simulations. If both the ion heat flux and the measured temperature fluctuations are attributed predominantly to long-wavelength turbulence, then under-prediction of electron heat flux strongly suggests that electron scale turbulence is important for transport in C-Mod Ohmic L-mode discharges. In addition, no evidence is found from linear or nonlinear simulations for a clear transition from trapped electron mode to ion temperature gradient turbulence across the LOC/SOC transition, and also there is no evidence in these Ohmic L-mode plasmas of the “Transport Shortfall” [C. Holland et al., Phys. Plasmas 16, 052301 (2009)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

How Accurate Are the Minnesota Density Functionals for Noncovalent Interactions, Isomerization Energies, Thermochemistry, and Barrier Heights Involving Molecules Composed of Main-Group Elements?

The 14 Minnesota density functionals published between the years 2005 and early 2016 are benchmarked on a comprehensive database of 4986 data points (84 data sets) involving molecules composed of main-group elements. The database includes noncovalent interactions, isomerization energies, thermochemistry, and barrier heights, as well as equilibrium bond lengths and equilibrium binding energies of noncovalent dimers. Additionally, the sensitivity of the Minnesota density functionals to the choice of basis set and integration grid is explored for both noncovalent interactions and thermochemistry. By and large, the main strength of the hybrid Minnesota density functionals is that the best ones provide very good performance for thermochemistry (e.g., M06-2X), barrier heights (e.g., M08-HX, M08-SO, MN15), and systems heavily characterized by self-interaction error (e.g., M06-2X, M08-HX, M08-SO, MN15), while the main weakness is that none of them are state-of-the-art for the full spectrum of noncovalent interactions and isomerization energies (although M06-2X is recommended from the 10 hybrid Minnesota functionals). Similarly, the main strength of the local Minnesota density functionals is that the best ones provide very good performance for thermochemistry (e.g., MN15-L), barrier heights (e.g., MN12-L), and systems heavily characterized by self-interaction error (e.g., MN12-L and MN15-L), while the main weakness is that none of them are state-of-the-art for the full spectrum of noncovalent interactions and isomerization energies (although M06-L is clearly the best from the four local Minnesota functionals). Finally, as an overall guide, M06-2X and MN15 are perhaps the most broadly useful hybrid Minnesota functionals, while M06-L and MN15-L are perhaps the most broadly useful local Minnesota functionals, although each has different strengths and weaknesses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Code and Solution Verification Assessment of the CTF Thermal Hydraulic Subchannel Code

CTF is a thermal-hydraulics subchannel code jointly developed by Oak Ridge National Laboratory and North Carolina State University. Over the past seven years, the Consortium for Advanced Simulation of Light Water Reactors (CASL) has made a significant investment in developing CTF so it can be used to model light water reactors, including nominal operating conditions, departure from nucleate boiling analysis, and transients ranging from loss of flow to reactivity insertion accidents. In addition to implementing new modeling capabilities and developing the user input and output interface, extensive work has been performed to improve the code’s quality assurance program, resulting in a development process that conforms with NQA-1 requirements. The CASL program follows the Predictive Capability Maturity Model (PCMM) approach for assessing code quality, which emphasizes performing code verification(ensuring the code converges to the correct answer) and solution verification (ensuring the code converges for the intended application). Code and solution verification are used to identify uncertainty errors introduced by numerical approximations in the code and are important for demonstrating that the model is coded without error, which is an important aspect of the Best Estimate plus Uncertainty method. This paper presents a comprehensive overview of the code and solution verification testing that has been performed on CTF. A top-down approach is taken in which the intended CTF applications are presented, followed by the code features required for their modeling. These features are then linked to the applicable code and solution verification tests that demonstrate proper functioning. Past testing efforts are summarized, and new tests are added to help close gaps in the presented test matrix. Rather than performing “one-off” exercises, these tests are added to the automated CTF regression test suite to ensure continual code quality.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

The Optical Corrector for the Dark Energy Spectroscopic Instrument

The Dark Energy Spectroscopic Instrument (DESI) is currently measuring the spectra of 40 million galaxies and quasars, the largest such survey ever made to probe the nature of cosmological dark energy. The 4 m Mayall telescope at Kitt Peak National Observatory has been adapted for DESI, including the construction of a 3$_{.}^{°}$2 diameter prime focus corrector that focuses astronomical light onto a 0.8 m diameter focal surface with excellent image quality over the DESI bandpass of 360–980 nm. The wide-field corrector includes six lenses, as large as 1.1 m in diameter and as heavy as 237 kilograms, including two counterrotating wedged lenses that correct for atmospheric dispersion over zenith angles from 0° to 60°. The lenses, cells, and barrel assembly all meet precise alignment tolerances on the order of tens of microns. The barrel alignment is maintained throughout a range of observing angles and temperature excursions in the Mayall dome by use of a hexapod, which is itself supported by a new cage, ring, and truss structure. In this paper we describe the design, fabrication, and performance of the new corrector and associated structure, focusing on how they meet DESI requirements. In particular, we describe the prescription and specifications of the lenses, design choices and error budgeting of the barrel assembly, stray light mitigations, and integration and test at the Mayall telescope. We conclude with some validation highlights that demonstrate the successful corrector on-sky performance, and we list some lessons learned during the multiyear fabrication phase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A Chip-Scale Oscillation-Mode Optomechanical Inertial Sensor Near the Thermodynamical Limits

Modern navigation systems integrate the global positioning system (GPS) with an inertial navigation system (INS), which complement each other for correct attitude and velocity determination. Here, the core of the INS integrates accelerometers and gyroscopes used to measure forces and angular rate in the vehicular inertial reference frame. With the help of gyroscopes and by integrating the acceleration to compute velocity and distance, precision and compact accelerometers with sufficient accuracy can provide small–error location determination. Solid–state implementations, through coherent readout, can provide a platform for high performance acceleration detection. In contrast to prior accelerometers using piezoelectric or capacitive readout techniques, optical readout provides narrow–linewidth high–sensitivity laser detection along with low–noise resonant optomechanical transduction near the thermodynamical limits. Here an optomechanical inertial sensor with an 8.2 µg Hz –1/2 velocity random walk (VRW) at an acquisition rate of 100 Hz and 50.9 µg bias instability is demonstrated, suitable for applications, such as, inertial navigation, inclination sensing, platform stabilization, and/or wearable device motion detection. Driven into optomechanical sustained–oscillation, the slot photonic crystal cavity provides radio–frequency readout of the optically–driven transduction with an enhanced 625 µg Hz –1 sensitivity. Measuring the optomechanically–stiffened oscillation shift, instead of the optical transmission shift, provides a 220× VRW enhancement over pre–oscillation mode detection.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

High-precision control of tracked field robots in the presence of unknown traction coefficients

Accurate steering through crop rows that avoids crop damage is one of the most important tasks for agricultural robots utilized in various field operations, such as monitoring, mechanical weeding, or spraying. In practice, varying soil conditions can result in off-track navigation due to unknown traction coefficients so that it can cause crop damage. To address this problem, this work presents the development, application, and experimental results of a real-time receding horizon estimation and control (RHEC) framework applied to a fully autonomous mobile robotic platform to increase its steering accuracy. Recent advances in cheap and fast microprocessors, as well as advances in solution methods for nonlinear optimization problems, have made nonlinear receding horizon control (RHC) and receding horizon estimation (RHE) methods suitable for field robots that require high-frequency (milliseconds) updates. A real-time RHEC framework is developed and applied to a fully autonomous mobile robotic platform designed by the authors for in-field phenotyping applications in sorghum fields. Nonlinear RHE is used to estimate constrained states and parameters, and nonlinear RHC is designed based on an adaptive system model that contains time-varying parameters. The capabilities of the real-time RHEC framework are verified experimentally, and the results show an accurate tracking performance on a bumpy and wet soil field. Finally, the mean values of the Euclidean error and required computation time of the RHEC framework are equal to 0.0423 m and 0.88 ms, respectively.

42 ENGINEERING↗
DOE OSTI2025

Heterogeneous Mixtures of Dictionary Functions to Approximate Subspace Invariance in Koopman Operators: Why Deep Koopman Operators Work

Abstract Koopman operators model nonlinear dynamics as a linear dynamic system acting on a nonlinear function as the state. This nonstandard state is often called a Koopman observable and is usually approximated numerically by a superposition of functions drawn from a dictionary . In a widely used algorithm, extended dynamic mode decomposition (EDMD), the dictionary functions are drawn from a fixed class of functions. Deep learning combined with EDMD has been used to learn novel dictionary functions in an algorithm called deep dynamic mode decomposition (deepDMD). The learned representation both (1) accurately models and (2) scales well with the dimension of the original nonlinear system. In this paper, we analyze the learned dictionaries from deepDMD and explore the theoretical basis for their strong performance. We explore State-Inclusive Logistic Lifting (SILL) dictionary functions to approximate Koopman observables. Error analysis of these dictionary functions show they satisfy a property of subspace approximation, which we define as uniform finite approximate closure. Typically, a Koopman dictionary’s nonlinear functions are homogeneous. In this paper, we discover that structured mixing of heterogeneous dictionary functions drawn from different classes of nonlinear functions achieve the same accuracy and dimensional scaling as the deep-learning-based deepDMD algorithm Yeung et al. ( In: 2019 American Control Conference (ACC), 2019). We specifically show this by building a heterogeneous dictionary comprised of SILL functions and conjunctive radial basis functions (RBFs). This mixed dictionary achieves similar accuracy and dimensional scaling to deepDMD with an order of magnitude reduction in parameters, while maintaining geometric interpretability. These results strengthen the viability of dictionary-based Koopman models to solving high-dimensional nonlinear learning problems.

Johnson, Charles A.↗
DOE OSTI2020

Reinforcement learning based automated history matching for improved hydrocarbon production forecast

History matching aims to find a numerical reservoir model that can be used to predict the reservoir performance. An engineer and model calibration (data inversion) method are required to adjust various parameters/properties of the numerical model in order to match the reservoir production history. In this study, we develop deep neural networks within the reinforcement learning framework to achieve automated history matching that will reduce engineers’ efforts, human bias, automatically and intelligently explore the parameter space, and remove the need of large set of labeled training data. To that end, a fast-marching-based reservoir simulator is encapsulated as an environment for the proposed reinforcement learning. The deep neural-network-based learning agent interacts with the reservoir simulator within reinforcement learning framework to achieve the automated history matching. Reinforcement learning techniques, such as discrete Deep Q Network and continuous Deep Deterministic Policy Gradients, are used toth, used to train the learning agents. The continuous actions enable the Deep Deterministic Policy Gradients to explore more states at each iteration in a a learning episode; consequently, a better history matching is achieved using this algorithm as compared to Deep Q Network. For simplified dual-target composite reservoir models, the best history-matching performances of the discrete and continuous learning methods in terms of normalized root mean square errors are 0.0447 and 0.0038, respectively. Furthermore, our study shows that continuous action space achieved by the deep deterministic policy gradient drastically outperforms deep Q network.

42 ENGINEERING↗
DOE OSTI2022

Quantitative evaluations of subtropical westerly jet simulations over East Asia based on multiple CMIP5 and CMIP6 GCMs

As a salient feature of the Asian monsoon system, the East Asian subtropical westerly jet (EASWJ) exerts significant impacts on weather and climate changes in China and even throughout East Asia. In this paper, we applied a new self-adaptive algorithm to detect the EASWJ, identify its boundaries, and then represent its characteristics by defining three indices: the intensity index, meridional displacement index, and width index. Compared to the reanalysis data, we carried out a comprehensive, objective, and quantitative EASWJ evaluation using historical experiments from multiple global climate models (GCMs) in the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6). The results show that the multimodel ensemble mean (MME) of both CMIP5 and CMIP6 can simulate the characteristics of winter EASWJ well. While for the other three seasons, the MME of both phase models underestimate the 200-hPa zonal wind (U200) strength in the jet coverage area and overestimate the U200 outside the jet area, such simulation results weaken the meridional shear of the wind field. The EASWJ simulations from the CMIP5 GCMs had no consistent intensity or location characteristic tendencies, and most CMIP5 GCMs tended to simulate relatively wide-coverage jets. In contrast, most CMIP6 GCMs are inclined to simulate significantly weaker, wider, and more-northward jets. Compared to the predecessors in CMIP5, about half of CMIP6 GCMs significantly minimized the jet intensity bias, but remarkable errors were still observed in their jet location and coverage representations. Furthermore, the comparative analysis performed by classifying models based on their evaluated simulation results suggested that the simulated performance of the meridional temperature gradient was important for capturing the EASWJ characteristics. Further in-depth study of the causes of model differences is warranted to improve simulation results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Force field for calcium sulfate minerals to predict structural, hydration, and interfacial properties

Calcium sulfates such as anhydrite, hemihydrate, and gypsum find widespread use in building materials, implants, and tissue healing. We introduce a simple and compatible atomistic force field for all calcium sulfate phases that reproduces a wide range of experimental data including lattice parameters, surface, hydration, mechanical, and thermal properties in 1% to 5% accuracy relative to experiments. The performance is several times better than prior force fields and DFT methods, which lead to errors in structures and energies up to 100%. We explain (hkl) cleavage energies, the dynamics of (hkl) water interfaces, and new insights into molecular origins of crystal-facet specific hydration and solubility. Impressive agreement of computed and experimentally measured hydration energies is shown. The models add to the Interface force field (IFF) and are compatible with multiple force fields (CHARMM, AMBER, GROMOS, CVFF, PCFF, OPLS-AA) for property predictions of sulfate-containing materials from atoms to the large nanometer scale.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Frankenstein’s ROMster: Avoiding pitfalls of reduced-order model development

Reduced-order models (ROMs) are a widely used and powerful approach to reducing the complexity of predictive physics-based numerical simulations for a wide range of applications, including electronics and fluid mechanics such as geologic CO 2 sequestration (GCS). ROMs are critical for optimization, sensitivity analysis, model calibration and uncertainty quantification where full-order models cannot be feasibly executed many times. Traditional approaches generate a single ROM for each simulated response (e.g., CO 2 injection rates, pH changes) based on a set of training simulations. Here, we demonstrate that a single ROM can display excellent overall predictive statistics, but have predictions that dramatically and unacceptably deviate from simulator responses especially when the response variable has a large range (i.e., vary over multiple orders of magnitude). For example, we show that a traditional statistically-high-performing GCS ROM (coefficient of determination R 2 of 0.99) can have average absolute relative errors of over 200%. To address this, we propose a new and novel approach where a set of sub-ROMs are generated to overcome the potential pitfalls in traditional single ROM development. The effectiveness of the proposed approach—the ROMster framework—is demonstrated using a case study of predicted CO 2 injection rates for GCS. We find our approach is a robust and general framework for ROM development, reducing the average “error” from 200% to only 4% in our case study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

gLaSDI: Parametric physics-informed greedy latent space dynamics identification

A parametric adaptive physics-informed greedy Latent Space Dynamics Identification (gLaSDI) method is proposed for accurate, efficient, and robust data-driven reduced-order modeling of high-dimensional nonlinear dynamical systems. In the proposed gLaSDI framework, an autoencoder discovers intrinsic nonlinear latent representations of high-dimensional data, while dynamics identification (DI) models capture local latent-space dynamics. Here, an interactive training algorithm is adopted for the autoencoder and local DI models, which enables identification of simple latent-space dynamics and enhances accuracy and efficiency of data-driven reduced-order modeling. To maximize and accelerate the exploration of the parameter space for the optimal model performance, an adaptive greedy sampling algorithm integrated with a physics-informed residual-based error indicator and random-subset evaluation is introduced to search for the optimal training samples on the fly. Further, to exploit local latent-space dynamics captured by the local DI models for an improved modeling accuracy with a minimum number of local DI models in the parameter space, a -nearest neighbor convex interpolation scheme is employed. The effectiveness of the proposed framework is demonstrated by modeling various nonlinear dynamical problems, including Burgers equations, nonlinear heat conduction, and radial advection. The proposed adaptive greedy sampling outperforms the conventional predefined uniform sampling in terms of accuracy. Compared with the high-fidelity models, gLaSDI achieves 17 to 2,658× speed-up with 1 to 5% relative errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Numerical simulation of NSLS-II fast orbit feedback system

We discuss recent work on the construction of a numerical simulation of the fast orbit feedback system at NSLS-II. The simulation operates in the time domain and also includes the spatial domain, i.e. all beam position monitors (BPMs) and correctors. It can accept inputs of the real beam orbit and the measured orbit response matrix. It can also add errors to every stage of the calculation. We present methods to verify the simulation results by comparing the simulation results with experimental data collected at NSLS-II. The results are in very good agreement. The effects of errors from BPMs and correctors, as well as the amplitude of excitation, on the feedback performance, are also explored. This simulation can be used to predict the behavior and performance of the system for a future upgrade.

36 MATERIALS SCIENCE↗