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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.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Computer simulation of the effect of dDAVP with saline loading on fluid balance after 24-hour head-down tilt

Fluid loading (FL) before Shuttle reentry is a countermeasure currently in use by NASA to improve the orthostatic tolerance of astronauts during reentry and postflight. The fluid load consists of water and salt tablets equivalent to 32 oz (946 ml) of isotonic saline. However, the effectiveness of this countermeasure has been observed to decrease with the duration of spaceflight. The countermeasure's effectiveness may be improved by enhancing fluid retention using analogs of vasopressin such as lypressin (LVP) and desmopressin (dDAVP). In a computer simulation study reported previously, we attempted to assess the improvement in fluid retention obtained by the use of LVP administered before FL. The present study is concerned with the use of dDAVP. In a recent 24-hour, 6 degree head-down tilt (HDT) study involving seven men, dDAVP was found to improve orthostatic tolerance as assessed by both lower body negative pressure (LBNP) and stand tests. The treatment restored Luft's cumulative stress index (cumulative product of magnitude and duration of LBNP) to nearly pre-bedrest level. The heart rate was lower and stroke volume was marginally higher at the same LBNP levels with administration of dDAVP compared to placebo. Lower heart rates were also observed with dDAVP during stand test, despite the lower level of cardiovascular stress. These improvements were seen with only a small but significant increase in plasma volume of approximately 3 percent. This paper presents a computer simulation analysis of some of the results of this HDT study.

NASA Discipline Cardiopulmonary↗
DOE OSTI2022

Hot-melt extrudability of amorphous solid dispersions of flubendazole-copovidone: An exploratory study of the effect of drug loading and the balance of adjuvants on extrudability and dissolution

The FDA-approved anthelmintic flubendazole has shown potential to be repositioned to treat cancer and dry macular degeneration; however, its poor water solubility limits its use. Amorphous solid dispersions may overcome this challenge, but the balance of excipients may impact the preparation method and drug release. Here, we evaluate the influence of adjuvants and drug loading on the development of an amorphous solid dispersion of flubendazole-copovidone by hot-melt extrusion. The drug, copovidone, and adjuvants (magnesium stearate and hydroxypropyl cellulose) mixtures were statistically designed, and the process was performed in a twin-screw extruder. The study showed that flubendazole and copovidone mixtures were highly extrudable, except when drug loading was high (>40%). Furthermore, magnesium stearate positively impacted the extrusion and was more effective than hydroxypropyl cellulose. The extruded materials were evaluated by modulated differential scanning calorimetry and X-ray powder diffraction, obtaining positive amorphization and physical stability results. Pair distribution function analysis indicated the presence of drug rich domains with medium-range order structure and no evidence of polymer-drug interaction. All extrudates presented faster dissolution (HCl, pH 1.2) than pure flubendazole, and both adjuvants had a notable influence on the dissolution rate. In conclusion, hot-melt extrusion may be a viable option to obtain stable flubendazole: copovidone amorphous dispersions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

The effect of dDAVP with saline loading on fluid balance during LBNP and standing after 24-hr head-down bedrest

Shuttle astronauts currently drink approximately a quart of water with eight salt tablets before reentry to restore lost body fluid and thereby reduce the likelihood of cardiovascular instability and syncope during reentry and after landing. However, the saline loading countermeasure is not entirely effective in restoring orthostatic tolerance to preflight levels. We tested the hypothesis that the effectiveness of this countermeasure could be improved with the use of a vasopressin analog, 1-deamino-8-D-arginine vasopressin (dDAVP). The rationale for this approach is that reducing urine formation with exogenous vasopressin should increase the magnitude and duration of the vascular volume expansion produced by the saline load, and in so doing improve orthostatic tolerance during reentry and postflight.

NASA Discipline Number 14-10↗
NASA NTRS2013

A Baseline Load Schedule for the Manual Calibration of a Force Balance

A baseline load schedule for the manual calibration of a force balance is defined that takes current capabilities at the NASA Ames Balance Calibration Laboratory into account. The chosen load schedule consists of 18 load series with a total of 194 data points. It was designed to satisfy six requirements: (i) positive and negative loadings should be applied for each load component; (ii) at least three loadings should be applied between 0 % and 100 % load capacity; (iii) normal and side force loadings should be applied at the forward gage location, aft gage location, and the balance moment center; (iv) the balance should be used in "up" and "down" orientation to get positive and negative axial force loadings; (v) the constant normal and side force approaches should be used to get the rolling moment loadings; (vi) rolling moment loadings should be obtained for 0, 90, 180, and 270 degrees balance orientation. In addition, three different approaches are discussed in the paper that may be used to independently estimate the natural zeros, i.e., the gage outputs of the absolute load datum of the balance. These three approaches provide gage output differences that can be used to estimate the weight of both the metric and non-metric part of the balance. Data from the calibration of a six-component force balance will be used in the final manuscript of the paper to illustrate characteristics of the proposed baseline load schedule.

Ulbrich, N.↗
NASA NTRS2013

A Baseline Load Schedule for the Manual Calibration of a Force Balance

A baseline load schedule for the manual calibration of a force balance was developed that takes current capabilities at the NASA Ames Balance Calibration Laboratory into account. The load schedule consists of 18 load series with a total of 194 data points. It was designed to satisfy six requirements: (i) positive and negative loadings should be applied for each load component; (ii) at least three loadings should be applied between 0 % and 100 % load capacity; (iii) normal and side force loadings should be applied at the forward gage location, the aft gage location, and the balance moment center; (iv) the balance should be used in UP and DOWN orientation to get axial force loadings; (v) the constant normal and side force approaches should be used to get the rolling moment loadings; (vi) rolling moment loadings should be obtained for 0, 90, 180, and 270 degrees balance orientation. Three different approaches are also reviewed that may be used to independently estimate the natural zeros of the balance. These three approaches provide gage output differences that may be used to estimate the weight of both the metric and non-metric part of the balance. Manual calibration data of NASA s MK29A balance and machine calibration data of NASA s MC60D balance are used to illustrate and evaluate different aspects of the proposed baseline load schedule design.

Ulbrich, N.↗
NASA NTRS1998

Method and Apparatus for Coupling Space Vehicles

A first space vehicle is attached with a second space vehicle which includes a rocket propulsion nozzle having a combustion chamber upstream from the nozzle throat. Apparatus 10 includes an elongate grappling arm 12 extending from the first space vehicle, a pair of inflatable bladders 16, 18 positioned about the grappling arm for engaging an inner surface of the combustion chamber upon inflation. and a pair of rear bladders 20, 22 positioned about the grappling arm for engaging an inner surface of the nozzle downstream from the combustion chamber upon inflation for aligning the grappling arm and the rocket propulsion nozzle. A pressurized fluid source 24 is provided on the first space vehicle for supplying fluid pressure to the inflatable bladders. and a fluid control valve manifold 30 selectively controls the release of pressurized fluid to the bladders. According to the method of the invention. the grappling arm is inserted into the rocket propulsion nozzle. and the control valves are actuated to first inflate the front bladders and thereby interconnect the grappling arm and the rocket propulsion nozzle. The rear bladders are subsequently inflated to align a central axis of the grappling arm with a central axis of the rocket propulsion nozzle. Inflation of the rear bladders provides an axial reaction load to balance the axial load provided by the front bladders. Attaching the vehicles in space may be controlled from the earth by activating the control valves to inflate the bladders. The cost of attaching space vehicles is significantly reduced by attaching a grappling arm on one vehicle with the existing rocket propulsion nozzle of another vehicle.

Schneider, William C.↗
NASA NTRSDate not supplied

Comparison of Two Load Prediction Methods for Strain-Gage Balances

Data from a high-capacity semi-span balance is used to perform a detailed comparison of the load prediction accuracy of two strain-gage balance load prediction methods. Both methods independently obtain their load prediction equations from multivariate least squares fits of balance calibration data. The first method is called Non-Iterative Method. This approach directly uses regression models of the individual load components of a balance for the load prediction. The second method is called Iterative Method. This alternate approach uses a load iteration equation for the load prediction that is constructed from the regression models of the gage outputs of the balance. Basic characteristics of the two methods are reviewed. Afterwards, both methods are applied to calibration and check load data of the chosen balance. Finally, selected analysis results are compared. These comparisons confirmed that the load prediction accuracy of the two methods is the same for all practical purposes.

wind tunnel test↗
NASA NTRS1991

Dual strain gage balance system for measuring light loads

A dual strain gage balance system for measuring normal and axial forces and pitching moment of a metric airfoil model imparted by aerodynamic loads applied to the airfoil model during wind tunnel testing includes a pair of non-metric panels being rigidly connected to and extending towards each other from opposite sides of the wind tunnel, and a pair of strain gage balances, each connected to one of the non-metric panels and to one of the opposite ends of the metric airfoil model for mounting the metric airfoil model between the pair of non-metric panels. Each strain gage balance has a first measuring section for mounting a first strain gage bridge for measuring normal force and pitching moment and a second measuring section for mounting a second strain gage bridge for measuring axial force.

Roberts, Paul W.↗
NASA NTRS1989

Development of a dual strain gage balance system for measuring light loads

A strain-gage-balance (SGB) force-measurement system is described which was designed to meet light-load requirements for an airfoil model tested in the NASA Langley low-turbulence pressure tunnel (LTPT). This system was developed to obtain direct force data needed to verify calculated pressure/force correlations used in previous aerodynamic tests. The three-component force-measurement system was designed so that the SGBs would simultaneously support and measure the following loads: weight of the airfoil (approximately 3.0 lbf); 8.0 lbf of lift; 0.5 lbf of drag; and 16.0 in. lbf of pitching moment. In addition to these design loads, the system was required to withstand 100-percent overload on all three components. The system comprises an airfoil, two SGBs, a thermal flexure, and a mounting plate. The installation of the system in the LTPT is also discussed.

Roberts, Paul W.↗
DOE OSTI2022

An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids

An MILP-based distributed energy management for the coordination of networked microgrids is proposed in this paper. Multiple microgrids and the utility grid are coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) update their schedules separately. Then, the price signals are updated according to the generation–load mismatch and distributed to MCs and DMS for the next iteration. The iteration continues until the generation–load mismatch is small enough, i.e., the generation and load are balanced under agreed price signals. Through the proposed distributed energy management, various microgrids and the utility grid with different economic, resilient, emission and socio-economic objectives are coordinated with generation–load balance guaranteed and the microgrid customers’ privacy preserved. In particular, a piecewise linearization technique is employed to approximate the augmented Lagrange term in the alternating direction method of multipliers (ADMM) algorithm. Thus, the subproblems are transformed into mixed integer linear programming (MILP) problems and efficiently solved by open-source MILP solvers, which would accelerate the adoption and deployment of microgrids and promote clean energy. The proposed MILP-based distributed energy management is demonstrated through various case studies on a networked microgrids test system with three microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2024

Evaluation, Analysis, and Application of Internal Strain-Gage Balance Data

Experimental processes, analytical methods, and numerical algorithms are described that may be used to predict the forces and moments of an internal strain–gage balance during a wind tunnel test. First, the control volume model of a strain–gage balance and the concepts of load state, load space, and output space are introduced. These important abstractions provide a better understanding of fundamental characteristics of different balance load prediction approaches. Then, the description of strain–gage balance data and the definition of the primary bridge sensitivity are discussed. Afterwards, basic elements of the calibration of a typical six–component balance are reviewed. Two fundamentally different balance load prediction methods, the processing of check loads, and related topics are also discussed. Three real–world balance data examples are reviewed in great detail to illustrate typical analysis results for a variety of strain–gage balance designs. Finally, important observations are summarized and recommendations are provided. – Additional information and detailed mathematical derivations can be found in the appendices of the document. They include the following topics: balance terminology, definitions of important statistical metrics, balance axis system conventions, balance load transformations, the combined load diagram, electrical output format options, bi–directional output characteristics, determination of the natural zeros, derivation of two balance load prediction methods, description of two tare load iteration algorithms, modeling of balance temperature effects, basics of three–component moment balances, definition of the percent contribution, detection of linear and near–linear dependencies in balance calibration data, a regression model search algorithm, balance interactions, and other related information.

strain-gage balance↗
NASA NTRS1955

Flight Measurements of Horizontal-Tail Loads on the Bell X-5 Research Airplane at a Sweep Angle of 58.7 Deg

A flight investigation was made at altitudes of 40,000, 25,000 and 15,000 feet to determine the horizontal-tail loads of the Bell X-5 research airplane at a sweep angle of 58.7 deg over the lift range of the airplane for Mach numbers from 0.61 to 1.00. The horizontal-tail loads were found to be nonlinear with lift throughout the lift ranges tested at all Mach numbers except at a Mach number of 1.00. The balancing tail loads reflected the changes which occur in the wing characteristics with increasing angle of attack. The nonlinearities were, in general, more pronounced at the higher angles of attack near the pitch-up where the balancing tail loads indicate that the wing-fuselage combination becomes unstable. No apparent effects of altitude on the balancing tail loads were evident over the comparable lift ranges of these tests at altitudes from 40,000 feet to 15,000 feet. Comparisons of balancing tail loads obtained from flight and windtunnel tests indicated discrepancies in absolute magnitudes, but the general trends of the data agree. Some differences in absolute magnitude may be accounted for by the tail load carried inboard of the strain-gage station and the load induced on the fuselage by the presence of the tail. These loads were not measured in flight.

Reed, Robert D↗
NASA NTRS2021

Evaluation, Analysis, and Application of Internal Strain-Gage Balance Data

Experimental processes, analytical methods, and numerical algorithms are described that may be used to predict the forces and moments of an internal strain-gage balance during a wind tunnel test. First, the control volume model of a strain-gage balance and the concepts of load state, load space, and output space are introduced. These important abstractions provide a better understanding of fundamental characteristics of different balance load prediction approaches. Then, the description of strain-gage balance data and the definition of the primary gage sensitivity is discussed. Afterwards, basic elements of the calibration of a typical six-component balance are reviewed. Two fundamentally different balance load prediction methods, the processing of check loads, and related topics are also discussed. Three real-world balance data examples are reviewed in great detail to illustrate typical analysis results for a variety of strain-gage balance designs. Finally, important observations are summarized and recommendations are provided. Additional information and detailed mathematical derivations can be found in the appendices of the document. They include the following topics: balance terminology, definitions of important statistical metrics, balance axis system conventions, balance load transformations, the combined load diagram, electrical output format options, bi-directional gage output characteristics, determination of the natural zeros, derivation of two balance load prediction methods, description of two tare load iteration algorithms, modeling of balance temperature effects, basics of three-component moment balances, definition of the percent contribution, detection of linear and near-linear dependencies in balance calibration data, a regression model term selection algorithm, and other related topics.

wind tunnel test↗
NASA NTRSDate not supplied

Application of the Concepts of Load State, Load Space, and Output Space to Strain-Gage Balances

The concepts of load state, load space, and output space are used to describe elements of the development of a load prediction process for a six–component strain–gage balance. The use of these terms adds clarity during the selection of the independent and dependent variables for the development of the load prediction process. First, the control volume model of a strain–gage balance is reviewed as it helps better understand the role of loads, outputs, and state variables during the load prediction. Then, the description of the absolute load datum in both the load space and the output space is discussed. It is concluded that the use of the difference between a raw output and the natural zero of a balance gage has a key advantage for the definition of the output space. In that case, the origin of the output space will also describe the absolute load datum of the balance. Finally, details of the application of the concepts of load state, load space, and output space to two commonly used balance load prediction methods are discussed.

strain-gage balance↗
NASA NTRS1989

SSME alternate turbopump (pump section) axial load analysis

A flow balancing computer program constructed to calculate the axial loads on the Space Shuttle Main Engine (SSME) alternate turbopumps (ATs) pump sections are described. The loads are used in turn to determine load balancing piston design requirements. The application of the program to the inlet section, inducer/impeller/stage, bearings, seals, labyrinth, damper, piston, face and corner, and stationary/rotating surfaces is indicated. Design analysis results are reported which show that the balancing piston's designs are adequate and that performance and life will not be degraded by the turbopump's axial load characteristics.

Crease, G. A.↗
NASA NTRS1964

Self-balancing beam permits safe, easy load handling under overhang

The use of a self-balancing I-beam with a counterweight and motor simplifies moving heavy loads that are inaccessible for cranes. The beam cannot be overloaded, as the counterweight will not balance the load, and thus acts as an automatic safety device.

Edwards, O. H.↗
NASA NTRS2009

Analysis of Sting Balance Calibration Data Using Optimized Regression Models

Calibration data of a wind tunnel sting balance was processed using a search algorithm that identifies an optimized regression model for the data analysis. The selected sting balance had two moment gages that were mounted forward and aft of the balance moment center. The difference and the sum of the two gage outputs were fitted in the least squares sense using the normal force and the pitching moment at the balance moment center as independent variables. The regression model search algorithm predicted that the difference of the gage outputs should be modeled using the intercept and the normal force. The sum of the two gage outputs, on the other hand, should be modeled using the intercept, the pitching moment, and the square of the pitching moment. Equations of the deflection of a cantilever beam are used to show that the search algorithm s two recommended math models can also be obtained after performing a rigorous theoretical analysis of the deflection of the sting balance under load. The analysis of the sting balance calibration data set is a rare example of a situation when regression models of balance calibration data can directly be derived from first principles of physics and engineering. In addition, it is interesting to see that the search algorithm recommended the same regression models for the data analysis using only a set of statistical quality metrics.

Ulbrich, Norbert↗
NASA NTRS1989

Monitoring dynamic loads on wind tunnel force balances

Two devices have been developed at NASA Langley to monitor the dynamic loads incurred during wind-tunnel testing. The Balance Dynamic Display Unit (BDDU), displays and monitors the combined static and dynamic forces and moments in the orthogonal axes. The Balance Critical Point Analyzer scales and sums each normalized signal from the BDDU to obtain combined dynamic and static signals that represent the dynamic loads at predefined high-stress points. The display of each instrument is a multiplex of six analog signals in a way that each channel is displayed sequentially as one-sixth of the horizontal axis on a single oscilloscope trace. Thus this display format permits the operator to quickly and easily monitor the combined static and dynamic level of up to six channels at the same time.

Ferris, Alice T.↗