Lift and Moment Characteristics at Subsonic Mach Numbers of Four 10-percent-thick Airfoil Sections of Varying Trailing-edge Thickness
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Abstract not provided.
A wide-band penetrating radar system for measuring the thickness of sea ice is under development. The need for this or a similar system arises as follows: Spatial and temporal variations in the thickness of sea ice are important indicators of heat fluxes between the ocean and atmosphere and, hence, are important indicators of climate change in polar regions. A remote-sensing system that could directly measure the thickness of sea ice over a wide thickness range from aboard an aircraft or satellite would be of great scientific value. Obtaining thickness measurements over a wide region at weekly or monthly time intervals would contribute significantly to understanding of changes in the spatial distribution and of the mass balance of sea ice. A prototype of the system was designed on the basis of computational simulations directed toward understanding what signal frequencies are needed to satisfy partly competing requirements to detect both bottom and top ice surfaces, obtain adequate penetration despite high attenuation in the lossy sea-ice medium, and obtain adequate resolution, all over a wide thickness range. The prototype of the system is of the frequency-modulation, continuous-wave (FM-CW) type. At a given time, the prototype functions in either of two frequency-band/operational-mode combinations that correspond to two thickness ranges: a lower-frequency (50 to 250 MHz) mode for measuring thickness greater than about 1 m, and a higher frequency (300 to 1,300 MHz) mode for measuring thickness less than about 1 m. The bandwidth in the higher-frequency (lesser-thickness) mode is adequate for a thickness resolution of 15 cm; the bandwidth in the lower-frequency (greater-thickness) mode is adequate for a thickness resolution of 75 cm. Although a thickness resolution of no more than 25 cm is desired for scientific purposes, the 75-cm resolution was deemed acceptable for the purpose of demonstrating feasibility. The prototype was constructed as a modified version of a 500-to-2,000-MHz FM-CW radar system developed previously for mapping near-surface internal layers of the Greenland ice sheet. The prototype included two sets of antennas: one for each frequency-band/mode. For Arctic and Antarctic field tests, the prototype was mounted on a sled that was towed across the ice. The Arctic field test was performed in the lower-frequency mode on ice ranging in thickness from 1 to 4 m. In the analysis of the results of the Arctic field test, a comparison of the radar-determined ice thicknesses with actual ice thicknesses yielded an overall mean difference of 14 cm and standard deviation of 30 cm. The Antarctic field test was performed in the higher-frequency mode; analysis of the results led to the conclusion that this mode is useful for measuring thicknesses between 0.5 and 1 m. Several modifications have been conceived for implementation in further development toward an improved practical system: The system would function in a single frequency-band/mode (100 to 1,200 MHz) that would afford a resolution of about 15 cm. There would be a single antenna system that would be optimized for the entire 100-to-1,000-MHz frequency band. To enable ice-thickness surveys over larger areas, the system would be made capable of operating aboard a low-flying aircraft that could be either piloted or robotic. Data-processing techniques to deconvolve the system response have been developed on the basis of impulse-response measurements over a calm ocean. Implementation of these techniques in the system would enable correction for imperfections of the system and would thereby increase the effective sensitivity of the system.
Purpose: The aim of this work was twofold: (1) to examine whether, with standard automatic exposure control (AEC) settings that maintain pixel values in the detector constant, lesion detectability in clinical images decreases as a function of breast thickness and (2) to verify whether a new AEC setup can increase lesion detectability at larger breast thicknesses. Methods: Screening patient images, acquired on two identical digital mammography systems, were collected over a period of 2 yr. Mammograms were acquired under standard AEC conditions (part 1) and subsequently with a new AEC setup (part 2), programmed to use the standard AEC settings for compressed breast thicknesses ≤49 mm, while a relative dose increase was applied above this thickness. The images were divided into four thickness groups: T1 ≤ 29 mm, T2 = 30–49 mm, T3 = 50–69 mm, and T4 ≥ 70 mm, with each thickness group containing 130 randomly selected craniocaudal lesion-free images. Two measures of density were obtained for every image: a BI-RADS score and a map of volumetric breast density created with a software application (VolparaDensity, Matakina, NZ). This information was used to select subsets of four images, containing one image from each thickness group, matched to a (global) BI-RADS score and containing a region with the same (local) VOLPARA volumetric density value. One selected lesion (a microcalcification cluster or a mass) was simulated into each of the four images. This process was repeated so that, for a given thickness group, half the images contained a single lesion and half were lesion-free. The lesion templates created and inserted in groups T3 and T4 for the first part of the study were then inserted into the images of thickness groups T3 and T4 acquired with higher dose settings. Finally, all images were visualized using the ViewDEX software and scored by four radiologists performing a free search study. A statistical jackknife-alternative free-response receiver operating characteristic analysis was applied. Results: For part 1, the alternative free-response receiver operating characteristic curves for the four readers were 0.80, 0.65, 0.55 and 0.56 in going from T1 to T4, indicating a decrease in detectability with increasing breast thickness. P-values and the 95% confidence interval showed no significant difference for the T3-T4 comparison (p = 0.78) while all the other differences were significant (p < 0.05). Separate analysis of microcalcification clusters presented the same results while for mass detection, the only significant difference came when comparing T1 to the other thickness groups. Comparing the scores of part 1 and part 2, results for the T3 group acquired with the new AEC setup and T3 group at standard AEC doses were significantly different (p = 0.0004), indicating improved detection. For this group a subanalysis for microcalcification detection gave the same results while no significant difference was found for mass detection. Conclusions: These data using clinical images confirm results found in simple QA tests for many mammography systems that detectability falls as breast thickness increases. Results obtained with the AEC setup for constant detectability above 49 mm showed an increase in lesion detection with compressed breast thickness, bringing detectability of lesions to the same level.
A recent revision to the ASTM E837 standard for near-surface residual stress measurement by the hole-drilling method describes a new thickness-dependent stress calculation procedure applicable to “thin” and “intermediate” workpieces for which strain versus depth response depends on workpiece thickness. This new calculation procedure differs from that of the prior standard, which applies only to thick workpieces with strain versus depth response independent of thickness. Herein we assess the new calculation procedures by performing hole-drilling residual stress measurements in samples with a range of thickness. Near-surface residual stress is measured in a thick aluminum plate containing near-surface residual stress from a uniform shot peening treatment, and in samples of different thickness removed from the plate at the peened surface. A finite element (FE) model is used to assess consistency between measured residual stress across the range of sample thickness. Measured residual stress varies with sample thickness, with thinner samples exhibiting smaller near-surface compressive stress and a larger gradient of subsurface stress. These trends are consistent with both observed bending (curvature) of the removed samples and the trend in FE-calculated expected residual stress. The measured and expected residual stresses are in good agreement for samples of intermediate thickness, but the agreement decreases with sample thickness. Measured residual stress is invariant with gage circle diameter. The new thickness-dependent stress calculation procedure for hole-drilling provides meaningful improvement compared to thick-workpiece calculations.
Purpose: The accuracy of volume estimated of a treatment planning system is investigated in this study. In addition, the effect of slice thickness on IMRT planning is also studied. Methods: The accuracy in volume determination was investigated using a water phantom containing various objects with known volumes ranging from 1–100cm{sup 3}. The phantom was scanned with different slice thickness (1–10 mm). The CT data sets were sent to Eclipse TPS for contour delineation and volume calculation. The effect of slice thickness on IMRT planning was studied using a commercial phantom containing four different shaped objects. The phantom was scanned with different slice thickness (1–5 mm). IMRT plans were generated for the different CT datasets to calculate TCP, homogeneity (HI) and conformity indices (CI). Results: The variability of volumes with CT slice thickness was significant especially for small volume structures. The minimum and maximum error in the volume estimation is in the range of −2.3% to 92%. On the other hand, with increasing slice thickness, the PTV mean dose and TCP values decreases. Maximum variation of ∼5% was observed in mean dose and ∼2% in TCP with slice thickness change from 1–5 mm. The relative decrease in target volume receiving 95% of prescribed dose is ∼5% slice thickness change from 1–5 mm. HI increases up to 163% and CI decreases by 4% between 1–5 mm slice thickness change, producing highly inhomogeneous and least conformal plan. Conclusion: Accuracy of volume estimation is dependent on CT slice thickness and the contouring algorithm in a TPS. During TPS commissioning and for all clinical protocols, evaluation of volume should be included to provide the limit of accuracy in DVH calculation. A smaller slice thickness provides superior dosimetry with improved TCP values. Thus, the smallest possible slice thickness should be used for IMRT planning.
A sandwich construction consists of a low-density core material with high strength face sheets bounded to the top and bottom surfaces. The construction has been widely used in the aerospace and marine industries due to its outstanding characteristics such as noise absorption, weight minimization, heat insulation, and better bending stiffness. In sandwich structures used in high-performance aircraft, the face sheets are often made of fiber-reinforced composite materials and the core is made of honeycomb. The structures may also have variable thickness so as to satisfy aerodynamic requirements. In the stress analysis, the constant-thickness face sheets are usually considered as membrane and the core is assumed to be inextensible but deformable in the thickness direction. The static behavior of variable-thickness, isotropic and homogeneous sandwich beams was successfully studied by employing a constant-thickness theory but allowing stiffnesses to vary in accordance with local thickness variations. It has been recently found in a refined theory that the analyses based on the constant thickness theory locally can lead to significant errors in structural responses if the sandwich beam is thickness-tapered and the cores are deformable in transverse shear. The errors arise mainly from two factors: (1) the transverse shear components of the membrane forces in the face sheets alter the transverse shears carried by the core; and (2) the face-sheet membrane strains arise from transverse shear deformation of the core. In practice the variable thickness may not only exist in core but also in face sheets. The thickness-variations may even be a type of step function. In this case the transverse shear stress in the face sheets and bending stress in the core should be taken into account in the refined theory mentioned. In the present study, energy principles are employed in deriving governing equations for general bending of anisotropic sandwich beams with variable thickness in both face sheets and cores. Solutions to these equations are based on a finite difference scheme. As an example in application, a simply supported thickness-tapered sandwich beam subject to a concentrated load at its center is considered. Let W' be the maximum deflection of the beam in which face sheets are considered as membrane, while W'' is that based on using the modified refined theory. It is found that W' is always larger than W'', however, the magnitude of (W'- W'') appears to be insensitive to the change of the taper of the beam.
Lightning can pose a potential threat to space launch vehicles. In response to this, rules were created called the Lightning Launch Commit Criteria (LLCC) that help weather personnel evaluate the potential for natural and rocket-triggered lightning. One of the ten LLCC with the least research is called the Thick Cloud Layers rule. To further understand electrification of thick cloud layers and potentially improve the Thick Cloud Layers rule, a database of thick cloud layers that occurred over the Eastern Range was created. This database is then used to create an algorithm for identifying and differentiating thick cloud layers from other cloud types based on radar characteristics, temperature levels in reference to cloud height, and the surface electric field. By analyzing and identifying thick cloud events, this project could help narrow down when thick clouds are occurring and potentially minimize unnecessary launch delays. Events that caused LLCC violations involving the Thick Cloud Layers rule were analyzed by hand using Level-2 NEXRAD radar data from the National Weather Service WSR-88D radar in Melbourne with the program GR2Analyst. Cases that were found to be isolated and not involved with convection were recorded (date, start/end time, location) in a database. Radar data associated with these cases was collected and gridded using Python radar packages. Once gridded, I calculated and recorded for each radar scan the following radar reflectivity driven parameters within an 11x11 km bin centered on each 1 square km grid point: the mean reflectivity colder than 0 degrees Celsius, Maximum Radar Reflectivity (MRR) colder than 0 degrees Celsius, Volume Averaged Height Integrated Radar Reflectivity (VAHIRR), Hydrometeor Identification (HID), the difference between the maximum and mean reflectivity, the cloud depth colder than 0 degrees Celsius, the overall cloud depth, the cloud top, and the cloud bottom. Soundings for each event were used to determine cloud temperature levels, and where the cloud is in relation to the freezing level. Electric field mill data collected over the Eastern Range was used to determine surface electric fields below each cloud. All parameters were analyzed in depth for several thick cloud cases to gain an understanding of typical thick cloud characteristics. Cases of thick clouds and other isolated cloud types were also recorded for training purposes to see if enough differences exist between cloud types to differentiate them with an algorithm. Each case along with its corresponding characteristics was recorded in a database, and this database was used to compare differing cloud types, as well as train the algorithm to detect thick clouds.
Efficient and effective oil spill response requires accurate information regarding slick location, extent, and thickness to direct remediation activities. Of these three, the most challenging to determine is thickness. Ideally, the needed information would be provided by remote sensing instruments, particularly those operating from space. In this study we consider the capability of L-band synthetic aperture radar (SAR) for identifying oil layer thickness for slicks in open water given the range of oil properties and environmental conditions typical in this setting. The goal is to determine layer thickness with precision equivalent to that of the Bonn Agreement Oil Appearance Code. Here we report preliminary results of an ongoing study to determine whether either relative or absolute slick thickness can be determined from L-band SAR. The study has an experimental component, which uses low noise airborne SAR data acquired over slicks to evaluate the capability to determine relative thickness, i.e., to differentiate sheen from zones of varying thicker oil within a slick. The component of the study to evaluate whether absolute thickness can be determined from SAR uses backscatter simulations within a physics- based model of electromagnetic scattering from slicked and unslicked ocean surfaces accounting for oil properties, meteorological conditions, and sea state. As part of the theoretical component of the study, we evaluate the backscatter sensitivity to oil characteristics to determine which properties most influenced the SAR measurements. These results are used to determine whether the oil-to-water ratio or the oil thickness can be quantified with reasonable accuracy based upon SAR backscatter intensities alone or whether it requires calibration to go from relative to absolute thickness. The ratio of the backscatter contrast between clean and slicked ocean surfaces is shown to be sensitive to variations within slicks that well correlate with the oil layer thickness. Determination of absolute thickness is much more challenging given the variation of oil properties as the oil weathers on the sea surface.
X-ray photoelectron spectroscopy (XPS) has been utilized as a versatile method for thickness characterization of various two-dimensional (2D) films. Accurate thickness can be measured simultaneously while acquiring XPS data for chemical characterization of 2D films having thickness up to approximately 10 nm. For validating the developed technique, thicknesses of few-layer graphene (FLG), MoS 2 and amorphous boron nitride (a-BN) layer, produced by microwave plasma chemical vapor deposition (MPCVD), plasma enhanced chemical vapor deposition (PECVD), and pulsed laser deposition (PLD) respectively, were accurately measured. The intensity ratio between photoemission peaks recorded for the films (C 1s, Mo 3d, B 1s) and the substrates (Cu 2p, Al 2p, Si 2p) is the primary input parameter for thickness calculation, in addition to the atomic densities of the substrate and the film, and the corresponding electron attenuation length (EAL). The XPS data was used with a proposed model for thickness calculations, which was verified by cross-sectional transmission electron microscope (TEM) measurement of thickness for all the films. The XPS method determines thickness values averaged over an analysis area which is orders of magnitude larger than the typical area in cross-sectional TEM imaging, hence provides an advanced approach for thickness measurement over large areas of 2D materials. The study confirms that the versatile XPS method allows rapid and reliable assessment of the 2D material thickness and this method can facilitate in tailoring growth conditions for producing very thin 2D materials effectively over a large area. Furthermore, the XPS measurement for a typical 2D material is non-destructive and does not require special sample preparation. Furthermore, after XPS analysis, exactly the same sample can undergo further processing or utilization.
Germanium–tin (GeSn) alloys are emerging as promising materials for mid-infrared optoelectronics and silicon-compatible photonic devices, owing to their tunable direct bandgap. However, the growth of high-quality GeSn films with high Sn content remains challenging due to strain-induced defect formation. In this study, we investigate the role of film thickness on strain-induced relaxation, defect density, and Sn segregation. A series of five samples with varying thicknesses and ∼15% Sn-containing GeSn layers were grown, ranging from the critical thickness for strain relaxation to the onset of Sn segregation. All GeSn samples were analyzed using X-ray diffraction reciprocal space mapping (XRD-RSM) to explore the evolution of strain-induced relaxation as a function of thickness. Photoluminescence measurements reveal that increasing the GeSn thickness enhances strain relaxation while reducing defect-related emission, indicating a decrease in effective defect density prior to reaching the threshold thickness of GeSn layer. At a thickness of ∼150 nm, the GeSn layer shows the onset of Sn segregation, evident in the XRD-RSM spectrum, marking the threshold thickness for Sn segregation. This work defines an effective growth window in terms of thickness (35 to 150 nm) for fabricating relaxed, defect-suppressed GeSn layers with 15% Sn content. These findings emphasize the crucial role of thickness control in balancing strain relaxation and defect suppression, advancing the fabrication of high-quality, high Sn-content relaxed GeSn using molecular beam epitaxy.
Purpose: To quantitatively evaluate the esophageal cancer response to chemoradiation therapy (CRT) by measuring the esophageal wall thickness in CT. Method: Two datasets were used in this study. The first dataset is composed of CT scans of 15 esophageal cancer patients and 15 normal controls. The second dataset is composed of 20 esophageal cancer patients who underwent PET/CT scans before (Pre-CRT) and after CRT (Post-CRT). We first segmented the esophagus using a multi-atlas-based algorithm. The esophageal wall thickness was then computed, on each slice, as the equivalent circle radius of the segmented esophagus excluding the lumen. To evaluate the changes of wall thickness, we computed the standard deviation (SD), coefficient of variation (COV, SD/Mean), and flatness [(Max–Min)/Mean] of wall thickness along the entire esophagus. Results: For the first dataset, the mean wall thickness of cancer patients and normal controls were 6.35 mm and 6.03 mm, respectively. The mean SD, COV, and flatness of the wall thickness were 2.59, 0.21, and 1.27 for the cancer patients and 1.99, 0.16, and 1.13 for normal controls. Statistically significant differences (p < 0.05) were identified in SD and flatness. For the second dataset, the mean wall thickness of pre-CRT and post-CRT patients was 7.13 mm and 6.84 mm, respectively. The mean SD, COV, and flatness were 1.81, 0.26, and 1.06 for pre-CRT and 1.69, 0.26, and 1.06 for post-CRT. Statistically significant difference was not identified for these measurements. Current results are based on the entire esophagus. We believe significant differences between pre- and post-CRT scans could be obtained, if we conduct the measurements at tumor sites. Conclusion: Results show thicker wall thickness in pre-CRT scans and differences in wall thickness changes between normal and abnormal esophagus. This demonstrated the potential of esophageal wall thickness as a marker in the tumor CRT response evaluation. This work was supported in part by the National Cancer Institute Grant R01CA172638.