Search NASA⌕ Search

SEARCH · Search NASA

Results for “Structural 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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers (Final Technical Report)

This report summarizes the carbon capture research and development conducted by The State University of New York at Buffalo (UB) and GTI Energy (GTI) for award “DE-FE0031969: Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers” sponsored by the U.S. Department of Energy (DOE). The objective of this project is to develop an innovative sorbent structure of trapped small amines in HNC embedded in PEF for DAC. This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An innovative sorbent structure of trapped small amines in hierarchical nanoporous capsules (HNC) embedded in porous electrospun fibers (PEF) was developed for direct air capture (DAC). This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An interfacial polymerization process was developed, which utilized loaded amines inside mesoporous silica and trimesoyl chloride (TMC) dissolved in organic solvents as the precursors, to generate a polyamide (PA) coating layer on mesoporous silica and thus trap amines. Reaction conditions, including TMC concentration, organic solvents, reaction time, etc., for interfacial polymerization were optimized to effectively trap loaded amines, and cyclic heating-cooling operation was conducted to evaluate the coating quality. Larger pore volume mesoporous silica was also synthesized to increase amine loading and thus increase CO 2 capacity. The optimized sorbent material exhibited CO 2 capacity as high as 4.88 mmol/g under humid DAC conditions and negligible loss (<1%) during 10 cyclic heating-cooling operations. The optimized PA-coated sorbent also showed fast adsorption and desorption kinetics, with <20% t1/2 increase compared to uncoated sorbent. PEF fabrication conditions, including organic solvents for dissolving core and shell polymers, voltage, distance from the nozzle to the collection panel, etc. were adjusted to better incorporate HNC. After incorporating the optimized sorbent material into PEF, the structured sorbent had a CO 2 capacity of approximately 4.0 mmol/g under humid DAC conditions, with capacity loss of 0.17% per cycle and t1/2 increase less than 10%. A techno-economic analysis (TEA) for the process design for a DAC system based on our developed sorbent structure of trapped small amines in HNC embedded in PEF was conducted. The process design included process description and major equipment sizing and energy and mass balances in addition to scale-up research results and estimated capture cost. Aspen Adsorption Simulator was used to fit the experimentally measured breakthrough curves and extract equilibrium and kinetic data of the optimized sorbent. Our results indicated that for a DAC plant with CO 2 productivity of 3,000 tonne/year, the levelized cost of CO 2 capture was $\$$612/tonne, with the largest contribution of 44.33% from the fixed operation cost. Increasing CO 2 productivity, while maintaining similar fixed operation cost, is expected to significantly reduce the CO 2 capture cost. A sensitivity study was also conducted to understand the influence of total plant cost, sorbent cost, CO 2 concentration in the feed, sorbent mat lifetime, sorbent regeneration electricity, and adsorption blower pressure drop on the levelized cost of CO 2 capture, revealing a capture cost range of $\$$520-870/tonne.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Efficient QAOA Optimization using Directed Restarts and Graph Lookup

Variational Quantum Algorithms (VQA) aim to enhance the capabilities of Noisy Intermediate-Scale Quantum (NISQ) devices. These algorithms utilize parameterized circuits and classical optimizers to iteratively execute circuits with varying parameters. However, VQA faces computational overheads due to repeated iterations and random restarts. Prior work suggests using basic sub-graphs to transfer parameters for the input graph, reducing optimizer overheads but limiting applicability to structured regular graphs. In real-world applications, random irregular graphs are common, and existing methods are not scalable or practical for such graphs. This paper presents a framework that aims to improve random irregular graphs in VQA. The framework uses graph similarity and important features like total edge counts, average edge counts, and variance. It follows an iterative process to choose basis sub-graphs from a small database and adjust parameters accordingly. Classical optimizers then utilize these parameters to determine when to restart and perform gradient descent. This approach increases the chances of reaching global maximum points.

Wang, Meng↗
DOE OSTI2021

Modeling and analyzing parasitic parameters in high frequency converters

This research focuses on electromagnetic interference (EMI) / electromagnetic compatibility (EMC) design and analysis in power electronics systems. To limit the EMI under the standards, different methods and strategies are investigated. Parasitic parameters of high frequency (HF) transformer are analyzed using a novel analytical method, finite element method (FEM), and experimental measurements for different structures and windings arrangements. Also, the magnetic field, electric field, electric displacement, and electric potential distribution are simulated and analyzed. Moreover, a high voltage system is considered and analyzed to improve the EMC. The EMI propagation paths are analyzed. The EMI noise level of the system is obtained and compared to the IEC61800-3 standard. To improve the EMC, the parasitic parameters of the transformer, as the main path of EMI circulation, are analyzed and optimized to block the propagation. Furthermore, the geometry structure of the HF transformer is optimized to lower the parasitics in the system. Three pareto-optimal techniques are investigated for the optimization. The models and results are verified by 3D-FEM and experimental results for several given scenarios. Furthermore, the EMC modeling and conducted EMI analysis are developed for a system including an AC-DC-DC power supply (rectifier and dual active bridge (DAB) converter). Moreover, the common mode (CM) EMI noise propagation through the system is discussed and the noise sources and effect of components on the noise are analyzed. Additionally, the CM impedance of different parts of the system and the noise levels are discussed. Finally, EMI attenuation techniques were applied to the system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Efficient Parameterization of Density Functional Tight-Binding for 5 f -Elements: A Th–O Case Study

Density functional tight binding (DFTB) models for f-element species are challenging to parametrize owing to the large number of adjustable parameters. The explicit optimization of the terms entering the semiempirical DFTB Hamiltonian related to f orbitals is crucial to generating a reliable parametrization for f-block elements, because they play import roles in bonding interactions. However, since the number of parameters grows quadratically with the number of orbitals, the computational cost for parameter optimization is much more expensive for the f-elements than for the main group elements. In this work we present a set of efficient approaches for mitigating the hurdle imposed by the large size of the parameter space. A novel group-by-orbital correction functions for two-center bond integrals was developed. With this approach the number of parameters is reduced, and it grows linearly with the number of elements, maintaining the accuracy and the number of parameters, in the case of f elements, by more than 40%. The parameter optimization step was accelerated by means of the mini-batch BFGS method. This method allows parameter optimizations with much larger training sets than other single batch methods. A stochastic optimizer was employed that helped overcome shallow local minima in the objective function. The proposed algorithm was used to parametrize the DFTB Hamiltonian for the Th–O system, which was subsequently applied to the study of ThO 2 nanoparticles. The training set consisted of 6322 unique structures, which is barely feasible with conventional optimization methods. The optimized parameter set, LANL-ThO, displays good agreement with DFT-calculated properties such as energies, forces, and structures for both clusters and bulk ThO 2 . Benefiting from the fewer number of parameters and lower computational costs for objective function evaluations, this new approach shows its potential applications in DFTB parametrization for elements with high angular momentum, which present a challenge to conventional methods.

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

TMD phenomenology motivated by nonperturbative structures

This talk summarized work done recently to organize the steps for implementing TMD phenomenology in a way optimized for contexts where the extraction and interpretation of hadronic structures and nonperturbative effects is the primary driving motivation.

Rogers, Ted↗
DOE OSTI2022

Automatic parameter selection for electron ptychography via Bayesian optimization

Abstract Electron ptychography provides new opportunities to resolve atomic structures with deep sub-angstrom spatial resolution and to study electron-beam sensitive materials with high dose efficiency. In practice, obtaining accurate ptychography images requires simultaneously optimizing multiple parameters that are often selected based on trial-and-error, resulting in low-throughput experiments and preventing wider adoption. Here, we develop an automatic parameter selection framework to circumvent this problem using Bayesian optimization with Gaussian processes. With minimal prior knowledge, the workflow efficiently produces ptychographic reconstructions that are superior to those processed by experienced experts. The method also facilitates better experimental designs by exploring optimized experimental parameters from simulated data.

42 ENGINEERING↗
DOE OSTI2023

Evaluation of the Reconstruction Accuracy of the Ultrasound Model–Based Image Reconstruction (U-MBIR) Method for Concrete to Optimize Damage Detection

Reinforced concrete is a critical structural material used to construct nuclear power plants (NPPs). As such, its safety and performance must be thoroughly examined throughout the life cycle of the NPP infrastructure system. Ultrasonic measurements have been an industry standard for both surface and subsurface inspections. To support the development of these techniques, Oak Ridge National Laboratory (ORNL) has researched and developed advanced image reconstruction algorithms to capture internal damage. The results and discussion presented herein summarize the current state of the ultrasonic model–based iterative reconstruction (U-MBIR) algorithm developed at ORNL. In the work documented in this report, the U-MBIR methodology was applied to four sets of ultrasonic data collected from concrete specimens. The results demonstrate that the U-MBIR algorithm can successfully detect defects within the four concrete samples. The reconstruction images help identify the specimen thickness, regions of delamination, and location of rebar embedded within the concrete. The reconstruction images allow engineers and technicians to characterize the internal defects within concrete specimens and structural members. Ultimately, this knowledge can guide engineers in making informed decisions regarding the performance, safety, and reliability of structural materials (i.e., reinforced concrete) throughout the life cycle of NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

New high-throughput endstation to accelerate the experimental optimization pipeline for synchrotron X-ray footprinting

Synchrotron X-ray footprinting (XF) is a growing structural biology technique that leverages radiation-induced chemical modifications via X-ray radiolysis of water to produce hydroxyl radicals that probe changes in macromolecular structure and dynamics in solution states of interest. The X-ray Footprinting of Biological Materials (XFP) beamline at the National Synchrotron Light Source II provides the structural biology community with access to instrumentation and expert support in the XF method, and is also a platform for development of new technological capabilities in this field. Hee, the design and implementation of a new high-throughput endstation device based around use of a 96-well PCR plate form factor and supporting diagnostic instrumentation for synchrotron XF is described. This development enables a pipeline for rapid comprehensive screening of the influence of sample chemistry on hydroxyl radical dose using a convenient fluorescent assay, illustrated here with a study of 26 organic compounds. The new high-throughput endstation device and sample evaluation pipeline now available at the XFP beamline provide the worldwide structural biology community with a robust resource for carrying out well optimized synchrotron XF studies of challenging biological systems with complex sample compositions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Structure of a HIV-1 IN-Allosteric inhibitor complex at 2.93 Å resolution: Routes to inhibitor optimization

HIV integrase (IN) inserts viral DNA into the host genome and is the target of the strand transfer inhibitors (STIs), a class of small molecules currently in clinical use. Another potent class of antivirals is the allosteric inhibitors of integrase, or ALLINIs. ALLINIs promote IN aggregation by stabilizing an interaction between the catalytic core domain (CCD) and carboxy-terminal domain (CTD) that undermines viral particle formation in late replication. Ongoing challenges with inhibitor potency, toxicity, and viral resistance motivate research to understand their mechanism. Here, we report a 2.93 Å X-ray crystal structure of the minimal ternary complex between CCD , CTD , and the ALLINI BI-224436. This structure reveals an asymmetric ternary complex with a prominent network of π-mediated interactions that suggest specific avenues for future ALLINI development and optimization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Elucidating the Interfacial Effects of Nonmetallic Elements on the Dehydrogenation Behavior of Nanoconfined NaAlH 4 in Zeolite-Templated Carbon

Confining materials within nanoscale volumes alters their physical and chemical properties, with positive consequences for energy storage, conversion, and catalysis. The pore structure and composition of scaffolds are essential variables for optimizing these properties, with carbon-based materials being preferred due to their tunable porous structures and chemical versatility. This study investigates the influence of surface functional groups on the dehydrogenation kinetics of nanoconfined NaAlH4 using zeolite-templated carbons (ZTCs). Here we focus on oxygen functional groups commonly present as intrinsic impurities on carbon scaffolds, analyzing three ZTC scaffolds to determine how their concentrations and configurations affect dehydrogenation behavior. Our findings reveal that carbonyl groups enhance charge transfer and destabilize Al–H bonds more effectively than ether or phenol groups. This indicates that the type of oxygen functional group is more critical than the quantity, highlighting the importance of properly tailoring oxygen defects to improve hydrogen storage performance in nanoconfined systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Chance-Constrained Optimization for Critical Infrastructure Protection

Stochastic optimization deals with making highly reliable decisions under uncertainty. Chance constraints are a crucial tool of stochastic optimization to develop mathematical optimization models; they form the backbone of many important national security data science applications. These include critical infrastructure resiliency, cyber security, power system operations, and disaster relief management. However, existing algorithms to solve chance-constrained optimization models are severely limited by problem size and structure. In this investigative study, we (i) develop new algorithms to approximate chance-constrained optimization models, (ii) demonstrate the application of chance-constraints to a national security problem, and (iii) investigate related stochastic optimization problems. We believe our work will pave way for new research is stochastic optimization as well as secure national infrastructures against unforeseen attacks.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2019

Gating System Design Optimization for Investment Casting Process

This article aims to optimize specific castings, characterized as an element of the continuous track for armored vehicle. During the primary melts, defects in the form of oxide films and shrinkage porosity occurred. Steel 20ChGSNM described by the Russian GOST standard was used as a batch material, and the investment casting method was selected for production. To eliminate the above-mentioned defects, only changes in the gating system were allowed, because the interference with an ongoing production regarding technical and technological parameters was unacceptable by the manufacturer. Numerical simulation, x-ray, macro-structural and micro-structural analysis were used during the optimization process. The three variants were analyzed, and the achieved results demonstrated that it is possible to significantly affect the casting internal homogeneity by modifying the gating system individual parts. The final variant ensured a decrease in defects by up to 90% and the production of casting having the quality required by the customer.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Compromise between band structure and phonon scattering in efficient n-Mg 3 Sb 2-x Bi x thermoelectrics

n-type Mg 3 Sb 2 -based materials have become a top candidate for efficient thermoelectric applications within 300–700 K, due to its high band degeneracy, inherently high carrier mobility and low lattice thermal conductivity, as well as its advantages of less toxicity and abundance. Existing works showed that Mg 3 Bi 2 -alloying largely help ensure the exceptional performance, leaving a key issue to be uncovered on the primary mechanisms favoring or limiting the thermoelectric performance of Mg 3 Sb 2-x Bi x alloys. Furthermore we focus on the alloy composition dependent transport properties at various temperatures, with a large volume of experimental data. It is revealed that, with increasing x, the reduction in both inertial mass and lattice thermal conductivity is significantly beneficial, but the closure in band gap leads to a strong compensation due to the bipolar effect. Such a compromise between band structure and phonon scattering results in optimal Mg 3 Bi 2 -alloying concentrations to be about 50%–75% at 300 K, 50%–60% at 450 K and 50% at 600 K, which successfully guiding this work to realize extraordinary thermoelectric figure of merit at these temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Review on organosulfur materials for rechargeable lithium batteries

Organic electrode materials have been considered as promising candidates for the next generation rechargeable battery systems due to their high theoretical capacity, versatility, and environmentally friendly nature. Among them, organosulfur compounds have been receiving more attention in conjunction with the development of lithium-sulfur batteries. Usually, organosulfide electrodes can deliver relatively high theoretical capacity based on reversible breakage and formation of disulfide (S-S) bonds. Here, we provide an overview of organosulfur materials for rechargeable lithium batteries, including their molecular structural design, structure related electrochemical performance study as well as electrochemical performance optimization. In addition, recent progress of advanced characterization techniques for investigation of the structure and lithium storage mechanism of organosulfur electrodes are elaborated. To further understand the perspective application, additive effect of organosulfur compounds for lithium metal anodes, sulfur cathodes as well as high voltage inorganic cathode materials are reviewed with typical examples. Finally, some remaining challenges and perspective of the organosulfur compounds as lithium batteries components are also discussed. This review is intended to serve as a general guidance for researcher to facilitate the development of organosulfur compounds.

25 ENERGY STORAGE↗
DOE OSTI2018

Optimizing Native Ion Mobility Q-TOF in Helium and Nitrogen for Very Fragile Noncovalent Structures

The amount of internal energy imparted to the ions prior to the ion mobility cell influences the ion structure and thus the collision cross section. Non-covalent complexes with few internal degrees of freedom and/or high charge densities are particularly sensitive to collisional activation. Here, we investigated the effects of virtually all tuning parameters of the Agilent 6560 IM-Q-TOF on the arrival time distributions of ubiquitin{sup 7+} and found conditions in which the native state prevails. We discuss the effects of solvent evaporation conditions in the source, of the entire pre-IM DC voltage gradient, of the funnel RF amplitudes. We also report on ubiquitin{sup 7+} conformations in different solvents, including native supercharging conditions. Collision-induced unfolding (CIU) can be conveniently provoked either behind the source capillary or in the trapping funnel. The softness of the instrumental conditions behind the mobility cell was further optimized with the DNA G-quadruplex [(dG{sub 4}T{sub 4}G{sub 4}){sub 2}·(NH{sub 4}{sup +}){sub 3}-8H]{sup 5−}, for which ion activation results in ammonia loss. To reduce the ion internal energy and obtain the intact 3-NH{sub 4}{sup +} complex, we reduce the post-IM voltage gradient, but this results in a lower IM resolving power due to increased diffusion behind the drift tube. The article describes the various trade-offs between ion activation, ion transmission, and ion mobility performance for native MS of very fragile structures. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Genetic Algorithms for Rapid Molecular Materials Screening

This project developed efficient methods for rapid computational screening of conjugated polymers and oligomers with optimal or near-optimal photovoltaic, dielectric, spintronic, and other unique electronic structure properties using genetic algorithms (GA). A key promise of organic materials is that using the incredible tailorability of synthetic organic chemistry enables experimental optimization of performance across multiple relevant properties (e.g., organic photovoltaics, organic lasers). The fundamental challenge is inverse design: how does one find the molecular or polymer structures with desired properties in the face of a near-infinite (e.g., >10 20 - 10 60 ) number of possible molecular structures, combined with time-consuming experiments or electronic structure calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Community detection in sequence similarity networks based on attribute clustering

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs, for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments

59 BASIC BIOLOGICAL SCIENCES↗