Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Shape”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Ruggedness Evaluation of ASTM International Standard Test Methods for Shape Memory Materials: E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys

This paper evaluates the ruggedness testing of the newly released ASTM International E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys. The ruggedness experiment was designed with eight runs in two replicates, consisting of seven factors of strain rate (ė), heating and cooling rates (Ṫ(heat) and Ṫ(cool), respectively), upper and lower cycle temperatures (UCT and LCT, respectively), hold time (thold), and minimum load (Fmin) imparted on the samples. The results indicate that the hold time factor had no effect on any result variable. The minimum load factor, alternatively, had the greatest effect on several result variables, with the greatest influence on the strains at martensite start and finish (strain variation ~0.1 percent), and the strains at the upper and lower cycle temperatures (strain variation of 0.14 percent). The UCT was found to have a large effect on the austenite and martensite finish tangent line and data intersect, denoted by Af* and Mf*, by ~17 and 4 °C, respectively. The testing methodology, analysis techniques, and resulting conclusions on the ruggedness of the test methods are presented.

shape memory alloy↗
NASA NTRS2023

Ruggedness Evaluation of ASTM International Standard Test Methods for Shape Memory Materials: E3098 Standard Test Method for Mechanical Uniaxial Pre-strain and Thermal Free Recovery of Shape Memory Alloys

This paper evaluates the ruggedness testing of the recently released ASTM International E3098 Standard Test Method for Mechanical Uniaxial Pre-strain and Thermal Free Recovery of Shape Memory Alloys. The ruggedness experiment was designed with eight runs in two replicates, consisting of seven factors: strain rate (ė), heating and cooling rates (Ṫ heat and Ṫ cool , respectively), upper and lower cycle temperatures (UCT and LCT, respectively), hold time (t hold ), and minimum load (F min ) imparted on the samples. The results indicate that the strain rate factor had no effect on any result variable, whereas the minimum load factor had a large effect on several result variables including the austenite start and martensite finish temperatures as well as most of the strain measurements from the thermal cycle. The lower cycle temperature factor had a large effect on the stress at maximum strain during pre-straining (e i ), denoted by S i , at ~7.2 MPa, as well as the A f , at 5.47 °C. Closely following the LCT effect, Ṫ heat was found to have a large effect on the austenite start temperature (A s ), at a value of ~2.72 °C. The testing methodology, analysis techniques, and resulting conclusions on the ruggedness of the test method are presented.

Shape memory alloys↗
NASA NTRS1980

An empirical model of the Venusian outer environment. I - The shape of the dayside solar wind-atmosphere interface. II - The shape and location of the bow shock

Solar wind plasma and magnetic field data and ionospheric data obtained from the Pioneer Venus orbiter are discussed. The variation in the magnetic field pressure within the magnetic barrier is shown to be similar to that expected for the solar wind pressure variations along an obstacle's boundary when a more realistic approximation of the shape of the ionosphere is included. Simultaneous solar wind pressure, ionospheric pressure, and magnetic barrier pressure data reveal that the ionospheric pressure below the ionopause is approximately equal to the solar wind pressure. The magnetic barrier pressure is found to be equal to approximately 2/3 to 3/4 of both the solar wind pressure and the ionospheric pressure. Estimates of the hot plasma pressure contribution to the total pressure in the magnetic barrier vary from 1/4 to 1/3. Just below the ionopause the ionospheric pressure deviations from the mean ionospheric pressure are significant, especially below approximately 400 km; they appear to be indicative of the adjustment of the ionospheric structure to changeing solar wind conditions. A first-order model of the ionopause pressure variations as a function of height and solar-zenith angle is proposed. Venera 9 and Venera 10 bow shock crossings are then analyzed for solar zenith angles in the range from approximately 25 deg to approximately 153 deg. A comparison of Venera 9 and Venera 10 bow shock crossings with those observed by the Pioneer Venus orbiter suggests that both the secular variation and the latitudinal asymmetry may be responsible for the closer shock crossings of the Venera 9 and Venera 10 spacecraft.

Vaisberg, O. L.↗
NASA NTRS2011

An Estimate of the Size and Shape of Sunspot Cycle 24 Based on its Early Cycle Behavior using the Hathaway-Wilson-Reichmann Shape-Fitting Function

On the basis of 12-month moving averages (12-mma) of monthly mean sunspot number (R), sunspot cycle 24 had its minimum amplitude (Rm = 1.7) in December 2008. At 12 mo past minimum, R measured 8.3, and at 18 mo past minimum, it measured 16.4. Thus far, the maximum month-to-month rate of rise in 12-mma values of monthly mean sunspot number (AR(t) max) has been 1.7, having occurred at elapsed times past minimum amplitude (t) of 14 and 15 mo. Compared to other sunspot cycles of the modern era, cycle 24?s Rm and AR(t) max (as observed so far) are the smallest on record, suggesting that it likely will be a slow-rising, long-period sunspot cycle of below average maximum amplitude (RM). Supporting this view is the now observed relative strength of cycle 24?s geomagnetic minimum amplitude as measured using the 12-mma value of the aa-geomagnetic index (aam = 8.4), which also is the smallest on record, having occurred at t equals 8 and 9 mo. From the method of Ohl (the inferred preferential association between RM and aam), one predicts RM = 55 +/- 17 (the ?1 se prediction interval) for cycle 24. Furthermore, from the Waldmeier effect (the inferred preferential association between the ascent duration (ASC) and RM) one predicts an ASC longer than 48 mo for cycle 24; hence, maximum amplitude occurrence should be after December 2012. Application of the Hathaway-Wilson-Reichmann shape-fitting function, using an RM = 70 and ASC = 56 mo, is found to adequately fit the early sunspot number growth of cycle 24.

Wilson, Robert M.↗
NASA NTRS2019

Ruggedness Evaluation of ASTM International Standard Test Methods for Shape Memory Materials: E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys

This paper evaluates the ruggedness testing of the newly released ASTM International E3097 Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of Shape Memory Alloys. The ruggedness experiment was designed with eight runs in two replicates, consisting of seven factors of strain rate (ė), heating and cooling rates (T(sub heat) and T(sub cool), respectively), upper and lower cycle temperatures (UCT and LCT, respectively), hold time (t(sub hold)), and minimum load (F(sub min)) imparted on the samples. The results indicate that the hold time factor had no effect on any result variable. The minimum load factor, alternatively, had the greatest effect on several result variables, with the greatest influence on the strains at martensite start and finish (strain variation ~0.1 percent), and the strains at the upper and lower cycle temperatures (strain variation of 0.14 percent). The UCT was found to have a large effect on the austenite and martensite finish tangent line and data intersect, denoted by A(sub f(sup *)) and M(sub f(sup*)), by ~17 and 4 °C, respectively. The testing methodology, analysis techniques, and resulting conclusions on the ruggedness of the test methods are presented.

Benafan, Othmane↗
DOE OSTI2026

How nitrogen and oxygen shape SRF cavity performance

Nitrogen and oxygen-based surface treatments have revolutionized the performance of superconducting radiofrequency (SRF) cavities, enabling them to reach higher gradients and lower losses. However, the exact mechanisms by which these treatments improve cavity performance remain largely unknown. This work provides new insights into the role of nitrogen and oxygen in SRF cavity performance by using time-of-flight secondary ion mass spectrometry (TOF-SIMS) to precisely quantify the concentrations and depth profiles of these impurities within niobium cutouts. We correlate these impurity profiles with detailed cavity performance measurements, including surface resistance and quality factor, and compare our findings with predictions from BCS theory. The results demonstrate that while both nitrogen and oxygen enhance performance, ten times more oxygen is required to achieve the same reduction in BCS resistance as interstitial nitrogen. We present a potential model in which the observed variation arises from nitrogen's greater effectiveness in trapping hydrogen, thus reducing the formation of niobium hydrides and enhancing superconducting gap.

Hu, Hannah [Chicago U.]↗
NASA NTRS1998

Pulse Shaped 8-PSK Bandwidth Efficiency and Spectral Spike Elimination

The most bandwidth-efficient communication methods are imperative to cope with the congested frequency bands. Pulse shaping methods have excellent effects on narrowing bandwidth and increasing band utilization. The position of the baseband filters for the pulse shaping is crucial. Post-modulation pulse shaping (a low pass filter is located after the modulator) can change signals from constant envelope to non-constant envelope, and non-constant envelope signals through non-linear device (a SSPA or TWT) can further spread the power spectra. Pre-modulation pulse shaping (a filter is located before the modulator) will have constant envelope. These two pulse shaping methods have different effects on narrowing the bandwidth and producing bit errors. This report studied the effect of various pre-modulation pulse shaping filters with respect to bandwidth, spectral spikes and bit error rate. A pre-modulation pulse shaped 8-ary Phase Shift Keying (8PSK) modulation was used throughout the simulations. In addition to traditional pulse shaping filters, such as Bessel, Butterworth and Square Root Raised Cosine (SRRC), other kinds of filters or pulse waveforms were also studied in the pre-modulation pulse shaping method. Simulations were conducted by using the Signal Processing Worksystem (SPW) software package on HP workstations which simulated the power spectral density of pulse shaped 8-PSK signals, end to end system performance and bit error rates (BERS) as a function of Eb/No using pulse shaping in an AWGN channel. These results are compared with the post-modulation pulse shaped 8-PSK results. The simulations indicate traditional pulse shaping filters used in pre-modulation pulse shaping may produce narrower bandwidth, but with worse BER than those in post-modulation pulse shaping. Theory and simulations show pre- modulation pulse shaping could also produce discrete line power spectra (spikes) at regular frequency intervals. These spikes may cause interference with adjacent channel and reduce power efficiency. Some particular pulses (filters), such as trapezoid and pulses with different transits (such as weighted raised cosine transit) were found to reduce bandwidth and not generate spectral spikes. Although a solid state power amplifier (SSPA) was simulated in the non-linear (saturation) region, output power spectra did not spread due to the constant envelope 8-PSK signals.

Tao, Jian-Ping↗
DOE OSTI2025

A Computational Tool Compatible with NEAMS Code Packages for Optimizing the Shape of Nuclear Reactor Components and of Whole Core Performance

We designed and implemented a shape optimization tool that functions with NEAMS codes, and that nuclear scientists and engineers can employ to optimize the shape of individual components and the whole core under the applicable single- or multi-physics model comprising the employed code(s). The shape-optimization tool enables varying the geometric shape itself as well as its dimensions to yield, potentially, new component designs that are not limited by the designer’s intuition and previous experience. In cases where the optimal-shape object is an individual component, we provide the capability for additional verification that the whole-core performance using the optimized component performs better, under the prescribed optimization criteria, than the initial design. Our shape-optimization tool couples to NEAMS codes via a flexible input- composer interface and enables the user to constrain the shape’s evolution to ensure the component’s manufacturability. Finally, we demonstrate our shape-optimization tool with single- and multi-physics NEAMS codes. This objective is motivated by the recent advances in manufacturing technology that, combined with rising interest in novel reactor concepts, are creating new opportunities for innovation in the design of individual components that affect the performance of the full reactor system. In particular, Additive Manufacturing (AM) enables mass production of highly precise, intricate and complex component shapes that are not feasible with traditional manufacturing techniques. To accomplish this goal we developed and implemented in MOOSE: (1) discrete shape optimization capability based on a state-space search that uses Artificial Intelligence strategies to find the optimal state/shape; (2) smooth shape optimization tool that employs PETSc’s toolkit for advanced optimization (TAO) to optimize node-displacement of the components’ model sidesets; (3) hierarchical core optimization workflow that recognizes the repeating patterns typical in a nuclear reactor and performs the optimization one level at a time with increasing length scale. Each of these tools is equipped with user-specified constraints to avoid optimal shapes that are not manufacturable. The developed shape optimization tool is verified and demonstrated on various nuclear reactor core components and models. The optimization process accounts for tightly coupled physics that govern the behavior of these target reactors, and exercises several NEAMS codes in a coupled multiphysics fashion. The impact of the delivered shape optimization tool will materialize in the optimal design, from the outset, of advanced reactors currently contemplated to regain the US’s leadership in nuclear energy R&D. Novel reactor concepts, e.g. Molten Salt Reactors, and sizes/capacities, e.g. micro- reactors, provide a unique opportunity to optimize performance from the early stages of development, before the investment in components’ production lines, validation experiments, and licensing regimes make future improvements in performance prohibitively expensive and force sub-optimal performance on the affected reactor concept in perpetuity. This benefit will be realized by the delivered shape optimization tool regardless of the applicable manufacturing process whether traditional or AM, thereby broadening the impact of this project on current and future reactor concepts and technologies

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2017

Remote Sensing of Crystal Shapes in Ice Clouds

Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally inconsistent with the data and thus crystal impurity, distortion or surface roughness is prevalent. However, conclusions about the dominating ice shapes are often inconclusive and contradictory and are highly dependent on the limited selection of shapes included in the investigations. Since ice crystal optical properties are mostly determined by the aspect ratios of the crystal components and their microscale structure, it is advised that remote sensing applications focus on the variation of these ice shape characteristics, rather than on the macroscale shape or habit. Recent studies use databases with nearly continuous ranges of crystal component aspect ratio and-or roughness levels to infer the variation of ice crystal shape from satellite and airborne remote sensing measurements. Here, the rationale and results of varying strategies for the remote sensing of ice crystal shape are reviewed. Observed systematic variations of ice crystal geometry with location, cloud height and atmospheric state suggested by the data are discussed. Finally, a prospective is given on the future of the remote sensing of ice cloud particle shapes.

clouds↗
NASA NTRS2013

Absorption Efficiencies of Forsterite. I: DDA Explorations in Grain Shape and Size

We compute the absorption efficiency (Q(sub abs)) of forsterite using the discrete dipole approximation (DDA) in order to identify and describe what characteristics of crystal grain shape and size are important to the shape, peak location, and relative strength of spectral features in the 8 - 40 micron wavelength range. Using the DDSCAT code, we compute Q(sub abs) for non-spherical polyhedral grain shapes with a(sub eff) = 0.1 micron. The shape characteristics identified are: 1) elongation/reduction along one of three crystallographic axes; 2) asymmetry, such that all three crystallographic axes are of different lengths; and 3) the presence of crystalline faces that are not parallel to a specific crystallographic axis, e.g., non-rectangular prisms and (di)pyramids. Elongation/reduction dominates the locations and shapes of spectral features near 10, 11, 16, 23.5, 27, and 33.5 micron, while asymmetry and tips are secondary shape effects. Increasing grain sizes (0.1 - 1.0 micron) shifts the 10, 11 micron features systematically towards longer wavelengths and relative to the 11 micron feature increases the strengths and slightly broadens the longer wavelength features. Seven spectral shape classes are established for crystallographic a-, b-, and c-axes and include columnar and platelet shapes plus non-elongated or equant grain shapes. The spectral shape classes and the effects of grain size have practical application in identifying or excluding columnar, platelet or equant forsterite grain shapes in astrophysical environs. Identification of the shape characteristics of forsterite from 8 - 40 micron spectra provides a potential means to probe the temperatures at which forsterite formed.

circumstellar matter↗
DOE OSTI2024

Development of a Method for Shape Optimization for a Gas Turbine Fuel Injector Design Using Metal-Additive Manufacturing

Adjoint shape optimization has enabled physics-based optimal designs for aerodynamic surfaces. Additive manufacturing (AM) makes it possible to manufacture complex shapes. However, there has been a gap between optimal and manufacturable surfaces due to the inherent limitations of commercial computational fluid dynamics (CFD) codes to implement geometric constraints during adjoint computation. In such cases, the design sensitivities are exported and used to perform constrained shape modifications using parametric information stored in computer aided design (CAD) files to satisfy manufacturability constraints. However, modifying the design using adjoint methods in CFD solvers and performing constrained shape modification in CAD can lead to inconsistencies due to different shape parameterization schemes. This paper describes a method to enable the simultaneous optimization of the fluid domain and impose AM manufacturability constraints, resolving one of the key issues of geometry definition for isogeometric analysis. Similar to a grid convergence study, the proposed method verifies the consistencies between shape parameterization techniques present within commercial CAD and CFD software during mesh movement as a part of the adjoint shape optimization routine. By identifying the appropriate parameters essential to a shape optimization study, the error metric between the different parameterization techniques converges to demonstrate sufficient consistencies for justifiable exchange of data between CAD and CFD. For the identified shape optimization parameters, the error metric to measure the deviation between the two parameterization schemes lies within the AM laser-powder bed fusion (L-PBF) process tolerance. Additionally, comparison for subsequent objective function calculations between iterations of the optimization loop showed acceptable differences within 1% variation between the modified geometries obtained using the two parameterization schemes. This method provides justification for the use of multiphysics guided adjoint design sensitivities computed in CFD software to perform shape modifications in CAD to incorporate AM manufacturability constraints during the shape optimization loop such that optimal designs are also additively manufacturable.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation) [SWR-26-095]

FOILPOLARS (Grassmannian Foil Shape Sweeps for Polar Generation): Multifidelity aerodynamic polar data generation for hydrofoil/tidal-turbine airfoil sections. Foilpolars ties together three pieces: *AeroSandbox supplies the baseline airfoil coordinates (UIUC database). *G2Aero parameterizes those shapes on a Grassmannian manifold (Karcher mean + PGA basis) and samples new perturbed shapes around that basis. *XFoil (panel method) and NeuralFoil (neural-network surrogate, shipped with AeroSandbox) each solve the resulting shapes for lift, drag, moment, and pressure at the swept angles of attack, Reynolds numbers, and n_crit values. Design optimization of foil shapes in a computationally efficient way requires polars data across many candidate shapes, not just a handful of baseline foils. However, high-fidelity CFD at that scale is too costly, and naive shape perturbation strays from realistic geometries. FOILPOLARS addresses this by loading baseline airfoils (via AeroSandbox) and mapping them onto a Grassmannian manifold (via G2Aero), computing a Karcher mean and principal geodesic analysis (PGA) basis. New shapes are sampled by perturbing PGA coefficients, keeping them close to the manifold of realistic foils. Each sampled shape is evaluated across a configurable sweep of angle of attack, Reynolds number, and critical amplification factor using two solvers: XFoil (panel method) and NeuralFoil (neural-network surrogate), producing a paired dataset of lift, drag, moment, pressure, convergence, and confidence, indexed alongside each shape's PGA coefficients and shared Grassmannian basis in a single xarray dataset. From this, FOILPOLARS produces convergence summaries and comparison plots per shape, Reynolds number, and n_crit. A command-line interface exposes each pipeline stage independently, supporting data-driven design, optimization, and machine-learning workflows for foils.

Sandhu, Rimple [National Laboratory of the Rockies↗