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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Isopod (inverse Optimization And Design): Moose-based Application For Performing Inverse Optimization On Multiphysics Modeling And Simulation

ISOPOD (InverSe OPtimizatiOn and Design) will be a MOOSE (Multiphysics Object Oriented Simulation Environment)-based framework which will iteratively estimate the parameters by minimizing the difference between simulated and experimental observables. While inverse optimization has long been used for parameter estimation, the unique feature of ISOPOD is rapid solution of new inverse problems, leading to accelerated Research, Development and Demonstration (RD&D) for complex parameter estimation problems. This will be achieved by extending the software structure of MOOSE to inverse optimization, as well as building on the unique automatic differentiation feature of MOOSE.

Munday, LynnB↗
DOE OSTI2015

SU-E-T-759: To Replan Or Not To Replan for Each Fraction Using Inverse Optimization for Multichannel Vaginal Cylinder

Purpose: This study investigates whether replanning each fraction for vaginal cuff HDR therapy using a multichannel cylinder (MC) and brachytherapy inverse optimization (BIO) provides dosimetric benefits to organs-at-risk (OAR). The goal was to appropriately cover the target and limit dose to OAR, as well as evaluate dosimetric changes for each fraction, while doing this in a timely and cost effective manner. Methods: From an initial selection of 57 patients that were treated with 3 fractions using a MC and BIO, a subset of n=12 patients was selected based on the criterion that one plan was used for all 3 fractions. A simulation CT was acquired prior to each fraction. CT scans for fractions 2 and 3 were fused to the initial CT. Contours for the bladder and rectum were manually drawn on CTs for all 3 fractions, and the clinical treatment volume (PTVeval) was defined. Cylinders were reconstructed using applicator modeling library, influencing time and cost effectiveness. Planning objectives were at least 95% prescription dose to 95% (D95%) of target volume and limiting high dose to OAR. Dose to 2 cm{sup 3} (D2cc) for each OAR was analyzed using a t-test. Results: This study concentrated on comparing 2cm{sup 3} of highest dose to OAR (D2cc), for each fraction for the plans that were used to treat all 3 fraction. Based on statistical analysis, using the initial plan for fractions 2 and 3 resulted in approximately 6% change to the highest D2cc of the bladder (p=0.03). Conclusion: Performing CT fusion and contours of each OAR on each fraction allows objective plan evaluation and supports decision making on the necessity of replanning based on improved dose sparing for OAR. Future studies will investigate the effects of replanning on maximum dose (D0.1cc) using the same physician-drawn OAR contours to avoid subjectivity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TH-C-12A-06: Feasibility of a MLC-Based Inversely Optimized Multi-Field Grid Therapy Technique

Purpose: Grid therapy (GT), which generates highly spatially modulated dose distributions, can deliver single- or hypo-fractionated radiotherapy for large tumors without causing significant toxicities. GT may be applied in combination with immunotherapy, in light of recent preclinical data of synergetic interaction between radiotherapy and immunotherapy. However, conventional GT uses only one field, which does not have the advantage of multi-fields in 3D conformal-RT or IMRT. We have proposed a novel MLC-based, inverse-planned multi-field 3D GT technique. This study aims to test its deliverability and dosimetric accuracy. Methods: A lattice of small spheres was created as the boost volume within a large target. A simultaneous boost IMRT plan with 8-Gy to the target and 20-Gy to the boost volume was generated in the Eclipse treatment planning system (AAA v10) with a HD120 MLC. Nine beams were used, and the gantry and couch angles were selected so that the spheres were perfectly aligned in every beams eye view. The plan was mapped to a phantom with dose scaled. EBT3 films were calibrated and used to measure the delivered dose. Results: The IMRT plan generated a highly spatially modulated dose distribution in the target. D95%, D50%, D5% for the spheres and the targets in Gy were 18.5, 20.0, 21.4 and 7.9, 9.8, 16.1, respectively. D50% for a 1cm ring 1cm outside the target was 2.9-Gy. Film dosimetry showed good agreement between calculated and delivered dose, with an overall gamma passing rate of 99.6% (3%/1mm). The point dose differences for different spheres varied from 1–6%. Conclusion: We have demonstrated the deliverability and dose calculation accuracy of the MLC-based inversely optimized multi-field GT technique, which achieved a brachytherapy-like dose distribution. Single-fraction high dose can be delivered to the spheres in a large target with minimal dose to the surrounding normal tissue.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-498: Energy Minimization and Dose-Volume Inverse Optimization in Prostate Cancer

Purpose: To compare dose-volume (DVH) and energy minimization-based (EM) optimization for prostate cancer cases. Methods: A dozen of prostate plans were retrospectively studied. For each case two IMRT plans were generated, one with DVH and the other with EM objective cost function. Those different objective functions were used only for the organs at risk (OARs), while target objectives were achieved through DVH cost functions. The plans used the same beam angles, maximum number of segments per plan, minimum segment area and MUs per segment. Both plans were normalized such that 95% of the PTV was covered by the same prescription dose. After prescription was achieved, doses to the OARs were iteratively lowered until the standard deviation of the dose across the PTV was ~3.5%. Plan quality was evaluated by several dose indices (DIs). A DI represents the dose delivered to certain volume of a structure. Tallied DIs were for rectum and bladder 10%, 40%, 60% volumes, and 1% volumes of the femoral heads as surrogate for maximum doses. Statistical significance in the differences among DIs was quantified with two-tailed paired t-tests. Results: On average EM plans performed better than DVH plans. Statistically significant dose reduction in rectum DI10, DI40, and DI60, were 2.6%, 25.7%, and 35.9%, respectively. For bladder DI10, DI40, and DI60 the differences were 1.1%, 20.8%, and 29.7%. Left and right femoral head DI1s were better by 33.8% and 27.8% in EM plans. The quoted dose reduction is with respect to EM absolute doses for the DIs. Conclusion: The performance of EM optimization with respect to DVH optimization is patient and DI dependent. While in some cases specific DIs were better with DVH optimization, on average the energy minimization allows better (ranging from 1% to ~40%) OAR sparing than DVH optimization. NIH-NCI.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Optimal Power Management of Battery Energy Storage Systems via Ensemble Kalman Inversion

Optimal power management of battery energy storage systems (BESS) is crucial for their safe and efficient operation. Numerical optimization techniques are frequently utilized to solve the optimal power management problems. However, these techniques often fall short of delivering real-time solutions for large-scale BESS due to their computational complexity. To address this issue, this paper proposes a computationally efficient approach. We introduce a new set of decision variables called power-sharing ratios corresponding to each cell, indicating their allocated power share from the output power demand. We then formulate an optimal power management problem to minimize the system-wide power losses while ensuring compliance with safety, balancing, and power supply-demand match constraints. To efficiently solve this problem, a parametrized control policy is designed and leveraged to transform the optimal power management problem into a parameter estimation problem. We then implement the ensemble Kalman inversion to estimate the optimal parameter set. The proposed approach significantly reduces computational requirements due to 1) the much lower dimensionality of the decision parameters and 2) the estimation treatment of the optimal power management problem. Finally, we conduct extensive simulations to validate the effectiveness of the proposed approach. The results show promise in accuracy and computation time compared with explored numerical optimization techniques.

Farakhor, Amir↗
DOE OSTI2016

Optimization-Based Approach for Joint X-Ray Fluorescence and Transmission Tomographic Inversion

Fluorescence tomographic reconstruction, based on the detection of photons coming from fluorescent emission, can be used for revealing the internal elemental composition of a sample. On the other hand, conventional X-ray transmission tomography can be used for reconstructing the spatial distribution of the absorption coefficient inside a sample. In this work, we integrate both X-ray fluorescence and X-ray transmission data modalities and formulate a nonlinear optimization-based approach for reconstruction of the elemental composition of a given object. This model provides a simultaneous reconstruction of both the quantitative spatial distribution of all elements and the absorption effect in the sample. Mathematically speaking, we show that compared with the single-modality inversion (i.e., the X-ray transmission or fluorescence alone), the joint inversion provides a better-posed problem, which implies a better recovery. Therefore, the challenges in X-ray fluorescence tomography arising mainly from the effects of self-absorption in the sample are partially mitigated. The use of this technique is demonstrated on the reconstruction of several synthetic samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

MOOSE Optimization Module Overview: Application to Residual Stress Inversion in Nuclear Fuel Plates

Manufacturing methods, material selections and unique plate geometries used in low enriched uranium plate fuels for the High Performance Research Reactor (HPRR) have led to concerns about the residual stresses effect on bond strength of the fuel/cladding interfaces and overall fuel performance under irradiation. The current HPRR plate fuel test program performed residual stress calculations using the contour method with experimental displacement data obtained by incrementally cutting the plate fuel. In this work, we use a gradient based inverse optimization module developed within the MOOSE framework to estimate normal and shear residual stresses within the plate fuels using displacement data taken from a cut placed in the HPRR fuel plate. These results are verified against residual stress calculations obtained from the contour method. The inversion protocol used in this work utilizes two meshes to separately discretize the physics and parameter space. This allows a fine mesh to be used to fully resolve the physics and geometry of the forward problem. A coarser mesh is used to resolve the parameter space with spatially varying mesh density determined from a sensitivity analysis. The adaptive resolution of the parameter space essentially has the effect of regularization as it is designed to achieve the bias-variance tradeoff.

42 ENGINEERING↗
DOE OSTI2024

Revealing Decision Conservativeness Through Inverse Distributionally Robust Optimization

This paper introduces Inverse Distributionally Robust Optimization (I-DRO) as a method to infer the conservativeness level of a decision-maker, represented by the size of a Wasserstein metric-based ambiguity set, from the optimal decisions made using Forward Distributionally Robust Optimization (F-DRO). By leveraging the Karush-Kuhn-Tucker (KKT) conditions of the convex F-DRO model, we formulate I-DRO as a bi-linear program, which can be solved using off-the-shelf optimization solvers. Additionally, this formulation exhibits several advantageous properties. We demonstrate that I-DRO not only guarantees the existence and uniqueness of an optimal solution but also establishes the necessary and sufficient conditions for this optimal solution to accurately match the actual conservativeness level in F-DRO. Furthermore, we identify three extreme scenarios that may impact I-DRO effectiveness. Our case study applies F-DRO for power system scheduling under uncertainty and employs I-DRO to recover the conservativeness level of system operators. Numerical experiments based on an IEEE 5-bus system and a realistic NYISO 11-zone system demonstrate I-DRO performance in both normal and extreme scenarios. An extended version of this paper with additional analyses is available at li2024revealing.

distributionally robust optimization↗
DOE OSTI2015

A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion

In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by three steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

SU-E-T-213: Comparison of Treatment Efficiency of Gamma Knife SRS Plans for Brain Metastases with Different Planning Methods

Purpose: To improve Gamma Knife SRS treatment efficiency for brain metastases and compare the differences of treatment time and radiobiological effects between two different planning methods of automatic filling and manual placement of shots with inverse planning. Methods: T1-weighted MRI images with gadolinium contrast from five patients with a single brain metastatic-lesion were used in this retrospective study. Among them, two were from primary breast cancer, two from primary melanoma cancer and one from primary prostate cancer. For each patient, two plans were generated in Leksell GammaPlan10.1.1 for radiosurgical treatment with a Leksell GammaKnife Perfexion machine: one with automatic filling, automatic sector configuration and inverse optimization (Method1); and the other with manual placement of shots, manual setup of collimator sizes, manual setup of sector blocking and inverse optimization (Method2). Dosimetric quality of the plans was evaluated with parameters of Coverage, Selectivity, Gradient-Index and DVH. Beam-on Time, Number-of-Shots and Tumor Control Probability(TCP) were compared for the two plans while keeping their dosimetric quality very similar. Relative reduction of Beam-on Time and Number-of-Shots were calculated as the ratios among the two plans and used for quantitative analysis. Results: With very similar dosimetric and radiobiological plan quality, plans created with Method 2 had significantly reduced treatment time. Relative reduction of Beam-on Time ranged from 20% to 51 % (median:29%,p=0.001), and reduction of Number-of-Shots ranged from 5% to 67% (median:40%,p=0.0002), respectively. Time of plan creation for Method1 and Method2 was similar, approximately 20 minutes, excluding the time for tumor delineation. TCP calculated for the tumors from differential DVHs did not show significant difference between the two plans (p=0.35). Conclusion: The method of manual setup combined with inverse optimization in LGP for treatment of brain metastatic lesions with the Perfexion can achieve significantly higher time efficiency without degrading treatment quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-F-19A-03: Dosimetric Advantages in Critical Structure Dose Sparing by Using a Multichannel Cylinder in High Dose Rate Brachytherapy to Treat Vaginal Cuff Cancer

Purpose: The multichannel cylindrical vaginal applicator is a variation of traditional single channel cylindrical vaginal applicator. The multichannel applicator has additional peripheral channels that provide more flexibility in the planning process. The dosimetric advantage is to reduce dose to adjacent organ at risk (OAR) such as bladder and rectum while maintaining target coverage with the dose optimization from additional channels. Methods: Vaginal HDR brachytherapy plans are all CT based. CT images were acquired in 2 mm thickness to keep integrity of cylinder contouring. The CTV of 5mm Rind with prescribed treatment length was reconstructed from 5mm expansion of inserted cylinder. The goal was 95% of CTV covered by 95% of prescribed dose in both single channel planning (SCP)and multichannel planning (MCP) before proceeding any further optimization for dose reduction to critical structures with emphasis on D2cc and V2Gy . Results: This study demonstrated noticeable dose reduction to OAR was apparent in multichannel plans. The D2cc of the rectum and bladder were showing the reduced dose for multichannel versus single channel. The V2Gy of the rectum was 93.72% and 83.79% (p=0.007) for single channel and multichannel respectively (Figure 1 and Table 1). To assure adequate coverage to target while reducing the dose to the OAR without any compromise is the main goal in using multichannel vaginal applicator in HDR brachytherapy. Conclusion: Multichannel plans were optimized using anatomical based inverse optimization algorithm of inverse planning simulation annealing. The optimization solution of the algorithm was to improve the clinical target volume dose coverage while reducing the dose to critical organs such as bladder, rectum and bowels. The comparison between SCP and MCP demonstrated MCP is superior to SCP where the dwell positions were based on geometric array only. It concluded that MCP is preferable and is able to provide certain features superior to SCP.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Bayesian optimization for inverse calibration of expensive computer models: A case study for Johnson-Cook model in machining

Inverse model calibration for identifying the constitutive model parameters can be computationally demanding for expensive-to-evaluate simulation models. Here, this paper presents a modified Bayesian optimization (BO) method, denoted as BO-bound, that incorporates theoretical bounds on the quantity of interest. A case study for the inverse calibration of the Johnson Cook (J-C) flow stress model parameters is presented using machining (cutting) force data. The results show fast calibration of the five J-C parameters within 25 simulations. In general, the BO-bound method is applicable for inverse calibration of any expensive simulation models as well as optimization problems with known bounds.

Bayesian optimization↗