Search NASA⌕ Search

SEARCH · Search NASA

Results for “shape 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 1,513 records · Page 84

An optimization method for flexural bearing design for high-stroke high-frequency applications

A method for optimization of a high-stroke, high-frequency flexural bearing was completed. The main goal was to design a flexural bearing system as the energy restoration component of a one kW free piston linear engine alternator (LEA) operating at 90 Hz and maximum targeted displacement of 22 mm. Defined electricity output of 1 kW, with more than 30% efficiency, required engine operation under high speed and high stroke conditions. Under such challenging stroke and frequency requirements, a method of design was required to select between a wide range of parameters in flexural bearing design. A parametric CAD model was prepared and used in the optimization package of a finite element analysis (FEA) software. Four main parameters of flexural bearing geometry were identified and included the outer diameter, thickness, number of arms, and sweep angle of spiral cuts. Other design parameters including spiral gap width, shape factor and spiral start points angle were shown to be less important compared to these four main parameters in primary design and were examined separately. A neural network algorithm was used to investigate the interactions and effects of design parameters. The sensitivity of each parameter on output criteria such as maximum stress and natural frequency was examined and design charts developed. Methods for further modification of the spiral curve at end points were introduced to reduce the maximum stress level by up to 20%. Several steel alloys and a titanium-based alloy were identified as proper material candidates for high cycle applications and the final designed spring was manufactured and tested to validate the FEA results of axial stiffness and strain level throughout the flexure arms. The percent of the flexure’s moving mass was estimated to be 29% with FEA analysis and compared well with the experimental value of 31%. The stress/strain results of the FEA analysis matched with the experimental results – within ±5%.

42 ENGINEERING↗

Defect and satellite characteristics of additive manufacturing metal powders

Metal additive manufacturing (AM) requires high-quality metal powders to three-dimensionally (3D) print metallic components with complex and customizable geometries. The lack of quantification of AM metal powders creates quality control challenges for 3D printed components, increases the uncertainty of printing reliability and net cost of inspected and certified printed components, and reduces the recyclability of used powders. However, critical characteristics of AM metal powders that are decisive factors for the 3D printing process, such as internal porosity, contamination, and satellite feature, remain ambiguous. In this work, we developed a novel approach to 3D quantify key characteristics of AM metal powders down to individual particles by using high-resolution synchrotron x-ray computed tomography. Empowered by the penetrative capability of high-energy x-ray, internal porosity and contamination within as-atomized metal powders from high-entropy alloys to nickel-based superalloys were evaluated. Additionally, the newly-developed dispersion method enables the homogeneous separation of individual particles, and consequently, results in the implementation of 3D particle shape analysis. To resolve a major challenge of identification and quantification of satellite-feature particles in as-atomized AM metal powders, the satellite features were quantitated by modeling and analyzing the shape parameter of local thickness variance. Furthermore, the 3D analytical methods of particle assessment in this study can be applied to other materials systems like rock, food, and pharmaceutical particles, and provide insights for process optimization across powder metallurgy, concrete, food and pharmaceutical manufacturing, and AM industries.

36 MATERIALS SCIENCE↗

Computational fluid dynamics modeling and analysis of silica nanoparticle synthesis in a flame spray pyrolysis reactor

Flame Spray Pyrolysis (FSP) is a method for large-scale production of nanoparticles and nanoscale powders employed in a wide range of industrial applications. Particle size and morphology are complex functions of the physicochemical phenomena occurring in the FSP reactor. An extensive study of FSP-related phenomena can be utilized to develop effective strategies for achieving desired particle size/morphology and scaling up the overall yield of an FSP system. In this work, a computational fluid dynamics (CFD) model of an FSP reactor is developed to simulate the coupling of key phenomena involved in the particle synthesis process: liquid spray breakup and evaporation, mixing, combustion, and particle formation/growth of silica nanoparticles. Herein, the particle sizes and their distributions from the CFD simulations are validated against experimental data. Subsequently, the simulations are utilized to investigate the impact of process parameters on the resultant flame dynamics and particle growth. Firstly, the CFD results show that the particle sizes are strongly correlated with the precursor concentration in the solvent. At lower precursor concentrations, the spread of the distribution is relatively insensitive to the value of the concentration. At higher concentrations, the spread is higher as the collision probability between particles is higher. Secondly, increasing the pilot flow rate increases the length of the pilot flames impacting the local ignition location of the spray flame. Lastly, it is shown that the dispersion gas flow rate strongly influences the spray flame shape. This shape can be used for control of particle growth as it helps determine the regions of high temperature and the residence time of the particles in the high temperature region enabling the design and process optimization of the FSP reactor.

42 ENGINEERING↗

Support-induced morphology and content tailored NiCo 2 O 4 nanostructures on temperature-dependent carbon nanofibers with enhanced pseudocapacitive performance

Direct anchorage of metal oxides on carbon nanofibers is challenging, and simultaneous modulation of morphology, content and thus pseudocapacitance of anchored metal oxides has never been achieved. In this paper, we report direct anchorage of NiCo 2 O 4 nanostructures with tailored morphology, content and pseudocapacitance, on temperature-dependent carbon nanofibers (CNEs), which are derived from zinctrimesic acid fibers at a temperature no more than 600 degrees C. The temperature-dependent CNEs, including CNF-390, CNF-450 and CNF-600, were first investigated by SEM, TG, FT-IR, XPS and Boehm titration studies. It is found that their textural property, thermal stability and surface functionality vary depending on pyrolysis temperature. As a result, the morphology, content and thus the pseudocapacitance of anchored NiCo 2 O 4 nanostructures are also temperature-dependent. It is revealed that as increasing the pyrolysis temperature, the shape of NiCo 2 O 4 is transformed from embedded nanoparticles to exposed nanosheets while its content decreases from 95 to 55 wt%. The resultant NiCo 2 O 4 /CNF-450, bearing highly dispersed nanosheets and optimized NiCo 2 O 4 content (72.6%), exhibits the best capacitive performance with a large specific capacitance of 870 F g -1 at a scan rate of 1 mV s -1 , and a high energy density of 39.3 Wh kg -1 in the case of power density of 300 W kg -1 . The elaborately fabricated NiCo 2 O 4 /CNF-450 also shows excellent charge-discharge stability (with the capacity retention ratio of 85.7% after 5000 cycles). The improved accessibility for more pseudocapacitive NiCo 2 O 4 nanosheets, as well as the strong interaction between NiCo2O4 and carbon nanofiber, should be responsible for the enhanced capacitive performance of NiCo 2 O 4 /CNF-450. Lastly, this research also provides the concept of support-induced modulation of property and pseudocapacitive performance of anchored metal oxides.

36 MATERIALS SCIENCE↗

Understanding the Effect of Sample Geometry on Temperature Distribution during Optical Floating Zone Crystal Growth in Vacuum Environment through Heat Transfer Modeling

Optical floating zone furnaces (OFZ) have had a transformative impact on fundamental science due to their ability to rapidly produce large single crystals of a wide variety of complex materials. However, a quantitative understanding of the OFZ growth environment is generally lacking due to the difficulty of measuring the local sample temperatures during OFZ growth, as well as to the general lack of information about the temperature-dependent physical parameters needed to model heat transfer. To overcome these challenges, we apply a physics-based heat transfer model, parametrized by measurements from synchrotron experiments and a machine-learning (ML) algorithm, to simulate the temperature distributions of samples heated in an OFZ furnace in a vacuum environment. This model is used to quantitatively understand how the sample maximum temperature and temperature gradient (key parameters that influence the success of crystal growth) are affected by the rod size, rod shape, and heat-zone position on the rod. The results of this study can be applied to make informed decisions on how crystal growth parameters can be tuned to modify temperature profiles and to optimize crystal growth outcomes even when data on internal sample temperature profiles (e.g., those obtained through in situ synchrotron experiments) are not accessible.

36 MATERIALS SCIENCE↗

Finite-Temperature Structures of Supported Subnanometer Catalysts Inferred via Statistical Learning and Genetic Algorithm-Based Optimization

Single-atom catalysts (SACs) minimize noble metal utilization and can alter the activity and selectivity of supported metal nanoparticles. However, the morphology of active centers, including single atoms and subnanometer clusters of a few atoms, remains elusive due to experimental challenges. The computational cost to describe numerous cluster shapes and sizes makes direct first-principles calculations impractical. We present a computational framework to enable structure determination for single-atom and subnanometer cluster catalysts. As a case study, we obtained the low energy structures of Pd n (n = 1-21) clusters supported on CeO 2 (111), which are critical components of automobile three-way catalysts. Trained on density functional theory data, a three-dimensional cluster expansion is established using statistical learning to describe the Hamiltonian and predict energies of supported Pdn clusters of any structure. Low energy stable and metastable structures are identified using a Metropolis Monte Carlo-based genetic algorithm in the canonical ensemble at 300 K. We observe that supported single atoms sinter to form bilayer clusters and large cluster isomers share similarities in both shape and energy, and elucidate the significance of the support and microstructure on cluster stability. We discovered a simple surrogate structure-energy model, where the energy per atom scales with the square root of the average first coordination number, which can be used to estimate energies and compare the stability of clusters. Our framework, applicable to any metal/support system, fills an important methodological gap to predict the stability of supported metal catalysts in the subnanometer regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

First demonstration of improved yield with reduced adiabat in inertial confinement fusion implosions on the National Ignition Facility

Laser-driven, indirect-drive inertial confinement fusion (ICF) experiments at the National Ignition Facility (NIF) recently achieved a target gain greater than one, where fusion energy output exceeds input laser energy [Abu-Shawareb et al., Phys. Rev. Lett. 132, 065102 (2024)]. Despite this milestone, gain levels remain insufficient for practical applications such as inertial fusion energy, making performance improvement critical. One promising approach is increasing fuel compression by lowering the implosion adiabat. To explore reduced adiabat, experiments were conducted modifying the laser pulse shape and shock timing of an existing 1.9-MJ-drive implosion design performing near the ignition cliff [Abu-Shawareb et al., Phys. Rev. Lett. 129, 075001 (2022)]. These experiments demonstrated increased compression and fusion yield in ICF implosions at the NIF by using a lower fuel adiabat, and increased compression with a reduced adiabat in high-density carbon ablators. The updated design achieved up to 80% higher fusion yield and 14% greater fuel compression compared to the previous best-performing 1.9-MJ experiment, with repeatable performance, and is the only implosion design to achieve a target gain exceeding one with < 2.04 MJ laser energy. Notably, this work was made possible because of recent advances in target quality and pulse shape control allowing experimental access to the ignition regime, and thereby increased sensitivity to adiabat. This work addresses a long-standing question in ICF research and lays the foundation for higher target gains through optimized implosion strategies. It underscores the potential of reduced adiabat designs to enhance compression and fusion yields for future ICF applications.

Hohenberger, M. [Lawrence Livermore National Labor↗

Throughput Analytics of Cloud Networks

A network of virtual machines at cloud server sites connected over virtual IO connections is a flexible, easily deployable, and cost-effective alternative to a physical network infrastructure with dedicated servers connected over leased fiber lines. We study the throughput performance of such a cloud network by collecting measurements over Google Cloud infrastructure spanning multiple continents. To study its ideal performance and impact of packet losses, we utilize its emulation using dedicated servers and connection hardware emulation devices. We compare the measurements over the cloud network to those over its emulation on a testbed. We examine the throughput profiles of both networks as a function of the round trip time and their utilization-concavity coefficients, estimated using measurements for common TCP versions. The throughput profile's concave-convex shape and its coefficient are critical indicators of the network performance, qualitatively and quantitatively, respectively. The results indicate their overall agreement between the production cloud network and its emulation using dedicated connections, and a near optimal throughput performance of the former except for a few under-performing connections. Also, the number of parallel flows is found to be a dominant factor in optimizing the throughput across various conditions and TCP versions.

Phanekham, Derek↗

Carbide Particle Redistribution in U10Mo Alloy during Hot Rolling Process

The influence of initial carbide particle distribution features on the evolution of particle and stringer distribution within U10Mo alloy during hot rolling was investigated in this study. This work will provide guidance to casting optimization work and identify actionable process changes to eliminate the surface features directly attributed to carbides. Various synthetic microstructure-based finite-element (FE) models were generated with consideration of different parameters (i.e., particle shape, particle volume fraction and particle distribution). Plane-strain compression loading was employed in the FE models to simulate hot rolling to 40% and 80% reductions. Stringer statistics analyses and two-point correlation functions were then performed with the simulated hot-rolling results. The results from stringer analyses show that stringer volume fraction substantially increases with increased rolling reduction for microstructure with particles distributed along grain boundaries, and that microstructures with elliptical particles may have slightly higher stringer volume fractions than those with circular particles. The results also show that the maximum stringer length can increase substantially with increased rolling reduction for microstructures with elliptical particles along grain boundaries, and that the microstructures with higher-aspect-ratio elliptical particles may have higher stringer volume fraction and higher maximum stringer length. Near-surface numbers of particles and particle volume fractions also increase with increased rolling reduction. The results from application of the two-point correlation function show that the particle shape (i.e., circular or elliptical) may not have significant influence on the overall shapes of the correlation curves, and that the correlation curves tend to show higher peaks at short distance and then gradually decrease for microstructures with higher particle volume fractions and particles distributed along grain boundaries.

36 MATERIALS SCIENCE↗

A Framework for Identifying Building Energy Models of Localized Utility Service Areas Using Smart Meter Data

Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Peripheral visual response time to colored stimuli imaged on the horizontal meridian

Two male observers were administered a binocular visual response time task to small (45 min arc), flashed, photopic stimuli at four dominant wavelengths (632 nm red; 583 nm yellow; 526 nm green; 464 nm blue) imaged across the horizontal retinal meridian. The stimuli were imaged at 10 deg arc intervals from 80 deg left to 90 deg right of fixation. Testing followed either prior light adaptation or prior dark adaptation. Results indicated that mean response time (RT) varies with stimulus color. RT is faster to yellow than to blue and green and slowest to red. In general, mean RT was found to increase from fovea to periphery for all four colors, with the curve for red stimuli exhibiting the most rapid positive acceleration with increasing angular eccentricity from the fovea. The shape of the RT distribution across the retina was also found to depend upon the state of light or dark adaptation. The findings are related to previous RT research and are discussed in terms of optimizing the color and position of colored displays on instrument panels.

Haines, R. F.↗

Aerodynamic design and analysis of the AST-200 supersonic transport configuration concept

The design and analysis of a supersonic transport configuration was conducted using linear theory methods in conjunction with appropriate constraints. Wing optimization centered on the determination of the required twist and camber and proper integration of the wing and fuselage. Also included in the design are aerodynamic refinements to the baseline wing thickness distribution and nacelle shape. Analysis to the baseline and revised configurations indicated an improvement in lift-to-drag ratio of 0.36 at the Mach 2.7 cruise condition. Validation of the design is planned through supersonic wing tunnel tests.

Walkley, K. B.↗

Flexible space structure model reduction by modal cost analysis

It is noted that reduced models and reduced controllers for flexible space structures are obtained by retaining those modes which make the greatest contribution to quadratic control objectives. Attention is given to the relative importance of damping, frequency and mode shapes in the mode truncation decisions for the following control objectives: attitude control, vibration suppression and figure control. It is also shown that using Modal Cost Analysis (MCA) on the closed loop modes of the optimally controlled system allows the construction of reduced control policies which feedback only those closed loop coordinates which are most critical to the quadratic control performance criterion. In this manner, the modes which need to be controlled are deduced from truncations of the optimal controller.

Skelton, R. E.↗

An optimization study to minimize surface distortions of a hoop-column antenna

An automated procedure to lessen the tedium of manual approach currently used to minimize surface distortions in a hoop/column antenna is studied. Three fundamental elements are used for the study: (1) The finite element analysis program is used to calculate the antenna surface distortions due to externally applied loads; (2) a general purpose optimization program is used to determine the set of control cable tensions which minimize the antenna surface distortions; and (3) another program is used to calculate the best fit parabola passing through a distorted antenna shape and to calculate the RMS distortion error. The interim results of this feasibility study are given.

Wrenn, G. A.↗

Design optimization of axisymmetric bodies in nonuniform transonic flow

An inviscid transonic code capable of designing an axisymmetric body in a uniform or nonuniform flow was developed. The design was achieved by direct optimiation by coupling an analysis code with an optimizer. Design examples were provided for axisymmetric bodies with fineness ratios of 8.33 and 5 at different Mach numbers. It was shown that by reducing the nose radius and increasing the afterbody thickness of initial shapes obtained from symmetric NACA four-digit airfoil contours, wave drag could be reduced by 29 percent for a body of fineness ratio 8.33 in a nonuniform transonic flow of M = 0.98 to 0.995. The reduction was 41 percent for a body of fineness ratio 5 in a uniform transonic flow of M = 0.925 and 65 percent for the same body but in a nonuniform transonic flow of M = 0.90 to 0.95.

Lan, C. Edward↗

Precluding nonlinear ISI in direct detection long-haul fiber optic systems

Long-distance, high-rate fiber optic systems employing directly modulated 1.55-micron single-mode lasers and conventional single-mode fiber suffer severe intersymbol interference (ISI) with a large nonlinear component. A method of reducing the nonlinearity of the ISI, thereby making linear equalization more viable, is investigated. It is shown that the degree of nonlinearity is highly dependent on the choice of laser bias current, and that in some cases the ISI nonlinearity can be significantly reduced by biasing the laser substantially above threshold. Simulation results predict that an increase in signal-to-nonlinear-distortion ratio as high as 25 dB can be achieved for synchronously spaced samples at an optimal sampling phase by increasing the bias current from 1.2 times threshold to 3.5 times threshold. The high SDR indicates that a linear tapped delay line equalizer could be used to mitigate ISI. Furthermore, the shape of the pulse response suggests that partial response precoding and digital feedback equalization would be particularly effective for this channel.

Swenson, Norman L.↗

A Bell-Curved Based Algorithm for Mixed Continuous and Discrete Structural Optimization

An evolutionary based strategy utilizing two normal distributions to generate children is developed to solve mixed integer nonlinear programming problems. This Bell-Curve Based (BCB) evolutionary algorithm is similar in spirit to (mu + mu) evolutionary strategies and evolutionary programs but with fewer parameters to adjust and no mechanism for self adaptation. First, a new version of BCB to solve purely discrete optimization problems is described and its performance tested against a tabu search code for an actuator placement problem. Next, the performance of a combined version of discrete and continuous BCB is tested on 2-dimensional shape problems and on a minimum weight hub design problem. In the latter case the discrete portion is the choice of the underlying beam shape (I, triangular, circular, rectangular, or U).

Kincaid, Rex K.↗

Characterization of the Temperature Capabilities of Advanced Disk Alloy ME3

The successful development of an advanced powder metallurgy disk alloy, ME3, was initiated in the NASA High Speed Research/Enabling Propulsion Materials (HSR/EPM) Compressor/Turbine Disk program in cooperation with General Electric Engine Company and Pratt & Whitney Aircraft Engines. This alloy was designed using statistical screening and optimization of composition and processing variables to have extended durability at 1200 F in large disks. Disks of this alloy were produced at the conclusion of the program using a realistic scaled-up disk shape and processing to enable demonstration of these properties. The objective of the Ultra-Efficient Engine Technologies disk program was to assess the mechanical properties of these ME3 disks as functions of temperature in order to estimate the maximum temperature capabilities of this advanced alloy. These disks were sectioned, machined into specimens, and extensively tested. Additional sub-scale disks and blanks were processed and selectively tested to explore the effects of several processing variations on mechanical properties. Results indicate the baseline ME3 alloy and process can produce 1300 to 1350 F temperature capabilities, dependent on detailed disk and engine design property requirements.

Gabb, Timothy P.↗