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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system

There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.

Hein, C.↗
NASA NTRS1973

Perform - A performance optimizing computer program for dynamic systems subject to transient loadings

A description and applications of a computer capability for determining the ultimate optimal behavior of a dynamically loaded structural-mechanical system are presented. This capability provides characteristics of the theoretically best, or limiting, design concept according to response criteria dictated by design requirements. Equations of motion of the system in first or second order form include incompletely specified elements whose characteristics are determined in the optimization of one or more performance indices subject to the response criteria in the form of constraints. The system is subject to deterministic transient inputs, and the computer capability is designed to operate with a large linear programming on-the-shelf software package which performs the desired optimization. The report contains user-oriented program documentation in engineering, problem-oriented form. Applications cover a wide variety of dynamics problems including those associated with such diverse configurations as a missile-silo system, impacting freight cars, and an aircraft ride control system.

Pilkey, W. D.↗
DOE OSTI2024

Model Quality and Measurement Density Impact on Volt/Volt Ampere Reactive Optimization Performance

The operation of the utility grid is being reshaped by the continuous addition of distributed energy resources and advanced metering infrastructure, which challenge existing grid control strategies. Some utilities deploy advanced distribution management systems (ADMS) to assist with the consolidation of various applications and to augment situational awareness in response to the new power delivery dynamics. An ADMS is an integrated software platform that provides utilities with a way to enhance their reliability, control, and optimization with advanced applications, such as volt/VAR optimization (VVO). A VVO application could serve as a vehicle to deliver cost savings by providing the utility with a method to reduce rates by controlling the voltage and decreasing the energy usage in their service territory. Some utilities are reluctant to integrate an ADMS, because it is a significant investment that requires approval from the public regulatory commission and/or their customers. This paper evaluates the impact on VVO performance when using a lower-quality network model supplemented with additional measurements, which could provide an implementation for cost savings. The results show that a better model quality would provide the highest energy savings; however, some level of telemetry is necessary in all scenarios to prevent voltage exceedances.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Trends and limits of CO 2 capture in solid and liquid sorbents at standard conditions

Carbon capture and storage (CCS) plays a critical role in achieving climate change mitigation targets, offering a pathway to decarbonize power generation, industrial processes, and heat production while addressing atmospheric CO 2 removal. While CCS technologies are technically advanced, the widespread adoption of 100 % CO 2 capture capacities such as 1 mol of CO 2 /mol of material and 1 g CO 2 /g storage (targeted by the DARPA, Defense Sciences Office, USA Govt.) has raised questions about the feasibility of achieving higher capture capacities. In the context of limiting global warming to 1.5°C, reaching 100 % CO 2 capture capacity is increasingly necessary, with residual emissions requiring complementary carbon dioxide removal (CDR) technologies. This review exclusively focuses on the CO 2 capture capacities of various sorbents under standard conditions, using different evaluation metrics. This study explores the performance of solid and liquid sorbents under standard conditions, analyzing factors including surface area, pore structure, solvent type, and functionalization to identify materials optimized for industrial-scale CCS applications. Emerging sorbents, including ILs, MOFs, COFs, POPs, DES, RCC, hybrid materials, and reactive sorbents, offer significant potential for enhanced selectivity and energy-efficient regeneration. Through a systematic assessment of gravimetric, volumetric, and molar capacities, the study provides insights into material efficiencies and trade-offs, offering guidance on optimizing sorbent selection for specific applications. The research advances understanding of scalable CCS technologies, contributing to global efforts to achieve net-zero emissions and address the pressing challenge of climate change.

Absorption↗
DOE OSTI2021

Optimal Decision Making in High-Throughput Virtual Screening Pipelines

ABSTRACT Effective selection of the potential candidates that meet certain conditions in a tremendously large search space has been one of the major concerns in many real-world applications. In addition to the nearly infinitely large search space, rigorous evaluation of a sample based on the reliable experimental or computational platform is often prohibitively expensive, making the screening problem more challenging. In such a case, constructing a high-throughput screening (HTS) pipeline that pre-sifts the samples expected to be potential candidates through the efficient earlier stages, results in a significant amount of savings in resources. However, to the best of our knowledge, despite many successful applications, no one has studied optimal pipeline design or optimal pipeline operations. In this study, we propose two optimization frameworks, applying to most (if not all) screening campaigns involving experimental or/and computational evaluations, for optimally determining the screening thresholds of an HTS pipeline. We validate the proposed frameworks on both analytic and practical scenarios. In particular, we consider the optimal computational campaign for the long non-coding RNA (lncRNA) classification as a practical example. To accomplish this, we built the high-throughput virtual screening (HTVS) pipeline for classifying the lncRNA. The simulation results demonstrate that the proposed frameworks significantly reduce the effective selection cost per potential candidate and make the HTS pipelines less sensitive to their structural variations. In addition to the validation, we provide insights on constructing a better HTS pipeline based on the simulation results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Gallium Oxide Heterojunction Diodes for 400 °C High‐Temperature Applications

β ‐Ga 2 O 3 ‐based semiconductor devices are expected to have significantly improved high‐power and high‐temperature performance due to its ultrawide bandgap of close to 5 eV. However, the high‐temperature operation of these ultrawide‐bandgap devices is usually limited by the relatively low 1–2 eV built‐in potential at the Schottky barrier with most high‐work‐function metals. Herein, heterojunction p ‐NiO/n‐ β ‐Ga 2 O 3 diodes fabrication and optimization for high‐temperature device applications are reported, demonstrating a current rectification ratio ( I ON / I OFF ) of more than 10 6 at 410 °C. The NiO heterojunction diode can achieve higher turn‐on ( V ON ) voltage and lower reverse leakage current compared to the Ni‐based Schottky diode fabricated on the same single‐crystal β ‐Ga 2 O 3 substrate, despite charge transport dominated by interfacial recombination. Electrical characterization and device modeling show that these advantages are due to a higher built‐in potential and additional band offset. These results suggest that heterojunction p–n diodes based on β ‐Ga 2 O 3 can significantly improve high‐temperature electronic device and sensor performance.

Sohel, Shahadat H.↗
DOE OSTI2024

Binder-Coated Carbon Cloth Electrodes for All-Vanadium Redox Flow Batteries

Vanadium redox flow batteries (VRFBs) are a promising solution for integrating intermittent renewable energy sources into the existing power grid. However, enhancing the electrochemical performance of VRFBs is critical for their widespread adoption in grid-scale energy storage. This study investigates the impact of adding a porous binder to a carbon-cloth electrode, with a focus on optimizing thermal activation conditions. The electrochemical performance of the binder-coated electrodes compared to uncoated electrodes is evaluated through electrochemical impedance spectroscopy, polarization curve measurements, and charge-discharge cycling. The surface morphology and structural integrity of the binder-coated electrodes at each activation stage are examined using various material characterization techniques to assess the effects of thermal activation. The results are benchmarked against the experiments using non-coated electrodes to determine the performance improvements offered by the binder coating. Notably, the study reveals that binder-coated electrodes exhibit significantly lower resistance and improved efficiency compared to their uncoated counterparts, with optimal activation conditions enhancing performance metrics crucial for VRFB applications. These findings provide valuable insights for further optimizing electrode design and activation strategies, advancing the development of more efficient VRFB systems for large-scale energy storage.

Caiado, Ashley A.↗
DOE OSTI2023

Ciel

Compiler optimizations can alter the numerical results of scientific computing applications. When numerical results differ significantly between compilers, optimization levels, and floating-point hardware, these numerical inconsistencies can impact programming productivity. Ciel is a framework that helps programmers identify locations in the source code that are affected by compiler optimizations in CPU and GPU code. Ciel uses a floating-point precision enhancement strategy, guided by a recursive bisection search algorithm with increasing search granularity, to identify the program expressions that induce numerical inconsistencies due to compiler optimizations.

Miao, Wenjun↗
NASA NTRS2010

Optimization of Stimulus Characteristics for Vestibular Stochastic Resonance to Improve Balance Function

Stochastic resonance (SR) is a mechanism by which noise can assist and enhance the response of neural systems to relevant sensory signals. Recent studies have shown that applying imperceptible stochastic noise electrical stimulation to the vestibular system significantly improved balance and ocular motor responses. The goal of this study was to optimize the amplitude of the stochastic vestibular signals for balance performance during standing on an unstable surface. Subjects performed a standardized balance task of standing on a block of 10-cm-thick medium-density foam with their eyes closed. Balance performance was measured using a force plate under the foam block and using inertial motion sensors placed on the torso and head segments. Stochastic electrical stimulation was applied to the vestibular system through electrodes placed over the mastoid process. Subjects were tested at seven amplitudes in the 0.01-30Hz frequency range. The root mean square of the signal increased by 30 microamperes for each +/-100 microampere increment in the current range of 0 - +/-700 microampere. Six balance parameters were calculated to characterize the performance of subjects during the baseline and the stimulus periods for all seven amplitudes. Optimal stimulus amplitude was determined as the one at which the ratio of parameters from the stimulus period to the baseline period for any amplitude range was less than that for the no stimulus condition on a minimum of four of six parameters. Results from this study showed that balance performance at the optimal stimulus amplitude showed significant improvement with the application of the vestibular SR stimulation. The amplitude of optimal stimulus for improving balance performance in normal subjects was in the range of +/-100 - +/-300 microamps.

Mulavara, Ajitkumar↗
DOE OSTI2021

Modeling of Thermal Decomposition of TATB-Based Explosive for Safety Analysis

We investigate and model the cook-off behavior of LX-17 to understand the response of explosive systems in abnormal thermal environments. Decomposition has been explored via conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (Thermo-Gravimetric Analysis), and DSC (Differential Scanning Calorimetry) experiments under isothermal and ramped temperature profiles. The data were used to fit reaction rate parameters for proposed schemes in an ALE3D computational model. This model includes chemical reactions, thermo- and hydro-dynamics, and material properties, including thermal expansion, compressibility, and strength. These parameterizations were carried out utilizing a Python evolutionary optimization method on LLNL’s high-performance computing clusters. Additional experiments are being developed to further characterize and monitor decomposition intermediates to improve the model. Once experimentally validated, this model will be scalable to several applications involving LX-17. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials.

Chemistry - Chemical explosives↗
DOE OSTI2026

Fast Active-Set Thresholding Method for Nonnegative Least Squares

Nonnegative Least Squares (NNLS) is a fundamental constrained optimization problem encountered in many applications such as image deblurring, signal processing, nonnegative matrix factorization, magnetic microscopy, and hyperspectral imaging. Active-set based methods are a common class of algorithms for solving NNLS which identify the optimal variable set of the NNLS solution. They do so by iteratively solving a series of unconstrained least squares problems, identifying which variables violate the nonnegativity constraints, and then swapping variables in/out of consideration until the optimal set of variables is found. Several variations improving upon this method exist in the literature. In this work, we propose an active-set swap heuristic which further improves upon existing active-set based methods for NNLS. Our optimizations are based upon adding multiple variables to the passive set within a threshold of the smallest gradient value and removing variables within a similar threshold of the closest boundary constraint. We leverage these optimizations to yield a Fast Active-Set Thresholding NNLS (FAST-NNLS) algorithm which significantly outperforms the existing state-of-the-art NNLS algorithms for a wide range of problems. Rigorous convergence guarantees are proven for the proposed method. We demonstrate the effectiveness of our proposed method on multiple synthetic datasets and two realworld text analysis applications. In doing so, we present the most comprehensive NNLS solver comparison in the literature to date.

Cobb, Benjamin [Georgia Institute of Technology]↗
DOE OSTI2016

Variational Transition State Theory

This is the final report on a project involving the development and applications of variational transition state theory. This project involved the development of variational transition state theory for gas-phase reactions, including optimized multidimensional tunneling contributions and the application of this theory to gas-phase reactions with a special emphasis on developing reaction rate theory in directions that are important for applications to combustion. The development of variational transition state theory with optimized multidimensional tunneling as a useful computational tool for combustion kinetics involved eight objectives.

02 PETROLEUM↗
NASA NTRS2007

Quaternion Averaging

Many applications require an algorithm that averages quaternions in an optimal manner. For example, when combining the quaternion outputs of multiple star trackers having this output capability, it is desirable to properly average the quaternions without recomputing the attitude from the the raw star tracker data. Other applications requiring some sort of optimal quaternion averaging include particle filtering and multiple-model adaptive estimation, where weighted quaternions are used to determine the quaternion estimate. For spacecraft attitude estimation applications, derives an optimal averaging scheme to compute the average of a set of weighted attitude matrices using the singular value decomposition method. Focusing on a 4-dimensional quaternion Gaussian distribution on the unit hypersphere, provides an approach to computing the average quaternion by minimizing a quaternion cost function that is equivalent to the attitude matrix cost function Motivated by and extending its results, this Note derives an algorithm that deterniines an optimal average quaternion from a set of scalar- or matrix-weighted quaternions. Rirthermore, a sufficient condition for the uniqueness of the average quaternion, and the equivalence of the mininiization problem, stated herein, to maximum likelihood estimation, are shown.

Markley, F. Landis↗
DOE OSTI2016

Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Surface-Enhanced Raman Scattering (SERS) Studies of Disc-on-Pillar (DOP) Arrays: Contrasting Enhancement Factor with Analytical Performance

The use of nanomachining methods capable of reproducible construction of nano-arrayed devices have revolutionized the field of plasmonic sensing by the introduction of a diversity of rationally engineered designs. Significant strides have been made to fabricate plasmonic platforms with tailored interparticle gaps to improve their performance for surface-enhanced Raman scattering (SERS) applications. Over time, a dichotomy has emerged in the implementation of SERS for analytical applications, the construction of substrates, optimization of interparticle spacing as a means to optimize electromagnetic field enhancement at the localized surface plasmon level, and the substrate sensitivity over extended areas to achieve quantitative performance. Here, we assessed the enhancement factor of plasmonic Ag/SiO 2 /Si disc-on-pillar (DOP) arrays of variable pitch with its analytical performance for quantitative applications. Experimental data were compared with those from finite-difference time-domain (FDTD) simulations used in the optimization of the array dimensions. A self-assembled monolayer (SAM) of benzenethiol rendered highly reproducible signals (RSD ~4–10%) and SERS substrate enhancement factor (SSEF) values in the orders of 10 6 –10 8 for all pitches. Furthermore, spectra corresponding to rhodamine 6G (R6G) and 4-aminobenzoic acid demonstrated the advantages of using the more densely packed DOP arrays with a 160 nm pitch (gap= 40 nm) for quantitation in spite of the strongest SSEF was attained for a pitch of 520 nm corresponding to a 400 nm gap.

36 MATERIALS SCIENCE↗
NASA NTRS2021

Optimizing Surfactant Templating of Yttria-Stabilized Zirconia Aerogels for High-Temperature Applications: Effect of Cationic Surfactant

Aerogels can be used in spaceflight applications as thermal insulators due to their low density, low thermal conductivity, and tortuous path for solid conduction. However, the aerogel formulation must be optimized to increase the thermal stability of the aerogels, as a drastic densification and decrease in surface area often is exhibited after high-temperature exposure. This work considers yttria-stabilized zirconia (YSZ) aerogels, whichhave low thermal conductivity and are expected to be used for temperatures between 600°C and 1000°C. It is anticipated that new sol-gel chemistries will yield YSZ aerogels that exhibit retained mesoporous structure, increased surface area, and minimized shrinkage upon exposure to higher temperatures in the expected use range. This work investigates the addition of surfactant to 20 mol% YSZ aerogels. The cationic surfactant, cetrimonium bromide (CTAB), was used as the templating agent, preventing the collapse of the mesoporous structure upon gelation and drying. It was determined that adding one-half times the critical micelle concentration of CTAB increased the surface area of the aerogels by 72% and 41% and increased the pore volume following exposure to 600°C and1000°C, respectively. This level of CTAB had the greatest increase in surface area and pore volume as compared to aerogels without CTAB or with twice the critical micelle concentration of CTAB. By optimizing the concentration of CTAB, the thermal stability ofYSZ aerogels can be enhanced to make these materials more efficient when used as thermal management systems.

Yttria-stabilized zirconia aerogel↗
DOE OSTI2022

Dynamic machine learning-based optimization algorithm to improve boiler efficiency

With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. Further, the best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Microstructure evolution in the conventional single side and bobbin tool friction stir welding of thick rolled 7085-T7452 aluminum alloy

Highlights: • Comparison of microstructure evolution via EBSD of SS-FSW and BB-FSW was investigated. • Friction heat, strain rate and degree of recrystallization affected grain size. • Discontinuously dynamic recrystallization occurred in the weld nugget zone. • The degree of recrystallization was mainly controlled by the strain rate. - Abstract: The microstructure evolution during the conventional single side friction stir welding (SS-FSW) and the bobbin tool FSW (BB-FSW) of 7085-T7452 alloy thick plate was extensively studied by using the state-of-the-art materials characterization techniques. The Electron backscattering diffraction results reveal that a significant grain refinement and a larger percentage of high angle grain boundaries (HAGBs) exist in the weld nugget zone (WNZ) and the thermal-mechanical affected zone (TMAZ) compared with the base material. Meanwhile, more obviously inhomogeneous refined grains and HAGBs in WNZ along the thickness direction and a larger percentage of low angle grain boundaries (LAGBs) were observed in SS-FSW joint than that in BB-FSW joint. The change of the average grain size is the result of friction heat and strain rate of plastic deformation combined with a certain degree of recrystallization. Moreover, the recrystallization is mainly controlled by the strain rate during the FSW process. The presence of Cube and Cube ND after welding shows that the discontinuously dynamic recrystallization (DDRX) is a major factor in the final microstructural response. The research and findings help the understanding of the mechanism of microstructure homogenization and further optimizing the welding process for application.

36 MATERIALS SCIENCE↗