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Results for “Inverse Optimization”

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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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

TH-A-BRF-03: Evaluation of Synthetic CTs Generated Using MR-SIM Data

Purpose: To describe and evaluate a novel algorithm for generating synthetic CT images from MR-SIM data for dose calculations in MR-only treatment planning. Methods: A voxel-based weighted summation method was implemented to generate synthetic CT (synCT) images. MR data were acquired using Philips 1.0T Panorama high-field open MR-SIM. Retrospective patient data from seven prostate patients and one brain patient (three lesions) enrolled in an IRB-approved study were used. 3D T1-weighted fast field echo and 3D T2-weighted turbo spin echo sequences were utilized for all patients. A 3D balanced turbo field echo sequence using spectral presaturation with inversion recovery was acquired for prostate patients, but 3D ultra-short echo time (UTE)-DIXON was instead acquired for the brain patient to amplify bone signal for semi-automatic bone segmentation. Weight optimization was performed using a training subset of patients. HU value differences between planning CT and synCTs were analyzed using mean absolute error (MAE). Original patient CT-based treatment plans were mapped onto synCTs, dose was recalculated using original leaf motion and MU values, and DRRs were generated. Dosevolume metrics and gamma analysis were used for dosimetric evaluation. Results: Average whole-body MAE of synCTs across all patients was 75+12 HU. In prostate cancer patients, average HU difference between planning and synCTs was 0.9±1.0% for soft tissue structures and 4.3±2.5% for bony structures. DRRs were generated from synCTs and qualitatively showed good geometric agreement with planning CT-generated DRRs. D99, mean dose, and maximum dose to CTV calculated using the synCT remained within 1.2% of planning CT-based dose calculations. All gamma analysis evaluated at 2%/2mm dose difference/distance to agreement) pass rates were greater than 95% with an average of 99.9±0.1% for prostate patients and 98.4±2.2% for three brain lesions. Conclusion: SynCTs were generated with clinically acceptable accuracy comparable to planning CTs, enabling dose computations for MR-only simulation. Research supported in part by a grant from Philips HealthCare (Best, Netherlands)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

High-Efficiency Solar-To-Fuel Photoelectrochemistry in Disordered Photonic Glass Electrodes (Final Technical Report)

This project investigated how photonic glass (PG) photoelectrodes—disordered arrangements of dielectric scatterers—can serve as scalable, tunable platforms for light trapping in photoelectrochemical (PEC) solar-to-fuel systems. By leveraging disorder-driven optical phenomena such as multiple scattering resonances and light localization, PG structures offer an alternative to conventional photonic crystals and inverse opals that require high structural precision. The scientific goals were to twofold: (1) develop approaches to predictive models for high performance PG electrodes based on light absorption simulations, and (2) fabricate, characterize, and optimize PG-based photoelectrodes for solar-to-hydrogen and solar-to-fuel photoelectrochemical applications. To overcome the complexity of ensemble optical simulations for disordered materials, the researchers developed a machine-learning-accelerated emulation of all configurations in the design space. With this approach, PG photoelectrodes based on a TiO2 semiconductor were designed to enhance PEC currents of up to one hundred times higher than the equivalent ultra-thin film photoanodes and several times higher than the equivalent photonic crystal. The research also explored integrated systems for electrochemical hydrogen production based on replacing water oxidation with the specific glycerol oxidation electrocatalysis. Overall, the project outlined an approach to a simple-to-fabricate photoelectrode system to drive photoelectrochemical reactions relevant to solar photochemical energy conversion.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Feasibility Study of a Multi Tilt-rotor Aircraft as the Artemis Lunar Training Vehicle

The Lunar Landing Research Vehicles (LLRVs) and the Lunar Landing Training Vehicles (LLTVs) provided astronaut candidates for the Apollo program with essential experience and confidence required to complete the missions, and contributed to six successful manned landings on the moon. The primary challenge in terrestrial training was being able to replicate the ratio of bank angle to linear acceleration that a pilot would experience in lunar gravity. Presently, as the Artemis program seeks to return humans to the Moon by 2025, engineers are evaluating suitable platforms to serve as an In-Flight Trainer (IFT) or Artemis Lunar Training Vehicle (ALTV) for astronauts training in the task of manual landing. The program is investigating the viability of current technology in the field of electric vertical takeoff and landing (eVTOL) vehicles and is evaluating using a multi tilt-rotor aircraft platform as a candidate platform for a preliminary ALTV. The tilt-rotor capability enables the vehicle attitude to be decoupled from its flight path, which is a crucial requirement in realistically simulating lunar gravity on Earth. Other key considerations include compensating for a lack of aerodynamic forces while flying through the atmosphere of Earth, as well as the ability to simulate the dynamics of multiple different lander designs for the Human Landing System (HLS) program. This paper details the feasibility study and presents a preliminary flight control architecture for an IFT based on a notional multi tilt-rotor platform. The modeling-following control law, based on nonlinear dynamic inversion (NDI), removes the need for gain scheduling because the vehicle operates across a wide range of flight conditions. The inner-loop dynamic control allocation strategy consists of a static portion that is optimized offline for trim while compensating for the difference in gravity and a dynamic portion that is computed in real time. The reference model consists of the full closed-loop dynamics of a generic HLS design. The modularity of the flight control architecture enables evaluation of multiple HLS concepts with minimal modifications to the control law. Simulation results of the multi tilt-rotor configuration following the final portion of the Apollo 11 descent trajectory are shown.

Jing Pei↗
NASA NTRS1991

Recent progress in inverse methods in France

Given the current level of jet engine performance, improvement of the various turbomachinery components requires the use of advanced methods in aerodynamics, heat transfer, and aeromechanics. In particular, successful blade design can only be achieved via numerical design methods which make it possible to reach optimized solutions in a much shorter time than ever before. Two design methods which are currently being used throughout the French turbomachinery industry to obtain optimized blade geometries are presented. Examples are presented for compressor and turbine applications. The status of these methods as far as improvement and extension to new fields of applications is also reported.

Bry, Pierre-Francois↗
DOE OSTI2022

Inverse design of plasma metamaterial devices with realistic elements

In an expansion of a previous study, we apply inverse design methods to produce two-dimensional plasma metamaterial devices with realistic plasma elements which incorporate quartz envelopes, collisionality (loss), non-uniform density profiles, and resistance to experimental error/perturbation. Finite difference frequency domain simulations are used along with forward-mode differentiation to design waveguides and demultiplexers operating under the transverse magnetic polarization. Additionally, optimal devices with realistic elements are compared to previous devices with idealized elements, and several parameter initialization schemes for the optimization algorithm are explored, yielding a robust procedure for producing such devices. Demultiplexing and waveguiding are demonstrated for microwave-regime devices composed of plasma elements with reasonable space-averaged plasma frequencies ~10GHz and a collision frequency ~1 GHz, allowing for future in-situ training and experimental realization of these designs.

42 ENGINEERING↗
DOE OSTI2018

J-variational inequalities and zeroes of a family of maximal monotone operators by sunny generalized nonexpansive retraction

In this paper, using generalized resolvents and retractions onto shrinking closed subsets, we present new extragradient algorithms for finding the solution of a J-variational-like inequality, the zero points of a family of maximal monotone operators, and the solution set of mixed equilibrium problems for a J-α-inverse-strongly monotone-like operator in a 2-uniformly convex and 2-uniformly smooth Banach space. By introducing the new definitions, we prove strong convergence of generated iterates in the extragradient methods. Using FMINCON optimization toolbox in MATLAB, we give some numerical examples and compare them with several existence results in the literature to illustrate the usability of our results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Smartphone-based Dual-channel Immunochromatographic Test Strip with Polymer Quantum Dot Labels for Simultaneous Detection of Cypermethrin and 3-phenoxybenzoic acid

Currently, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) are the primary methods used to detect pesticides and their metabolites for biomonitoring of exposure. Although GC-MS and LC-MS can provide accurate and sensitive measurements, these techniques are not suitable for point-of-care or in-field biomonitoring applications. The objective of this work is to develop a smartphone-based dual-channel immunochromatographic test strip (ICTS) for on-site biomonitoring of exposure to cypermethrin by simultaneous detection of cypermethrin and its metabolite, 3-phenoxybenzoic acid (3-PBA). Polymer carbon dots (PCDs) with ultra-high fluorescent brightness were synthesized and used as signal amplifier in ICTS assay. Cypermethrin (a representative pyrethroid pesticide) and its major metabolite 3-PBA were simultaneously detected to provide more comprehensive analysis of cypermethrin exposure. After competitive immunoreactions between the target sample and the coating antigens preloaded on the test line, the tracer antibody (PCDs conjugated antibody) was quantitatively captured on the test lines. The captured PCDs were inversely proportional to the amount of the target compound in sample. The red fluorescence on the test line then was recorded by a smartphone-based device capable of conducting image analysis and recording. Under optimal conditions, the sensor showed excellent linear responses for detecting cypermethrin and 3-PBA ranging from 1 ng/mL to 100 ng/mL and from 0.1 ng/mL to 100 ng/mL, the limits of detection were calculated to be ~0.35 ng/mL for cypermethrin and ~0.04 ng/mL for 3-PBA, respectively. The results demonstrate that the ICTS device is promising for accurate point-of-care biomonitoring of pesticide exposure.

Zhao, Yuting↗
DOE OSTI2014

Effect of internal noise on the oscillation of N{sub 2}O decomposition over Cu-ZSM-5 zeolites using a stochastic description

When considering stochastic oscillations of heterogeneous catalyst systems, most researches have focused on the surface of a metal or its oxide catalysts, but there have been few studies on porous catalysts. In this work, the effects of internal noise on oscillations of N{sub 2}O decomposition over Cu-ZSM-5 zeolites are investigated, using the chemical Langevin equation and a mesoscopic stochastic model. Considering that Cu-ZSM-5 particles are finely divided particles, the number of Cu ions (N{sub s}) is proportional to the particle size at a certain Cu/Al, and the internal noise is inversely proportional to N{sub s}. Stochastic oscillations can be observed outside the deterministic oscillatory region. Furthermore, the performance of the oscillation characterized by the signal-to-noise ratio has a maximum within the optimal size range of 4–8 nm. This suggests that a nanometer-sized zeolite may be best for oscillations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

3D radiated power analysis of JET SPI discharges using the Emis3D forward modeling tool

Abstract Precise values for radiated energy in tokamak disruption experiments are needed to validate disruption mitigation techniques for burning plasma tokamaks like ITER and SPARC. Control room analysis of radiated power ( P rad ) on JET assumes axisymmetry, since fitting 3D radiation structures with limited bolometry coverage is an under-determined problem. In mitigated disruptions, radiation is toroidally asymmetric and 3D, due to fast-growing 3D MHD modes and localized impurity sources. To address this problem, Emis3D adopts a physics motivated forward modeling (‘guess and check’) approach, comparing experimental bolometry data to synthetic data from user-defined radiation structures. Synthetic structures are observed with the Cherab modeling framework and a best fit chosen using a reduced χ 2 statistic. 2D tomographic inversion models are tested, as well as helical flux tubes and 3D MHD simulated structures from JOREK. Two nominally identical pure neon shattered pellet injection (SPI) mitigated discharges in JET are analyzed. 2D tomographic inversions with added toroidal freedom are the best fits in the thermal quench (TQ) and current quench (CQ). In the pre-TQ, 2D reconstructions are statistically the best fits, but are likely over-optimized and do not capture the 3D radiation structure seen in fast camera images. The next-best pre-TQ fits are helical structures that extend towards the high-field side, consistent with an impurity flow under the magnetic nozzle effect also observed in JOREK simulations. Whole-disruption radiated fractions of 0.98 + 0.03 / − 0.29 and 1.01 + 0.02 / − 0.17 are found, suggesting that the stored energy may have been fully mitigated by each SPI, although mitigation efficiencies well below ITER and SPARC requirements for high energy pulses are still within the large uncertainties. Emis3D is also used to validate JOREK SPI simulations, and confirms improvements in matching experiment from changes to impurity modeling. Time-dependent toroidal peaking factors are calculated and discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Spatiotemporal control of laser intensity using differentiable programming

Optical techniques for spatiotemporal control can produce laser pulses with custom amplitude, phase, or polarization structure. In nonlinear optics and plasma physics, the use of structured pulses typically follows a forward design approach, in which the efficacy of a known structure is analyzed for a particular application. Inverse approaches, in contrast, enable the discovery of new structures with the potential for superior performance. Here, an implementation of the unidirectional pulse propagation equation that supports automatic differentiation is combined with gradient-based optimization to design structured pulses with features that are advantageous for a range of nonlinear optical and plasma-based applications: (1) a longitudinally uniform intensity over an extended region, (2) a superluminal intensity peak that travels many Rayleigh ranges with constant duration, spot size, and amplitude, and (3) a laser pulse that ionizes a gas to form a uniform column of plasma. In the final case, optimizing the full spatiotemporal structure improves the performance by a factor of 15 compared to optimizing only spatial or only temporal structure, highlighting the advantage of spatiotemporal control.

automatic differentiation↗
DOE OSTI2020

MIRaGE: Design Software for Metamaterials

Metamaterials are artificial optical structures that allow control of light in ways not found in, or offered by, naturally occurring materials. Sandia's Multiscale Inverse Rapid Group-theory for Engineered-metamaterials (MIRaGE) software, which won an R&D100 award in 2019, allows researchers to deterministically design and produce metamaterials with unique characteristics. MIRaGE also provides powerful autonomous optimization techniques for real-world performance in a rigorous, robust, and accurate manner.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Scalable deep learning for watershed model calibration

Watershed models such as the Soil and Water Assessment Tool (SWAT) consist of high-dimensional physical and empirical parameters. These parameters often need to be estimated/calibrated through inverse modeling to produce reliable predictions on hydrological fluxes and states. Existing parameter estimation methods can be time consuming, inefficient, and computationally expensive for high-dimensional problems. In this paper, we present an accurate and robust method to calibrate the SWAT model (i.e., 20 parameters) using scalable deep learning (DL). We developed inverse models based on convolutional neural networks (CNN) to assimilate observed streamflow data and estimate the SWAT model parameters. Scalable hyperparameter tuning is performed using high-performance computing resources to identify the top 50 optimal neural network architectures. We used ensemble SWAT simulations to train, validate, and test the CNN models. We estimated the parameters of the SWAT model using observed streamflow data and assessed the impact of measurement errors on SWAT model calibration. We tested and validated the proposed scalable DL methodology on the American River Watershed, located in the Pacific Northwest-based Yakima River basin. Our results show that the CNN-based calibration is better than two popular parameter estimation methods (i.e., the generalized likelihood uncertainty estimation [GLUE] and the dynamically dimensioned search [DDS], which is a global optimization algorithm). For the set of parameters that are sensitive to the observations, our proposed method yields narrower ranges than the GLUE method but broader ranges than values produced using the DDS method within the sampling range even under high relative observational errors. The SWAT model calibration performance using the CNNs, GLUE, and DDS methods are compared using R 2 and a set of efficiency metrics, including Nash-Sutcliffe, logarithmic Nash-Sutcliffe, Kling-Gupta, modified Kling-Gupta, and non-parametric Kling-Gupta scores, computed on the observed and simulated watershed responses. The best CNN-based calibrated set has scores of 0.71, 0.75, 0.85, 0.85, 0.86, and 0.91. The best DDS-based calibrated set has scores of 0.62, 0.69, 0.8, 0.77, 0.79, and 0.82. The best GLUE-based calibrated set has scores of 0.56, 0.58, 0.71, 0.7, 0.71, and 0.8. The scores above show that the CNN-based calibration leads to more accurate low and high streamflow predictions than the GLUE and DDS sets. Our research demonstrates that the proposed method has high potential to improve our current practice in calibrating large-scale integrated hydrologic models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Iterative optical vector-matrix processors (survey of selected achievable operations)

An iterative optical vector-matrix multiplier with a microprocessor-controlled feedback loop capable of performing a wealth of diverse operations was described. A survey and description of many of its operations demonstrates the versatility and flexibility of this class of optical processor and its use in diverse applications. General operations described include: linear difference and differential equations, linear algebraic equations, matrix equations, matrix inversion, nonlinear matrix equations, deconvolution and eigenvalue and eigenvector computations. Engineering applications being addressed for these different operations and for the IOP are: adaptive phased-array radar, time-dependent system modeling, deconvolution and optimal control.

Casasent, D.↗
NASA NTRS1998

A Framework for a Supervisory Expert System for Robotic Manipulators with Joint-Position Limits and Joint-Rate Limits

This report addresses the problem of path planning and control of robotic manipulators which have joint-position limits and joint-rate limits. The manipulators move autonomously and carry out variable tasks in a dynamic, unstructured and cluttered environment. The issue considered is whether the robotic manipulator can achieve all its tasks, and if it cannot, the objective is to identify the closest achievable goal. This problem is formalized and systematically solved for generic manipulators by using inverse kinematics and forward kinematics. Inverse kinematics are employed to define the subspace, workspace and constrained workspace, which are then used to identify when a task is not achievable. The closest achievable goal is obtained by determining weights for an optimal control redistribution scheme. These weights are quantified by using forward kinematics. Conditions leading to joint rate limits are identified, in particular it is established that all generic manipulators have singularities at the boundary of their workspace, while some have loci of singularities inside their workspace. Once the manipulator singularity is identified the command redistribution scheme is used to compute the closest achievable Cartesian velocities. Two examples are used to illustrate the use of the algorithm: A three link planar manipulator and the Unimation Puma 560. Implementation of the derived algorithm is effected by using a supervisory expert system to check whether the desired goal lies in the constrained workspace and if not, to evoke the redistribution scheme which determines the constraint relaxation between end effector position and orientation, and then computes optimal gains.

Mutambara, Arthur G. O.↗
DOE OSTI2022

Optimizing the accuracy of viscoelastic characterization with AFM force–distance experiments in the time and frequency domains

Atomic Force Microscopy (AFM) force-distance (FD) experiments have emerged as an attractive alternative to traditional micro-rheology measurement techniques owing to their versatility of use in materials of a wide range of mechanical properties. Here, we show that the range of time dependent behaviour which can reliably be resolved from the typical method of FD inversion (fitting constitutive FD relations to FD data) is inherently restricted by the experimental parameters: sampling frequency, experiment length, and strain rate. Specifically, we demonstrate that violating these restrictions can result in errors in the values of the parameters of the complex modulus. In the case of complex materials, such as cells, whose behaviour is not specifically understood a priori, the physical sensibility of these parameters cannot be assessed and may lead to falsely attributing a physical phenomenon to an artifact of the violation of these restrictions. We use arguments from information theory to understand the nature of these inconsistencies as well as devise limits on the range of mechanical parameters which can be reliably obtained from FD experiments. The results further demonstrate that the nature of these restrictions depends on the domain (time or frequency) used in the inversion process, with the time domain being far more restrictive than the frequency domain. Lastly, we demonstrate how to use these restrictions to better design FD experiments to target specific timescales of a material's behaviour through our analysis of a polydimethylsiloxane (PDMS) polymer sample.

information theory↗
DOE OSTI2024

Analysis and Optimization of the Recompression Cycle with High Temperature Recuperator Bypass for Concentrating Solar Power Applications

This work analyzes the sCO2 recompression with high temperature recuperator (HTR) bypass power cycle for use in concentrating solar power (CSP) systems. CSP operation differs from other thermal power plants in that CSP must balance between maximizing the heat transfer fluid (HTF) temperature difference and maximizing the cycle thermal efficiency, which typically are inversely related. Large HTF temperature differences reduce the size and cost of thermal energy storage (TES), improve the solar receiver efficiency, and require lower mass flow rates that reduce pumping power required to elevate the HTF to the receiver. The recompression cycle with HTR bypass potentially offers improved thermal efficiency with larger HTF temperature differences as compared to the recompression cycle, and it has fewer turbomachinery components than the partial cooling cycle. The recompression with HTR bypass cycle adds a second lower temperature primary heat exchanger which transfers heat from the HTF to the fraction of sCO2 flow that bypasses the HTR. We developed a model to compare the recompression with HTR bypass cycle to the recompression and partial cooling cycles. A sweep of design parameters including bypass fraction, recompression fraction, recuperator conductance, and pressure ratio is used to form a pareto-optimal front with the cycle thermal efficiency and HTF temperature difference as objectives. An optimization routine has also been developed to find optimal design point parameters for a target HTF temperature difference. The performance of the recompression with HTR bypass cycle is compared with recompression and partial cooling cycles.

concentrating solar power↗
DOE OSTI2019

Coupled Hydrodynamic-Geomechanical Modelling of CO2-WAG Field Development at Farnsworth Unit: A Case Study

Abstract The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations at Farnsworth, Texas, USA. Utilized CO2 is anthropogenic, sourced from a fertilizer and an ethanol plant. Major project goals are optimizing the storage/production balance, ensuring storage permanence, and developing best practices for CCUS. This paper provides a review of work performed toward development of a 3D coupled Mechanical Earth Model (MEM) for use in assessment of caprock integrity, fault reactivation potential, and evaluation of stress dependent permeability in reservoir forecasting. Mechanical property estimates computed from geophysical logs at selected wellbores were integrated with 3D seismic elastic inversion products to create a 3D "static" mechanical property model sharing the same geological framework as the existing reservoir simulation model including 3 major faults. Stresses in the MEM were initialized from wellbore stress estimates and reservoir simulation pore pressures. One way and two way coupled simulations were performed using a compositional hydrodynamic flow model and geomechanical solvers. Coupled simulations were performed on history matched primary, secondary (waterflood), and tertiary (CO2 WAG) recovery periods, as well as an optimized WAG prediction period. These simulations suggest that the field has been operating at conditions which are not conducive to either caprock failure or fault reactivation. Two way coupled simulations were performed in which permeability was periodically updated as a function of volumetric strain using the Kozeny-Carmen porosity-permeability relationship. These simulations illustrate the importance of frequent permeability updating when recovery scenarios result in large pressure changes such as in field re-pressurization through waterflood after a long primary depletion recovery period. Conversely, production forecasting results are less sensitive to permeability update frequency when pressure cycles are short and shallow as in WAG cycles. This paper describes initial work on development of a mechanical earth model for use in assessment of geomechanical risks associated with CCUS operations at FWU. The emphasis of this work is on integration of available geomechanical data for creation of the static mechanical property model. Preliminary coupled hydro-mechanical simulations are presented to illustrate some of the key diagnostic output from coupled simulations which will be used in later work for in depth evaluation of specific risk factors such as induced seismicity and caprock integrity.

02 PETROLEUM↗
DOE OSTI2014

Review of structure representation and reconstruction on mesoscale and microscale

Structure representation and reconstruction on mesoscale and microscale is critical in material design, advanced manufacturing and multiscale modeling. Microstructure reconstruction has been applied in different areas of materials science and technology, structural materials, energy materials, geology, hydrology, etc. This review summarizes the microstructure descriptors and formulations used to represent and algorithms to reconstruct structures at microscale and mesoscale. In the stochastic methods using correlation function, different optimization approaches have been adapted for objective function minimization. A variety of reconstruction approaches are compared in efficiency and accuracy.

Microstructure reconstruction, inverse design, mic↗