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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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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↗
NASA NTRS2011

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Dubovik, O↗
NASA NTRS2024

Piezoelectric impedance-based high-accuracy damage identification using sparsity conscious multi-objective optimization inverse analysis

Two elements are essential in structural health monitoring utilizing dynamic responses: response measurement with high-frequency contents, i.e., small characteristic wavelengths, that can adequately reflect damage features, and effective inverse identification analysis that is however oftentimes under-determined. The advancement of smart structure integration has led to active interrogation through frequency-sweeping piezoelectric impedance measurement at high frequency range. In this research we develop a multi-objective optimization formulation for the identification of damage location and severity utilizing piezoelectric impedance. While one optimization objective is to match the response measurement with finite element model prediction in the damage parametric space, the other is the number of locations of damage, i.e., the sparsity of damage index as the solution vector, since damage usually occurs within a small number of locations. This multi-objective formulation fits well the under-determined nature of damage identification, as it naturally provides multiple solutions as basis for further elucidation. The challenge remaining is how to find a small solution set that can include the actual damage scenario. Here we develop a novel inverse identification framework utilizing the intelligent swarm optimizer which possesses flexibility for enhancement. We first embed a sparsity enforcement process into the population generation of the optimizer, which yields a solution repository intrinsically possessing sparsity. We then apply reinforcement learning so the agents can adaptively opt for local strategies with the aim of enriching the searching patterns to diversify the solutions. Through the incorporation of a Q-table, searching toward more promising directions will be rewarded. Our case analyses employing experimental data indicate that this sparsity-conscious multi-objective particle swarm optimization technique can lead to a small solution set which generally encompasses the true damage scenario. This effectively solves the structural damage identification problem with piezoelectric impedance measurement.

Yang Zhang↗
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↗
NASA NTRS1969

Towards an optimal inversion method for remote atmospheric sensing

The inference of atmospheric structure from satellite radiometric observations requires an inversion algorithm. A variety of techniques was spawned to meet these demands. One class, the nonlinear inversion methods, copes with the problem of data noise. Unlike linear techniques which require a priori data smoothing, the nonlinear method can be applied directly to raw data. The algorithm discriminates the noise input by resolving the inferences into two types of solution, associating the real roots with atmospheric structure while ascribing the imaginary roots to noise.

King, J. I. F.↗
NASA NTRS2023

Optimal Estimation Inversion of Ionospheric Electron Density from GNSS-POD Limb Measurements: Part II-Validation and Comparison Using NmF2 and hmF2

A growing number of SmallSat/CubeSat constellations with high-rate (50–100 Hz) global navigation satellite system radio occultations (GNSS-RO) as well as low-rate (1 Hz) precise orbit determination (GNSS-POD) limb-viewing capabilities provide unprecedented spatial and temporal sampling rates for ionospheric studies. In the F-region electron density (N 𝑒 ) retrieval process, instead of the conventional onion-peeling (OP) inversion, an optimal estimation (OE) inversion technique was recently developed using total electron content measurements acquired by GNSS-POD link. The new technique is applied to data acquired from the COSMIC-1, COSMIC-2, and Spire constellations. Although both OE and OP techniques use the Abel weighting function in N 𝑒 inversion, OE significantly differs in its performance, especially in the lower F- and E-regions. In this work, we evaluate and compare newly derived data sets using F2 peak properties with other space-based and ground-based observations. We determine the F2 peak N 𝑒 (NmF2) and its altitude (hmF2), and compare them with the OP-retrieved values. Good agreement is observed between the two techniques for both NmF2 and hmF2. In addition, we also utilize autoscaled F2 peak measurements from a number of worldwide Digisonde stations (∼30). The diurnal sensitivity and latitudinal variability of the F2 peak between the two techniques are carefully studied at these locations. Good agreement is observed between OE-retrieved NmF2 and Digisonde-measured NmF2. However, significant differences appear between OE-retrieved hmF2 and Digisonde-measured hmF2. During the daytime, Digisonde-measured hmF2 remains ∼25–45 km below the OE-retrieved hmF2, especially at mid and high latitudes. We also incorporate F-region N 𝑒 measurements from two incoherent scatter radar observations at high latitudes, located in the North American (Millstone Hill) and European (EISCAT at Tromso) sectors. The radar measurements show good agreement with OE-retrieved values. Although there are several possible sources of error in the ionogram-derived N 𝑒 profiles, our further analysis on F1 and F2 layers indicates that the low Digisonde hmF2 is caused by the autoscaled method, which tends to detect a height systematically below the F2 peak when the F1 layer is present.

GNSS radio occultation↗
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↗
NASA NTRS2018

Real-Time Adaptive Drag Minimization Wind Tunnel Investigation of a Flexible Wing with Variable Camber Continuous Trailing Edge Flap System

This paper reports the results of a recently completed real-time adaptive drag minimization wind tunnel investigation of a highly flexible wing wind tunnel model equipped with the Variable Camber Continuous Trailing Flap (VCCTEF) technology at the University of Washington Aeronautical Laboratory (UWAL). The wind tunnel investigation is funded by NASA SBIR Phase II contract with Scientific Systems Company, Inc. (SSCI) and University of Washington (UW) as a subcontractor. The wind tunnel model is a sub-scale Common Research Model (CRM) wing constructed of foam core and fiberglass skin and is aeroelastically scaled to achieve a wing tip deflection of 10% of the wing semi-span which represents a typical wing tip deflection for a modern transport such as Boeing 787. The jig-shape twist of the CRM wing is optimized using a CART3D aero-structural model to achieve the minimum induced drag for the design cruise lift coefficient of 0.5. The wing is equipped with two chord wise cambered segments for each of the six span wise flap sections for a total of 12 individual flap segments that comprise the VCCTEF system. Each of the 12 flap segments is actively controlled by an electric servo-actuator. The real-time adaptive drag optimization strategy includes an on-board aerodynamic model identification, a model excitation, and a real-time drag optimization. The on-board aerodynamic model is constructed parametrically as a function of the angle of attack and flap positions to model the lift and drag coefficients of the wing. The lift coefficient models include a linear model and a second-order model. The drag coefficient models include a quadratic model and a higher-order up to 6th-order model to accurately model the drag coefficient at high angles of attack. The onboard aerodynamic model identification includes a recursive least-squares (RLS) algorithm and a batch least-squares (BLS) algorithm designed to estimate the model parameters. The model excitation method is designed to sample the input set that comprises the angle of attack and the flap positions. Three model excitation methods are developed: random excitation method, sweep method, and iterative angle-of-attack seeking method. The real-time drag optimization includes a generic algorithm developed by SSCI and several optimization methods developed by NASA which include a second-order gradient Newton-Raphson optimization method, an iterative gradient optimization method, a pseudo-inverse optimization method, an analytical optimization method, and an iterative refinement optimization method. The first wind tunnel test entry took place in September 2017. This test revealed major hardware issues and required further redesign of the flap servo mechanisms. The second test entry took place in April 2018. However, the test was not successful due to the issues with the onboard aerodynamic model identification RLS algorithm which incorrectly identified model parameters. This test also provides an experimental comparison study between the VCCTEF and a variable camber discrete trailing edge flap (VCDTEF) without the elastomer transition mechanisms. The experimental result confirms the benefit of the VCCTEF which produces lower drag by 5% than the VCDTEF. The third and final test entry took place in June 2018 after the issues with the RLS algorithm have been identified and corrected. Additional improvements were implemented. These include the BLS algorithm, the iterative angle-of-attack seeking method, the iterative gradient optimization method, and the pseudo-inverse optimization method. The test objectives were successfully demonstrated as the real-time drag optimization identifies several optimal solutions at off-design lift coefficients. The iterative gradient optimization method is found to achieve up to 4.7% drag reduction for the off-design lift coefficient of 0.7. The pseudo-inverse optimization method which does not require the drag coefficient model is found to be quite effective in reducing drag. Up to 9.4% drag reduction for the off-design lift coefficient of 0.7 is achieved with the pseudo-inverse optimization method. The wind tunnel investigation demonstrates the potential of real-time drag optimization technology. Several new capabilities are developed that could enable future adaptive wing technologies for flexible wings equipped with drag control devices such as the VCCTEF.

Drag Optimization↗
NASA NTRS2023

Equivalent Area Targets for Inverse Design Optimization With Changing Low-Boom Cruise Conditions

This paper provides theoretical and numerical justifications for inverse design optimization of reversed equivalent area (A e,r ) of low-boom supersonic aircraft when the cruise condition changes during the optimization iterations. A modified linear theory for steady flow around a supersonic projectile is used to establish the accuracy of A e,r -based body-of-revolution approximation of a low-boom supersonic aircraft for undertrack sonic boom analysis using computational fluid dynamics off-body pressure. As a result, designing a low-boom shape of the off-body pressure at three body lengths below the aircraft is equivalent to designing a low-boom A e,r shape. A Bezier curve with eight control points is used to define an A e,r target for inverse design optimization of A e,r of a supersonic aircraft. To make an A e,r target matchable by a low-boom supersonic aircraft, the A e,r target must have the minimal perceived level of decibels (PLdB) for sonic boom and satisfy two constraints defined by the cruise condition, effective length, and two nondimensional parameters. Numerical results are used to verify that, for different cruise conditions, all optimized A e,r targets with PLdB below 70 can be approximately generated by scaling one of them if the targets have the same nondimensional parameters and approximately the same effective length.

multidisciplinary optimization↗