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At least 1,099 records · Page 61

Helical Face Gear Development Under the Enhanced Rotorcraft Drive System Program

U.S. Army goals for the Enhanced Rotorcraft Drive System Program are to achieve a 40 percent increase in horsepower to weight ratio, a 15 dB reduction in drive system generated noise, 30 percent reduction in drive system operating, support, and acquisition cost, and 75 percent automatic detection of critical mechanical component failures. Boeing s technology transition goals are that the operational endurance level of the helical face gearing and related split-torque designs be validated to a TRL 6, and that analytical and manufacturing tools be validated. Helical face gear technology is being developed in this project to augment, and transition into, a Boeing AH-64 Block III split-torque face gear main transmission stage, to yield increased power density and reduced noise. To date, helical face gear grinding development on Northstar s new face gear grinding machine and pattern-development tests at the NASA Glenn/U.S. Army Research Laboratory have been completed and are described.

Heath, Gregory F.↗

Projection-based multifidelity linear regression for data-scarce applications

Surrogate modeling for systems with high-dimensional quantities of interest remains challenging, particularly when training data are costly to acquire. This work develops multifidelity methods for multiple-input multiple-output linear regression targeting data-limited applications with high-dimensional outputs. Multifidelity methods integrate many inexpensive low-fidelity model evaluations with limited, costly high-fidelity evaluations. We introduce two projection-based multifidelity linear regression approaches with linear and nonlinear features that leverage principal component basis vectors for dimensionality reduction and combine multifidelity data through: (i) a direct data augmentation using low-fidelity data, and (ii) a data augmentation incorporating explicit linear corrections between low-fidelity and high-fidelity data. The data augmentation approaches combine high-fidelity and low-fidelity data into a unified training set and train the linear regression model through weighted least squares with fidelity-specific weights. We introduce a proximity-based weighting scheme with automatic weight selection strategy through cross-validation. Here, the proposed multifidelity linear regression methods are demonstrated on approximating the surface pressure field of a hypersonic vehicle in flight and the temperature field on an aircraft disc braking system. In an ultra low-data regime of no more than twelve high-fidelity samples, multifidelity linear regression achieves approximately 2% – 12% improvement in median accuracy and a higher R 2 score relative to single-fidelity methods at comparable computational cost.

data augmentation↗

Fast-RF-Shimming: Accelerate RF shimming in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical diagnostics and advanced research. However, the jump to higher fields introduces complications, particularly transmit radiofrequency (RF) field ($B^{+}_{1}$) inhomogeneities, manifesting as uneven flip angles and image intensity irregularities. These artifacts can degrade image quality and impede broader clinical adoption. Traditional RF shimming methods, such as Magnitude Least Squares (MLS) optimization, effectively mitigate $B^{+}_{1}$ inhomogeneity, but remain time-consuming. Recent machine learning approaches, including RF Shim Prediction by Iteratively Projected Ridge Regression and other deep learning architectures, suggest alternative pathways. Although these approaches show promise, challenges such as extensive training periods, limited network complexity, and practical data requirements persist. In this paper, we introduce a holistic learning-based framework called Fast-RF-Shimming, which achieves a 5000 ​× ​speed-up compared to the traditional MLS method. In the initial phase, we employ random-initialized Adaptive Moment Estimation (Adam) to derive the desired reference shimming weights from multi-channel $B^{+}_{1}$ fields. Next, we train a Residual Network (ResNet) to map $B^{+}_{1}$ fields directly to the ultimate RF shimming outputs, incorporating the confidence parameter into its loss function. Finally, we design Non-uniformity Field Detector (NFD), an optional post-processing step, to ensure the extreme non-uniform outcomes are identified. Comparative evaluations with standard MLS optimization underscore notable gains in both processing speed and predictive accuracy, which indicates that our technique shows a promising solution for addressing persistent inhomogeneity challenges.

Deep learning↗

Implementation of the Molecular Electrostatic Potential over Graphics Processing Units

The molecular electrostatic potential (MEP) generated by quantum chemistry methods and Gaussian functions is evaluated over graphics processing units (GPUs). This implementation is based on full-range Rys polynomials with nodes and weights obtained in each thread of a GPU. For high angular moments, the corresponding integral is solved using a one dimension vertical recurrence relation. Thus, we computed the MEP with minimal approximations. We show that this implementation is stable and very efficient since the time consumed over GPUs is quite small compared with similar implementations over CPUs. The implementation was done by using CUDA-C programming techniques within the Graphics Processing Units for Atoms and Molecules (GPUAM) project, which has been designed to analyze quantum chemistry fields over heterogeneous computational resources. With this new scalar field GPUAM is a useful application for the quantum chemistry community, in particular for people interested in chemical reactivity analysis.

Cruz-Monterrosas, Julio-Cesar↗

Heavy Duty Commercial Vehicle Platooning Energy Benefits for Conventional and Electrified Powertrains

Heavy duty vehicle platooning under highway operating conditions, has been projected to provide significant fuel economy gains based on aerodynamic drag improvements of the platooning vehicles. Realizing these benefits under real-world operating conditions presents several challenges. This paper (the first as part of series) provides a framework to quantify the fuel economy benefits of both conventional and electrified powertrains operating across the U.S. Interstate highway system. In addition to the powertrain, key interactions that are explored include the vehicle separation distance, baseline vehicle aerodynamic properties, vehicle weight, number of vehicles in the platoon, excursions from road speed limits, and particular traffic interactions. While the approach makes use of a limited fidelity vehicle model for longitudinal dynamics, the narrative provides application decision personnel with a mechanism and well-defined set of fuel economy impact factors to consider as part of their architecture selection process.

Sujan, Vivek↗

Charge injection device as a candidate sensor for stellar tracking

Charge transfer devices (CTDs) are superior to the image dissector as stellar tracking sensors, considering their low voltage requirements, insensitivity to magnetic fields, good linearity, and low weight and power. An analysis of one type of CTD, called the charge injection device (CID), revealed an X-Y addressing capability which provides exceptional flexibility in array readout and results in enhanced S/N capability, a surface channel device which produces a larger dynamic range of operation, and exceptional and unique tolerance to optical overloads. A 128 row by 128 column CID array processed on silicon was evaluated in a cooled breadboard camera, and measured results indicate projected performance parameters of a large area CID array as follows: 20 micron square sensing site, noise not greater than 25 carriers per pixel, quantum yield of approximately 40% from 0.4 to 1.0 micron, and cooling requirements on the order of 0 degrees C.

Jones, C. S., Jr.↗

Conceptual design study for an advanced cab and visual system, volume 1

A conceptual design study was conducted to define requirements for an advanced cab and visual system. The rotorcraft system integration simulator is for engineering studies in the area of mission associated vehicle handling qualities. Principally a technology survey and assessment of existing and proposed simulator visual display systems, image generation systems, modular cab designs, and simulator control station designs were performed and are discussed. State of the art survey data were used to synthesize a set of preliminary visual display system concepts of which five candidate display configurations were selected for further evaluation. Basic display concepts incorporated in these configurations included: real image projection, using either periscopes, fiber optic bundles, or scanned laser optics; and virtual imaging with helmet mounted displays. These display concepts were integrated in the study with a simulator cab concept employing a modular base for aircraft controls, crew seating, and instrumentation (or other) displays. A simple concept to induce vibration in the various modules was developed and is described. Results of evaluations and trade offs related to the candidate system concepts are given, along with a suggested weighting scheme for numerically comparing visual system performance characteristics.

Rue, R. J.↗

Effect of spaceflight on isoflavonoid accumulation in etiolated soybean seedlings

In order to explore the potential impact of microgravity on flavonoid biosynthesis, we examined isoflavonoid levels in soybean (Glycine max) tissues generated under both spaceflight and clinorotation conditions. A 6-day Space Shuttle-based microgravity exposure resulted in enhanced accumulation of isoflavone glycosides (daidzin, 6"-O-malonyl-7-O-glucosyl daidzein, genistin, 6"-O-malonyl-7-O-glucosyl genistein) in hypocotyl and root tissues, but reduced levels in cotyledons (relative to 1g controls on Earth). Soybean seedlings grown on a horizontally rotating clinostat for 3, 4 and 5 days exhibited (relative to a vertical clinorotation control) an isoflavonoid accumulation pattern similar to the space-grown tissues. Elevated isoflavonoid levels attributable to the clinorotation treatment were transient, with the greatest increase observed in the three-day-treated tissues and smaller increases in the four- and five-day-treated tissues. Differences between stresses presented by spaceflight and clinorotation and the resulting biochemical adaptations are discussed, as is whether the increase in isoflavonoid concentrations were due to differential rates of development under the "gravity" treatments employed. Results suggest that spaceflight exposure does not impair isoflavonoid accumulation in developing soybean tissues and that isoflavonoids respond positively to microgravity as a biochemical strategy of adaptation.

Flight Experiment↗

Response of the neuromuscular unit to spaceflight: what has been learned from the rat model

Despite the inherent limitations placed on spaceflight investigations, much has been learned about the adaptations of the neuromuscular system to weightlessness from studies of rats flown for relatively short periods (approximately 4-22 days). Below is a summary of the major effects of spaceflight observed in muscles of rats that are not in their rapid growth stage: 1. Skeletal muscles atrophy rapidly during spaceflight; significant atrophy is observed as early as after 4 days of flight. 2. The atrophic response appears to be related to the primary function of the muscle. In the hindlimb, the relative amount of atrophy can be characterized as slow extensors > fast extensors > fast flexors. This pattern of relative atrophy does not appear to be occurring in the forelimb; however, not enough data are available to draw any definitive conclusions at this time. 3. Both slow and fast fibers atrophy during spaceflight, with the largest fibers within an individual muscle generally showing the greatest atrophic response. Interestingly, the amount of fiber atrophy appears to reach a plateau after about 14 days of flight. 4. Adaptations have been observed in the concentration and content of all muscle proteins pools, with the protein pools in slow muscles the most affected. 5. Some slow and fast fibers in predominantly slow and fast muscles show shifts in their histochemical and biochemical properties, toward those observed in a "faster" phenotype. 6. Some fibers, presumably expressing slow MHC isoforms before flight, begin to express fast MHC isoforms during flight. 7. The oxidative capacity of the muscles or fibers is relatively unaffected by spaceflight, particularly in the slow muscles. Any change in whole-body fatigability associated with spaceflight most likely reflects the loss in muscle and fiber mass. 8. The glycolytic capacity of the muscles and muscle fibers is enhanced after spaceflight. This metabolic adaptation seems to be related to the shift in the contractile proteins towards "faster" isoforms. 9. The vascularity of muscles appears to be maintained after flight, based, at least, on histological observations of capillarity. 10. The force capabilities of the muscles and fibers appear to decrease in parallel with the decreases in size, i.e., the specific tension is not significantly affected after flight. 11. Changes in the speed-related properties of the slow muscles are consistent with the adaptations in the myosin molecule, i.e., the slow muscles and some fibers in the slow muscles become "faster." 12. Some muscle fiber and neuromuscular junction damage has been observed after flight, particularly in the slow muscles. The extent of damage may be related to the amount of time that the muscles are allowed to reload before removal, i.e., in general, shorter intervals result in less fiber damage. 13. Adaptations in the motor (ventral horn) and sensory (spinal ganglia) neurons have been quite variable, but this may be related to the amount of time that the muscles are allowed to reload before removal. Morphological adaptations after relatively short periods of reloading may reflect a decrease in the activation of the neural elements during flight.

manned↗

Nuclear morphometric analysis of osteoblast precursor cells in periodontal ligament, SL-3 rats

Five small (55 days old, 196 +/- 5 g) (mean +/- SE) and five large (83 days old, 382 +/- 4 g) Sprague-Dawley strain, specific pathogen-free rats were exposed to a 7-day spaceflight and 12-h postflight recovery period. As measured in 3-micron sections, periodontal ligament (PDL) fibroblastlike cells were classified according to nuclear size: A + A' (40-79), B (80-119), C (120-169), and D (greater than or equal to 170 microns 3). Since the histogenesis sequence is A----A'----C----D----osteoblast, the relative incidence of A + A' to C + D is an osteogenic index. No difference in A + A' or C + D cells in small rats may reflect partial recovery of preosteoblast formation (A----C) during the 12-h postflight period. Large flight rats demonstrated increased numbers of A + A', indicating an inhibition of preosteoblast formation (A----C). At least in the older group, a 7-day flight is adequate to reduce PDL osteogenic potential (inhibition in PDL osteoblast differentiation and/or specific attrition of C + D cells) that does not recover by 12-h postflight.

Flight Experiment↗

Comparative Study of 3-Dimensional Woven Joint Architectures for Composite Spacecraft Structures

The National Aeronautics and Space Administration (NASA) Exploration Systems Mission Directorate initiated an Advanced Composite Technology (ACT) Project through the Exploration Technology Development Program in order to support the polymer composite needs for future heavy lift launch architectures. As an example, the large composite structural applications on Ares V inspired the evaluation of advanced joining technologies, specifically 3D woven composite joints, which could be applied to segmented barrel structures needed for autoclave cured barrel segments due to autoclave size constraints. Implementation of these 3D woven joint technologies may offer enhancements in damage tolerance without sacrificing weight. However, baseline mechanical performance data is needed to properly analyze the joint stresses and subsequently design/down-select a preform architecture. Six different configurations were designed and prepared for this study; each consisting of a different combination of warp/fill fiber volume ratio and preform interlocking method (Z-fiber, fully interlocked, or hybrid). Tensile testing was performed for this study with the enhancement of a dual camera Digital Image Correlation (DIC) system which provides the capability to measure full-field strains and three dimensional displacements of objects under load. As expected, the ratio of warp/fill fiber has a direct influence on strength and modulus, with higher values measured in the direction of higher fiber volume bias. When comparing the Z-fiber weave to a fully interlocked weave with comparable fiber bias, the Z-fiber weave demonstrated the best performance in two different comparisons. We report the measured tensile strengths and moduli for test coupons from the 6 different weave configurations under study.

Jones, Justin S.↗

Biomechanics of the Treadmill Locomotion on the International Space Station

Exercise prescriptions completed by International Space Station (ISS) crewmembers are typically based upon evidence obtained during ground-based investigations, with the assumption that the results of long-term training in weightlessness will be similar to that attained in normal gravity. Coupled with this supposition are the assumptions that exercise motions and external loading are also similar between gravitational environments. Normal control of locomotion is dependent upon learning patterns of muscular activation and requires continual monitoring of internal and external sensory input [1]. Internal sensory input includes signals that may be dependent on or independent of gravity. Bernstein hypothesized that movement strategy planning and execution must include the consideration of segmental weights and inertia [2]. Studies of arm movements in microgravity showed that individuals tend to make errors but that compensation strategies result in adaptations, suggesting that control mechanisms must include peripheral information [3-5]. To date, however, there have been no studies examining a gross motor activity such as running in weightlessness other than using microgravity analogs [6-8]. The objective of this evaluation was to collect biomechanical data from crewmembers during treadmill exercise before and during flight. The goal was to determine locomotive biomechanics similarities and differences between normal and weightless environments. The data will be used to optimize future exercise prescriptions. This project addresses the Critical Path Roadmap risks 1 (Accelerated Bone Loss and Fracture Risk) and 11 (Reduced Muscle Mass, Strength, and Endurance). Data were collected from 7 crewmembers before flight and during their ISS missions. Before launch, crewmembers performed a single data collection session at the NASA Johnson Space Center. Three-dimensional motion capture data were collected for 30 s at speeds ranging from 1.5 to 9.5 mph in 0.5 mph increments with a 12-camera system. During flight, each crewmember completed up to 6 data collection sessions spread across their missions, performing their normal exercise prescription for the test day, resulting in varying data collection protocols between sessions. Motion data were collected by a single HD video camera positioned to view the crewmembers' left side, and tape markers were placed on their feet, legs, and neck on specific landmarks. Before data collection, the crewmembers calibrated the video camera. Video data were collected during the entire exercise session at 30 Hz. Kinematic data were used to determine left leg hip, knee, and ankle range of motion and contact time, flight time, and stride time for each stride. 129 trials in weightlessness were analyzed. Mean time-normalized strides were found for each trial, and cross-correlation procedures were used to examine the strength and direction of relationships between segment movement pattern timing in each gravitational condition. Cross-correlation analyses between gravitational conditions revealed highly consistent movement patterns at each joint. Peak correlation coefficients occurred at 0% phase, indicating there were no lags in movement timing. Joint ranges of motion were similar between gravitational conditions, with some slight differences between subjects. Motion patterns in weightlessness were highly consistent at a given speed with those occurring in 1G, indicating that despite differing sensory input, subjects maintain running kinematics. The data suggest that individuals are capable of compensating for loss of limb weight when creating movement strategies. These results have important implications for creating training programs for use in weightlessness as practitioners can have greater confidence in running motions transferring across gravitational environments. Furthermore, these results have implications for use by researchers investigating motor control mechanisms and investigating hypotheses related to movement strategies when using sensory input that is dependent upon gravity.

DeWitt, John↗

Biologically-Inspired Control for a Planetary Exploration Tensegrity Robot

Tensegrity structures are becoming increasingly popular as mechanical structures for robots. Their inherent compliance makes them extremely robust to environmental disturbances, and their design allows them to have a high strength-to-weight ratio whilst being lightweight compared to traditional robots. For these reasons they would be of interest to the aerospace industry, particularly for planetary exploration. However, being such compliant structures thanks to their network of elastic elements also means that their control is not an easy task. Relying solely on traditional control strategies to generate efficient locomotion would surely be near impossible due to the complex oscillatory motions and nonlinear interactions of its members. The goal of this project was to use bio-inspired control techniques to generate locomotion for a tensegrity icosahedron, namely the SUPERball project of the Intelligent Robotics Group of NASA Ames Research Center.

Leroy, Marc↗

Dynamics retrieval from stochastically weighted incomplete data by low-pass spectral analysis

Time-resolved serial femtosecond crystallography (TR-SFX) provides access to protein dynamics on sub-picosecond timescales, and with atomic resolution. Due to the nature of the experiment, these datasets are often highly incomplete and the measured diffracted intensities are affected by partiality. To tackle these issues, one established procedure is that of splitting the data into time bins, and averaging the multiple measurements of equivalent reflections within each bin. This binning and averaging often involve a loss of information. Here, we propose an alternative approach, which we call low-pass spectral analysis (LPSA). In this method, the data are projected onto the subspace defined by a set of trigonometric functions, with frequencies up to a certain cutoff. This approach attenuates undesirable high-frequency features and facilitates retrieving the underlying dynamics. A time-lagged embedding step can be included prior to subspace projection to improve the stability of the results with respect to the parameters involved. Subsequent modal decomposition allows to produce a low-rank description of the system's evolution. Using a synthetic time-evolving model with incomplete and partial observations, we analyze the LPSA results in terms of quality of the retrieved signal, as a function of the parameters involved. We compare the performance of LPSA to that of a range of other sophisticated data analysis techniques. We show that LPSA allows to achieve excellent dynamics reconstruction at modest computational cost. Finally, we demonstrate the superiority of dynamics retrieval by LPSA compared to time binning and merging, which is, to date, the most commonly used method to extract dynamical information from TR-SFX data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diffusion and perfusion MR parameters to assess preoperative short-course radiotherapy response in locally advanced rectal cancer: a comparative explorative study among Standardized Index of Shape by DCE-MRI, intravoxel incoherent motion- and diffusion kurtosis imaging-derived parameters

Purpose: To assess preoperative short-course radiotherapy (SCR) tumor response in locally advanced rectal cancer (LARC) by means of Standardized Index of Shape (SIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters derived from diffusion-weighted MRI (DW-MRI). Materials and methods: Thirty-four patients with LARC who underwent MRI scans before and after SCR followed by delayed surgery, retrospectively, were enrolled. SIS, ADC, IVIM parameters [tissue diffusion (D{sub t}), pseudo-diffusion (D{sub p}), perfusion fraction (f{sub p})] and DKI parameters [mean diffusivity (MD), mean of diffusional kurtosis (MK)] were calculated for each patient. IVIM parameters were estimated using two methods, namely conventional biexponential fitting (CBFM) and variable projection (VARPRO). After surgery, the pathological TNM and tumor regression grade (TRG) were estimated. For each parameter, percentage changes between before and after SCR were evaluated. Furthermore, an artificial neural network was trained for outcome prediction. Nonparametric sample tests and receiver operating characteristic curve (ROC) analysis were performed. Results: Fifteen patients were classified as responders (TRG ≤ 2) and 19 as not responders (TRG > 3). Seven patients had TRG 1 (pathological complete response, pCR). Mean and standard deviation values of pre-treatment CBFM D{sub p} and mean value of VARPRO D{sub p} pre-treatment showed statistically significant differences to predict pCR. (p value at Mann–Whitney test was 0.05, 0.03 and 0.008, respectively.) Exclusively SIS percentage change showed significant differences between responder and non-responder patients after SCR (p value << 0.001) and to assess pCR after SCR (p value << 0.001). The best results to predict pCR were obtained by VARPRO Fp mean value pre-treatment with area under ROC of 0.84, a sensitivity of 96.4%, a specificity of 71.4%, a positive predictive value (PPV) of 92.9%, a negative predictive value (NPV) of 83.3% and an accuracy of 91.2%. The best results to assess after treatment complete pathological response were obtained by SIS with an area under ROC of 0.89, a sensitivity of 85.7%, a specificity of 92.6%, a PPV of 75.0%, a NPV of 96.1% and an accuracy of 91.2%. Moreover, the best results to differentiate after treatment responders vs. non-responders were obtained by SIS with an area under ROC of 0.94, a sensitivity of 93.3%, a specificity of 84.2%, a PPV of 82.4%, a NPV of 94.1% and an accuracy of 88.2%. Promising initial results were obtained using a decision tree tested with all ADC, IVIM and DKI extracted parameter: we reached high accuracy to assess pathological complete response after SCR in LARC (an accuracy of 85.3% to assess pathological complete response after SCR using VARPRO D{sub p} mean value post-treatment, ADC standard deviation value pre-treatment, MD standard deviation value post-treatment). Conclusion: SIS is a hopeful DCE-MRI angiogenic biomarker to assess preoperative treatment response after SCR with delayed surgery. Furthermore, an important prognostic role was obtained by VARPRO F{sub p} mean value pre-treatment and by a decision tree composed by diffusion parameters derived by DWI and DKI to assess pathological complete response.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S.

Seasonal influenza results in substantial annual morbidity and mortality in the United States and worldwide. Accurate forecasts of key features of influenza epidemics, such as the timing and severity of the peak incidence in a given season, can inform public health response to outbreaks. As part of ongoing efforts to incorporate data and advanced analytical methods into public health decision-making, the United States Centers for Disease Control and Prevention (CDC) has organized seasonal influenza forecasting challenges since the 2013/2014 season. In the 2017/2018 season, 22 teams participated. A subset of four teams created a research consortium called the FluSight Network in early 2017. During the 2017/2018 season they worked together to produce a collaborative multi-model ensemble that combined 21 separate component models into a single model using a machine learning technique called stacking. This approach creates a weighted average of predictive densities where the weight for each component is determined by maximizing overall ensemble accuracy over past seasons. In the 2017/2018 influenza season, one of the largest seasonal outbreaks in the last 15 years, this multi-model ensemble performed better on average than all individual component models and placed second overall in the CDC challenge. It also outperformed the baseline multi-model ensemble created by the CDC that took a simple average of all models submitted to the forecasting challenge. This project shows that collaborative efforts between research teams to develop ensemble forecasting approaches can bring measurable improvements in forecast accuracy and important reductions in the variability of performance from year to year. Efforts such as this, that emphasize real-time testing and evaluation of forecasting models and facilitate the close collaboration between public health officials and modeling researchers, are essential to improving our understanding of how best to use forecasts to improve public health response to seasonal and emerging epidemic threats.

59 BASIC BIOLOGICAL SCIENCES↗

Optimization of shallow arches against instability using sensitivity derivatives

The author discusses the problem of optimization of shallow frame structures which involve a coupling of axial and bending responses. A shallow arch of a given shape and of given weight is optimized such that its limit point load is maximized. The cross-sectional area, A(x) and the moment of inertia, I(x) of the arch obey the relationship I(x) = rho A(x) sup n, n = 1,2,3 and rho is a specified constant. Analysis of the arch for its limit point calculation involves a geometric nonlinear analysis which is performed using a corotational formulation. The optimization is carried out using a second-order projected Lagrangian algorithm and the sensitivity derivatives of the critical load parameter with respect to the areas of the finite elements of the arch are calculated using implicit differentation. Results are presented for an arch of a specified rise to span ratio under two different loadings and the limitations of the approach for the intermediate rise arches are addressed.

Kamat, Manohar P.↗

Manufacture and evaluation of Li/BCX DD cells

This project is divided into four main tasks: cell manufacture, acceptance, and lot certification of cells, performance testing of cells, and abuse testing of cells. Lithium/bromine chloride in thionyl chloride (Li/BCX) 149 DD cells (PN 3B2085-XA) were built according to the provisions of Electrochem Industries Quality Plan 17096. Acceptance and lot certification testing was performed according to NASA JSC Document EP5-83-025, Revision B. Acceptance testing included open circuit and load voltage check, visual examination, size and weight measurements, and high temperature exposure. Lot certification tests were performed for capacity performance and for performance under conditions of thermal and electrical abuse. These tests included 149 C exposure, capacity discharge, fuse check, high temperature exposure, high rate discharge, short circuit, vibration, and overdischarge testing. A quantity of 200 cells was delivered to Johnson Space Center for life test evaluation. A parametric evaluation of the capacity discharge of Li/BCX DD cells was performed over a variety of temperatures and discharge rates. This testing served to map the performance capability of the cell. Tests were also performed over a variety of electrical and thermal abuse conditions. Abuse tests included short circuit, charging, overdischarge, high temperature exposure, shock, and vibration.

Meyer, S.↗