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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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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Measuring Low-Order Aberrations in a Segmented Telescope

The in-focus PSF optimizer (IPO) is an algorithm for use in monitoring and controlling the alignment of the segments of a segmented-mirror astronomical telescope. IPO is so named because it computes wave-front aberrations of the telescope from digitized pointspread functions (PSFs) measured in infocus images. Inasmuch as distant astronomical objects that behave optically as point sources can typically be seen in almost any astronomical image, the main benefit afforded by IPO may be to enable maintenance of mirror-segment alignments without detracting from valuable scientific-observation time. IPO evolved from prescription-retrieval type algorithms. Prescription retrieval uses in-focus and out-of-focus PSFs to infer the state of an imaging optical system. The state, in this context, refers to the positions, orientations, and low-order figure errors of the optical elements in the system. Both prescription- retrieval and IPO use an iterative, nonlinear, least-squares optimizer to compute the optimal state parameters such that a digital computer-generated model image matches the digitized image acquired from the real system. The difference between IPO and prescription- retrieval algorithms is that IPO is specifically designed to utilize infocus images only. Although the restriction to in-focus images limits IPO to calculating only the lowest-order wave front aberrations, it also causes the resulting computation to take much less time because fewer degrees of freedom are included in the optimization process. In the prescription retrieval software developed at JPL, the model images are generated using the ray-trace/physical optics program, MACOS. IPO, on the other hand, uses a linear sensitivity matrix to compute the exit-pupil wave front from the system parameters; the wave front is then converted into a complex pupil field, which is then propagated to the image plane via a fast Fourier transform. This approach is computationally faster and requires less computer memory than is needed for prescription retrieval.

Ohara, Catherine↗
DOE OSTI2024

Li-ion battery design through microstructural optimization using generative AI

Lithium-ion batteries are used across various applications, necessitating tailored cell designs to enhance performance. Optimizing electrode manufacturing parameters is a key route to achieving this, as these parameters directly influence the microstructure and performance of the cells. However, linking process parameters to performance is complex, and experimental or modeling campaigns are often slow and expensive. This study introduces a fast computational optimization framework for electrode manufacturing parameters. A generative model, trained on a small dataset of microstructural images associated with different manufacturing parameters, efficiently generates representative microstructures for new parameters. This model is integrated into a Bayesian optimization loop that includes microstructure generation, characterization, and simulation, aiming to find optimal manufacturing parameters for a particular application. Significant improvement in the energy density of a 4680 cell is achieved through bespoke cell design, highlighting the importance of cell-scale normalization. The framework’s modularity allows its application to various advanced materials manufacturing scenarios.

batteries↗
DOE OSTI2016

SU-F-T-201: Acceleration of Dose Optimization Process Using Dual-Loop Optimization Technique for Spot Scanning Proton Therapy

Purpose: The purpose was to demonstrate a developed acceleration technique of dose optimization and to investigate its applicability to the optimization process in a treatment planning system (TPS) for proton therapy. Methods: In the developed technique, the dose matrix is divided into two parts, main and halo, based on beam sizes. The boundary of the two parts is varied depending on the beam energy and water equivalent depth by utilizing the beam size as a singular threshold parameter. The optimization is executed with two levels of iterations. In the inner loop, doses from the main part are updated, whereas doses from the halo part remain constant. In the outer loop, the doses from the halo part are recalculated. We implemented this technique to the optimization process in the TPS and investigated the dependence on the target volume of the speedup effect and applicability to the worst-case optimization (WCO) in benchmarks. Results: We created irradiation plans for various cubic targets and measured the optimization time varying the target volume. The speedup effect was improved as the target volume increased, and the calculation speed increased by a factor of six for a 1000 cm3 target. An IMPT plan for the RTOG benchmark phantom was created in consideration of ±3.5% range uncertainties using the WCO. Beams were irradiated at 0, 45, and 315 degrees. The target’s prescribed dose and OAR’s Dmax were set to 3 Gy and 1.5 Gy, respectively. Using the developed technique, the calculation speed increased by a factor of 1.5. Meanwhile, no significant difference in the calculated DVHs was found before and after incorporating the technique into the WCO. Conclusion: The developed technique could be adapted to the TPS’s optimization. The technique was effective particularly for large target cases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

MapsTorch : automatic differentiation for X-ray fluorescence data analysis

X-ray fluorescence (XRF) is a popular spectroscopy technique for elemental analysis. Spectrum fitting and parameter tuning are at the core of XRF analysis and are conventionally manually intensive, especially for synchrotron experiments involving large amounts of diverse samples. This work introduces the automatic differentiation (AD) technique to XRF and an open-source package called MapsTorch. By transforming an analytical model of the XRF spectrum into a differentiable computation graph with AD, MapsTorch enables robust optimization of parameters and elemental intensities. We evaluate MapsTorch by conducting computational experiments on a large number of historical synchrotron XRF datasets and compare its performance with the currently practiced fitting tool NLopt. The results show that MapsTorch consistently achieves high-quality fits and often leads to better fitting quality than NLopt, particularly in tasks such as initial spectrum fitting and elemental intensity refinement. The robust performance of MapsTorch paves the way for developing automated and high-throughput XRF data analysis workflows to handle the increasing data volumes expected from next-generation synchrotron facilities.

X-ray fluorescence↗
DOE OSTI2014

SU-E-T-182: Feasibility of Dose Painting by Numbers in Proton Therapy with Contour-Driven Plan Optimization

Purpose: The work aims to 1) prove the feasibility of dose painting by numbers (DPBN) in proton therapy with usual contour-driven plan optimization and 2) compare the achieved plan quality to that of rotational IMRT. Methods: For two patients with head and neck cancers, voxel-by-voxel prescription to the target volume (PTV-PET) was calculated from {sup 18} FDG-PET images and converted to contour-based prescription by defining several sub-contours. Treatments were planned with RayStation (RaySearch Laboratories, Sweden) and proton pencil beam scanning modality. In order to determine the optimal plan parameters to approach the DPBN prescription, the effect of the number of fields, number of sub-contours and use of range shifter were tested separately on each patient. The number of sub-contours were increased from 3 to 11 while the number of fields were set to 3, 5, 7 and 9. Treatment plans were also optimized on two rotational IMRT systems (TomoTherapy and Varian RapidArc) using previously published guidelines. Results: For both patients, more than 99% of the PTV-PET received at least 95% of the prescribed dose while less than 1% of the PTV-PET received more than 105%, which demonstrates the feasibility of the treatment. Neither the use of a range shifter nor the increase of the number of fields had a significant influence on PTV coverage. Plan quality increased when increasing number of fields up to 7 or 9 and slightly decreased for a bigger number of sub-contours. Good OAR sparing is achieved while keeping high plan quality. Finally, proton therapy achieved significantly better plan quality than rotational IMRT. Conclusion: Voxel-by-voxel prescriptions can be approximated accurately in proton therapy using a contour-driven optimization. Target coverage is nearly insensitive to the number of fields and the use of a range shifter. Finally, plan quality assessment confirmed the superiority of proton therapy compared to rotational IMRT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Validating automated resonance evaluation with synthetic data

The integrity and precision of nuclear data are crucial for a broad spectrum of applications, from national security and nuclear reactor design to medical diagnostics, where the associated uncertainties can significantly impact outcomes. A substantial portion of uncertainty in nuclear data originates from the subjective biases in the evaluation process, a crucial phase in the nuclear data production pipeline. Recent advancements indicate that automation of certain routines can mitigate these biases, thereby standardizing the evaluation process and enhancing reproducibility. This research aims to provide a methodology, framework, and metrics for the validation of automated nuclear data evaluation software leveraging high-quality synthetic data that closely mimic real experimental observables. An introduced error metric provides a scale and intuitive measure of the evaluation quality by quantifying the estimate’s accuracy and performance across the specified energy range. Synthetic data provides access to experimental observables and underlying resonance parameters, enabling comparison of different evaluations. The methodology is demonstrated using Ta-181 isotope data in the resolved resonance region. The Automated Resonance Identification Subroutine (ARIS), which operates without prior resonance information, was used to test and showcase the framework’s capabilities utilizing the proposed error metrics. The results demonstrate the effectiveness of the proposed approach and framework for optimizing software parameters and testing hypotheses through “what-if” controlled experiments, such as modifying assumptions about experimental conditions or average resonance parameters.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

An Intelligent System for Automatic Selection of DC-DC Converter Topology with Optimal Design

In this paper, we present an intelligent system that has the capabilities of automatically selecting topology classes and optimizing circuit parameters of DC-DC power converters for a given design specification. The system, Machine-Learning-enhanced Automated Circuit Configuration and Evaluation of Power Converters (ML-ACCEPT), uses a hybrid of machine learning technologies, decision tree inference, reinforcement learning and deep neural networks. The system gives high accurate recommendations of design topology classes and computationally efficient results in optimizing power efficiencies in power converter design.

Xue, Lincoln↗
DOE OSTI2022

Ultrasonic nondestructive diagnosis of lithium-ion batteries with multiple frequencies

Accurately estimating the state of charge (SoC) in battery management systems (BMSs) requires the measurement of numerous parameters and advanced algorithms. This work studies multifrequency ultrasonic waves to estimate the SoC of Li-ion batteries by sensing the material changes during charge/discharge. A pouch-type LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) graphite battery cell is designed and fabricated with a capacity of 2.4 Ah. Different ultrasonic testing setups are explored to determine the optimal testing parameters for the battery. An ultrasonic monitoring system is developed to monitor the battery during charge/discharge at 750 kHz, 1 MHz, and 1.5 MHz. Signal processing algorithms are proposed for extracting three ultrasonic features—amplitude, wave velocity, and attenuation. In a three-cycle test, the amplitude histories do not show clear correlations with the SoC. The wave velocities of all three frequencies have an approximately linear relationship with the SoC, which can be used for SoC estimation. Hysteresis behavior is observed for the wave velocity in terms of a larger slope in the discharge process and velocity drop after a close charge/discharge cycle. The wave attenuation is able to capture the material phase transitions during charge/discharge.

25 ENERGY STORAGE↗
DOE OSTI2024

Collaborative Research: Enhancing Laser-Based Ion Sources with High Data Rate Techniques

This collaborative research project focuses on leveraging advanced machine learning techniques to analyze and optimize data from high-repetition-rate laser experiments. The main goal is to apply modern computing hardware, customized data acquisition firmware/software, and machine learning approaches to improve data analysis and experimental control. The project also explores how methodology can be developed on smaller-scale experimental setups and then translated to larger facilities within DOE's LaserNetUS network. With extensive data collection and modeling, the research aims to predict and optimize experimental parameters to enhance performance and efficiency.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Optimization of solid state anaerobic digestion of the OFMSW by digestate recirculation: A new approach

Highlights: • Solid State Anaerobic Digestion (SSAD) of OFMSW can be optimized by irrigation with digestate. • Digestate spreading allows keeping optimal process parameters and high hydrolysis rate. • The 18.4% of CH{sub 4} was produced in the reactor, leaving the 49.7% in the percolate. • Successive CSTR feed with percolate shows a biogas enriched in methane (more than 80%). • The proposed process allow producing the 68% of OFMSW potential CH{sub 4}, getting high quality organic amendment. - Abstract: Dry anaerobic digestion (AD) of OFMSW was optimized in order to produce biogas avoiding the use of solid inoculum. Doing so the dry AD was performed irrigating the solid waste with liquid digestate (flow rate of 1:1.18–1:0.9 w/w waste/digestate; 21 d of hydraulic retention time – HRT) in order to remove fermentation products inhibiting AD process. Results indicated that a high hydrolysis rate of organic matter (OM) and partial biogas production were obtained directly during the dry AD. Hydrolysate OM was removed from digester by the percolate flow and it was subsequently used to feed a liquid anaerobic digester. During dry AD a total loss of 36.9% of total solids was recorded. Methane balance indicated that 18.4% of potential methane can be produced during dry AD and 49.7% by the percolate. Nevertheless results obtained for liquid AD digestion indicated that only 20.4% and 25.7% of potential producible methane was generated by adopting 15 and 20 days of HRT, probably due to the AD inhibition due to high presence of toxic ammonia forms in the liquid medium.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1995

F-18 High Alpha Research Vehicle (HARV) parameter identification flight test maneuvers for optimal input design validation and lateral control effectiveness

Flight test maneuvers are specified for the F-18 High Alpha Research Vehicle (HARV). The maneuvers were designed for open loop parameter identification purposes, specifically for optimal input design validation at 5 degrees angle of attack, identification of individual strake effectiveness at 40 and 50 degrees angle of attack, and study of lateral dynamics and lateral control effectiveness at 40 and 50 degrees angle of attack. Each maneuver is to be realized by applying square wave inputs to specific control effectors using the On-Board Excitation System (OBES). Maneuver descriptions and complete specifications of the time/amplitude points define each input are included, along with plots of the input time histories.

Morelli, Eugene A.↗
DOE OSTI2018

High thermal stability and excellent dielectric properties of a novel X8R-type CdCu3Ti4O12 ceramics through a sol-gel technique

Highlights: • CdCu{sub 3}Ti{sub 4}O{sub 12} (CdCTO) ceramics were successfully synthesized via the sol-gel method, and the optimized processing parameters were obtained. • The outstanding dielectric properties: ε{sub r} ≈ 1.63 × 10{sup 4} and tan δ = 0.035 (at 10 kHz) could be obtained in CdCTO ceramics sintered at 1000 °C. • The CdCTO-SG ceramics obtained an excellent thermal stability. - Abstract: CdCu{sub 3}Ti{sub 4}O{sub 12} (CdCTO) ceramics were systematically synthesized via the sol-gel technique. The optimal CH{sub 3}COOH and Ti(OC{sub 4}H{sub 9}){sub 4} concentrations in the synthesis solution and processing temperature were found to be 5.0 vol%, 0.50 mol/L and 60 °C, respectively. These materials exhibited high densities and fine-grained microstructures along with outstanding dielectric properties, including an ε{sub r} of approximately 1.63 × 10{sup 4} and a tan δ of 0.035 at 10 kHz. Over the temperature range from −55 to 150 °C, the temperature coefficients of the dielectric constant at 1 and 10 kHz were −13.9% to 1.20% and −9.10% to 3.92%, respectively, indicating that these ceramics possess excellent thermal stability. These properties also meet the requirements for X8R applications. Data acquired from complex impedance spectroscopy and electrical modulus assessments demonstrates that the superior dielectric properties of these CdCTO ceramics can be attributed to the internal barrier layer capacitor theory (IBLC).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A New Subfamily of Glycoside Hydrolase Family 30 with Strict Xylobiohydrolase Function

The Acetivibrioclariflavus (basonym: Clostridium clariflavum) glycoside hydrolase family 30 cellulosomal protein encoded by the Clocl_1795 gene was highly represented during growth on cellulosic substrates. In this report, the recombinantly expressed protein has been characterized and shown to be a non-reducing terminal (NRT)-specific xylobiohydrolase (AcXbh30A). Biochemical function, optimal biophysical parameters, and phylogeny were investigated. The findings indicate that AcXbh30A strictly cleaves xylobiose from the NRT up until an α-1,2-linked glucuronic acid (GA)-decorated xylose if the number of xyloses is even or otherwise a single xylose will remain resulting in a penultimate GA-substituted xylose. Unlike recently reported xylobiohydrolases, AcXbh30A has no other detectable hydrolysis products under our optimized reaction conditions. Sequence analysis indicates that AcXbh30A represents a new GH30 subfamily. This new xylobiohydrolase may be useful for commercial production of industrial quantities of xylobiose.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts

This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. As a result, this research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.

17 WIND ENERGY↗
NASA NTRS1962

Interplanetary Trajectory Optimization with Powerlimited Propulsion Systems

A trajectory-optimization process is described in which the optimum­ thrust equations are derived using the calculus of variations. The mag­nitude of the thrust is constrained within an upper and a lower bound, but the thrust direction is arbitrary. This formulation allows both the constant-thrust program and the variable-thrust program to be con­sidered. For the constant-thrust program, certain propulsion-system parameters are optimized for maximum final vehicle mass. This theory has been used to study interplanetary missions to Venus and Mars using a power-limited propulsion system. Both one-way and round­ trip rendezvous trajectories are considered. The analysis employs a two-body inverse-square force-field model of three dimensions. An iterative routine used to solve the two-point boundary-value problem is described in the Appendix.

TRAJECTORY↗
NASA NTRS1998

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Dhawan, Atam P.↗
DOE OSTI2018

Critical Evaluation and Thermodynamic Optimization of the Li{sub 2}O-Al{sub 2}O{sub 3} and Li{sub 2}O-MgO-Al{sub 2}O{sub 3} Systems

The thermodynamic and phase diagram data of the Li{sub 2}O-Al{sub 2}O{sub 3} and Li{sub 2}O-MgO-Al{sub 2}O{sub 3} systems were critically evaluated and optimized to obtain a set of consistent Gibbs energy functions for all phases in the systems. The LiAl{sub 5}O{sub 8}-MgAl{sub 2}O{sub 4} spinel solid solution was modeled with the two-sublattice compound energy formalism by considering the cation distribution between the tetrahedral and octahedral sites and excess vacancy in octahedral sites. The liquid phase and monoxide solid solution were also described using the modified quasichemical model with pair approximation and the Bragg–Williams random mixing model, respectively. The thermodynamic models with optimized model parameters enable the reproduction of all reliable thermodynamic and phase diagram as well as spinel structural data in the system.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A high fidelity and user-friendly equation-oriented optimization model for carbon capture using a novel water-lean solvent

Research Triangle Institute (RTI) International and SLB have developed a novel water-lean solvent technology for carbon capture, demonstrating low specific reboiler duty (SRD) values at capture rates exceeding 90%. At the Technology Centre Mongstad (TCM) pilot plant, the technology achieved an SRD of 2.55 GJ/t-CO2 at 95% capture, utilizing an intercooler and a 5°C temperature approach in the lean/rich solvent cross exchanger. To meet varying carbon capture targets for Front End Engineering and Design (FEED) studies and to enable real-time optimization and advanced process control, an efficient optimization model is required. This model needs to minimize energy demand for a given capture rate and determine optimal operating parameters in response to fluctuating flue gas conditions. While an existing Aspen Plus simulation model, developed by RTI and SLB, accurately matches TCM plant data, its sequential modular (SM) strategy is too slow for real-time applications due to recycle streams and tight heat integration inherent in solvent-based carbon capture processes. Although an equation-oriented (EO) modeling strategy is more suitable for optimizing these processes, its adoption has been limited by several factors: feature limitations in Aspen Plus EO mode (e.g., lack of balance block support), a less user-friendly interface for variable identification and loop solving, complex troubleshooting of convergence issues, and the necessity for accurate initial values.

carbon capture↗