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At least 1,549 records · Page 86

Prediction of SA 349/2 GV blade loads in high speed flight using several rotor analyses

The influence of blade dynamics, dynamic stall, and transonic aerodynamics on the predictions of rotor loads in high-speed flight are presented. Data were obtained from an Aerospatiale Gazelle SA 349/2 helicopter with three Grande Vitesse blades. Several analyses are used for this investigation. First, blade dynamics effects on the correlation are studied using three rotor analyses which differ mainly in the method of calculating the blade elastic response. Next, an ONERA dynamic stall model is used to predict retreating blade stall. Finally, advancing blade aerodynamic loads are calculated using a NASA-developed rotorcraft analysis coupled with two transonic finite-difference analyses.

Gaubert, Michel↗

Wake-Induced Aerodynamics on a Trailing Aircraft

NASA conducted flight tests to measure the exhaust products from alternative fuels using a DC-8 transport aircraft and a Falcon business jet. An independent analysis of the maximum vortex-induced loads on the Falcon in the DC-8 wake was conducted for pre-flight safety analysis and to define safe trail distances for the flight tests. Static and dynamic vortex-induced aerodynamic loads on the Falcon were predicted at a matrix of locations aft of the DC-8 under flight-test conditions, and the maximum loads were compared with design limit loads to assess aircraft safety. Trajectory simulations for the Falcon during close encounters with the DC-8 wake were made to study the vortex-induced loads during traverses of the DC-8 primary trailing vortex. A parametric study of flight traverses through the trailing vortex was conducted to assess Falcon flight behavior and motion characteristics.

Mendenhall, Michael R.↗

Fracture mechanics; Proceedings of the Seventeenth National Symposium, Albany, NY, August 7-9, 1984

The present conference gives attention to topics in the application of fracture mechanics, subcritical crack growth phenomena, fracture testing methods, ductile fracture behavior, and fracture mechanisms and their analysis. Specific papers treat the resistance curve approach to composite materials characterization, fracture toughness in ductile iron and cast steel, hold-time effects in elevated temperature fatigue crack propagation, creep crack growth under nonsteady conditions, viscoplastic fatigue in a superalloy at elevated temperatures, fracture testing with arc bend specimens, one-point bend impact test application, and a compact mode II fracture specimen. Also discussed are the computation of stable crack growth using the J-integral, the use of plastic energy dissipation to characterize crack growth, the extension of surface cracks under cyclic loading, the minimum time criterion for crack instability in structural materials, dynamic crack propagation and branching under biaxial loading, and boundary layer effects in cracked bodies.

Underwood, J. M.↗

Gilgamesh: A Multithreaded Processor-In-Memory Architecture for Petaflops Computing

Processor-in-Memory (PIM) architectures avoid the von Neumann bottleneck in conventional machines by integrating high-density DRAM and CMOS logic on the same chip. Parallel systems based on this new technology are expected to provide higher scalability, adaptability, robustness, fault tolerance and lower power consumption than current MPPs or commodity clusters. In this paper we describe the design of Gilgamesh, a PIM-based massively parallel architecture, and elements of its execution model. Gilgamesh extends existing PIM capabilities by incorporating advanced mechanisms for virtualizing tasks and data and providing adaptive resource management for load balancing and latency tolerance. The Gilgamesh execution model is based on macroservers, a middleware layer which supports object-based runtime management of data and threads allowing explicit and dynamic control of locality and load balancing. The paper concludes with a discussion of related research activities and an outlook to future work.

management locality load balance↗

Dynamic Regulation of Sub-Atmospheric Pressure for Constant and Cyclic Gas Loads During Testing of Spacesuit Components

New iterations of the various subsystems within the spacesuit will benefit from a new sorbent technology. For example, sorbents used in the Trace Contaminant Control (TCC) and the Rapid Cycle Amine (RCA) systems within the Exploration Portable Life Support System (xPLSS), part of the Extra-Vehicular Mobility Unit (xEMU). For proper validation, the sub-atmospheric pressure needs to be maintained within a simulated 2 ft 3 spacesuit volume. The traditional approach, which involves placing the entire vent loop within a hypobaric chamber, is not practical for the widespread testing of components and prototypes, as these specialized chambers are costly and not widely available. A two-stage regulator based sub-atmospheric pressure system is presented in this work. The method regulates the pressure based on pressure differentials between the pressure regulation pump, the test system, and the ambient environment. The performance of this system is demonstrated using data collected during a 150+ hour non-regenerative TCC sorbent evaluation, several 24-hour regenerative TCC sorbent evaluations with different regeneration cycles, and an 8-hour RCA sorbent evaluation, all under xEMU operating conditions. For regulation, the inlet regulator was set to propagate a small leak to increase the stability of the system as the gas load from the testing system changes. It was also found that controlling the input flow rate that replaces the material lost during regeneration is critical for ensuring the stability of the system. This system provided excellent pressure regulation, without adjustments, for constant loads during shorter time evaluations (hours), while longer time evaluations (days) are easily obtainable with periodic regulator adjustments. A second method is under development to address longer-term stability and to automate pressure regulation. It will incorporate flow and pressure measurements to dynamically control a set of electronically controlled proportional valves for adjusting the pumping speed and air bleed supply.

Nicholas F Materer↗

Failure behavior of generic metallic and composite aircraft structural components under crash loads

Failure behavior results are presented from crash dynamics research using concepts of aircraft elements and substructure not necessarily designed or optimized for energy absorption or crash loading considerations. To achieve desired new designs incorporating improved energy absorption capabilities often requires an understanding of how more conventional designs behave under crash loadings. Experimental and analytical data are presented which indicate some general trends in the failure behavior of a class of composite structures including individual fuselage frames, skeleton subfloors with stringers and floor beams without skin covering, and subfloors with skin added to the frame-stringer arrangement. Although the behavior is complex, a strong similarity in the static/dynamic failure behavior among these structures is illustrated through photographs of the experimental results and through analytical data of generic composite structural models.

Carden, Huey D.↗

Damage Instability and Transition From Quasi-Static to Dynamic Fracture

In a typical mechanical test, the loading phase is intended to be a quasi-static process, while the failure and collapse is usually a dynamic event. The structural strength and modes of damage can seldom be predicted without accounting for these two aspects of the response. For a proper prediction, it is therefore essential to use tools and methodologies that are capable of addressing both aspects of responses. In some cases, implicit quasi-static models have been shown to be able to predict the entire response of a structure, including the unstable path that leads to fracture. However, is it acceptable to ignore the effect of inertial forces in the formation of damage? In this presentation we examine aspects of the damage processes that must be simulated for an accurate prediction of structural strength and modes of failure.

Davila, Carlos G.↗

Modeling and Detection of Future Cyber-Enabled DSM Data Attacks

Demand-Side Management (DSM) is an essential tool to ensure power system reliability and stability. In future smart grids, certain portions of a customer’s load usage could be under the automatic control of a cyber-enabled DSM program, which selectively schedules loads as a function of electricity prices to improve power balance and grid stability. In this scenario, the security of DSM cyberinfrastructure will be critical as advanced metering infrastructure and communication systems are susceptible to cyber-attacks. Such attacks, in the form of false data injections, can manipulate customer load profiles and cause metering chaos and energy losses in the grid. The feedback mechanism between load management on the consumer side and dynamic price schemes employed by independent system operators can further exacerbate attacks. To study how this feedback mechanism may worsen attacks in future cyber-enabled DSM programs, we propose a novel mathematical framework for (i) modeling the nonlinear relationship between load management and real-time pricing, (ii) simulating residential load data and prices, (iii) creating cyber-attacks, and (iv) detecting said attacks. In this framework, we first develop time-series forecasts to model load demand and use them as inputs to an elasticity model for the price-demand relationship in the DSM loop. This work then investigates the behavior of such a feedback loop under intentional cyber-attacks. We simulate and examine load-price data under different DSM-participation levels with three types of random additive attacks: ramp, sudden, and point attacks. We conduct two investigations for the detection of DSM attacks. The first studies a supervised learning approach, with various classification models, and the second studies the performance of parametric and nonparametric change point detectors. Results conclude that higher amounts of DSM participation can exacerbate ramp and sudden attacks leading to better detection of such attacks, especially with supervised learning classifiers. We also find that nonparametric detection outperforms parametric for smaller user pools, and random point attacks are the hardest to detect with any method.

97 MATHEMATICS AND COMPUTING↗

Mass Mitigation in Structural Designs Via Dynamic Properties

Mass Mitigation in Structural Designs Via Dynamic Properties The reported efforts are focused on mitigating unnecessary mass in aerospace hardware via leveraging dynamic strength of materials and the frequency dependency of strain. Analytically predicted dynamic responses of structures are often applied as static loads in stress analyses that ultimately dictate the weight of a structural design. Assuming a dynamic response is a static load and then comparing resulting stress predictions to a static strength property is a long-standing engineering practice. Doing so is known to be, or is assumed to be, conservative. However, little indication of the order of magnitude of embedded conservatism has been identified. NASA/MSFC efforts in 2011, 2019, 2020, and now in 2021 have begun to qualitatively show the order of magnitude of that conservatism. A quick turnaround engineering method is pursued to leverage the subject facets of physics for the purpose of decreasing the weight of flight hardware. Tests performed using simple beams and significant observations are described.

mass mitigation↗

Peak load reduction and load shaping in HVAC and refrigeration systems in commercial buildings by using a novel lightweight dynamic priority-based control strategy

Reducing peak power demand in a building can reduce electricity expenses for the building owner and contribute to the efficiency and reliability of the electrical power grid. For the building owner, reduced expenses come from the reduction or elimination of peak power charges on electricity bills. For the power system operator, reducing peak power demand leads to a more predictable load profile and reduces stress on the electric grid system. Herein we present a computationally inexpensive, dynamic, and retrofit-deployable control strategy to effect peak load reduction and load shaping. The effectiveness of the control strategy is examined in a simulation with 80 air-conditioning units and 40 refrigeration units. The results show that a peak demand reduction of 60 kW can be achieved relative to peak demand in a typical set point–based approach. The proposed strategy was deployed in a gymnasium building with four rooftop HVAC units, where it showed over 15% peak demand (kW) reduction savings while maintaining or lowering energy consumption (in kilowatt-hours) relative to the set point–based thermostat controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Urban Air Mobility Airspace Dynamic Density

Effective flight planning requires information about a variety of potential threats, such as adverse weather or airspace restrictions, and about alternatives available if unforeseen events occur. Expected traffic along the route of flight is also essential to a safe outcome so that, for example, adequate fuel/energy supply can be loaded prior to flight. A dynamic density (DD) metric is introduced for the emerging urban air mobility (UAM) concept to predict airspace congestion that may lead to loss of separation between aircraft or less efficient operations. Using inspiration from dynamic density metric research for traditional air traffic management and a two-way highway analogy, we develop a dynamic density metric for a portion of airspace (aUAM corridor) that aggregates the impact from five factors: aircraft density, density of populous clusters, mean number of aircraft in populous clusters, mean distance between aircraft, and minimum distance between aircraft. This works describes our methodology, rationale, use cases, and visualization techniques to efficiently present the DD metric to an operator for informed decision making. We also present an approach for validating the metric. However, validation remains part of future work.

UAM↗

On the use of dynamic models for studying launch vehicle buffet and ground-wind loads

The complex nature of the random aerodynamic input forces associated with transonic buffet and ground winds leads to difficulty in analytical treatment of the response of launch vehicles to these important loading conditions. The application of aeroelastically scaled models in the wind tunnel as a mechanical analog of the matharnatically complex problem requiring solution is described. Scaling relationships involved in this approach are developed and some checks on their validity are presented. Model design and support techniques are discussed, and some typical results given. Some problems arising from the increased size of launch vehicles are discussed.

Perry W. Hanson↗

Predicting lake surface water phosphorus dynamics using process-guided machine learning

Phosphorus (P) loading to lakes is degrading the quality and usability of water globally. Accurate predictions of lake P dynamics are needed to understand whole-ecosystem P budgets, as well as the consequences of changing lake P concentrations for water quality. However, complex biophysical processes within lakes, along with limited observational data, challenge our capacity to reproduce short-term lake dynamics needed for water quality predictions, as well as long-term dynamics needed to understand broad scale controls over lake P. Here we use an emerging paradigm in modeling, process-guided machine learning (PGML), to produce a phosphorus budget for Lake Mendota (Wisconsin, USA) and to accurately predict epilimnetic phosphorus over a time range of days to decades. In our implementation of PGML, which we term a Process-Guided Recurrent Neural Network (PGRNN), we combine a process-based model for lake P with a recurrent neural network, and then constrain the predictions with ecological principles. We test independently the process-based model, the recurrent neural network, and the PGRNN to evaluate the overall approach. The process-based model accounted for most of the observed pattern in lake P; however it missed the long-term trend in lake P and had the worst performance in predicting winter and summer P in surface waters. The root mean square error (RMSE) for the process-based model, the recurrent neural network, and the PGRNN was 33.0 μg P L -1 , 22.7 μg P L -1 , and 20.7 μg P L -1 , respectively. All models performed better during summer, with RMSE values for the three models (same order) equal to 14.3 μg P L -1 , 10.9 μg P L -1 , and 10.7 μg P L -1 . Although the PGRNN had only marginally better RMSE during summer, it had lower bias and reproduced long-term decreases in lake P missed by the other two models. For all seasons and all years, the recurrent neural network had better predictions than process alone, with root mean square error (RMSE) of 23.8 μg P L -1 and 28.0 μg P L -1 , respectively. The output of PGRNN indicated that new processes related to water temperature, thermal stratification, and long term changes in external loads are needed to improve the process model. By using ecological knowledge, as well as the information content of complex data, PGML shows promise as a technique for accurate prediction in messy, real-world ecological dynamics, while providing valuable information that can improve our understanding of process.

54 ENVIRONMENTAL SCIENCES↗

Impedance Based Fixture Neutralization (FINE) Method to Replicate Field Environments in Laboratory Settings

Test article vibration test responses will vary from one test laboratory to another due to differences in shaker and fixture dynamic characteristics. This is also seen between the field and laboratory due to the differing dynamic characteristics between field assembly loading and boundary conditions compared to the laboratory configuration. This work introduces a technique called Impedance Fixture Neutralization which customizes input forces to cause consistent responses for the Device Under Test across different vibration testing conditions. The customized force neutralizes the dynamic variations between configurations for the Device Under Test. The device responses can be replicated in several situations: when using a different fixture with the same attachment points, when the test article mounting location on the fixture changes, when the force location changes, or any combination of these situations. Impedance Fixture Neutralization uses the uncoupled dynamic characteristics of the test article and excitation fixtures to customize the input thereby causing the same test article responses between two mounting configurations (either field to laboratory or two different laboratory configurations). The application of the technique is shown using an analytical model of a two-beam system and analytically using experimental FRFs from plate and frame component hardware characterization tests. In both cases a device under test is attached to two test fixtures wherein the dynamic differences in the configurations are neutralized.

Laboratory↗

Simulation-based assessment on stochastic load scheduling for building cooling systems

Here, to fill knowledge gaps related to stochastic load scheduling, we performed a comprehensive evaluation of the stochastic load scheduling for building cooling systems. Specifically, we studied the common uncertain variables in the load scheduling process for building cooling systems and categorized those variables based on their dynamic patterns. We then developed a generic stochastic load scheduling framework and applied it to building cooling systems that served a simulated community. This community consists of 100 heterogeneous houses and serves as a virtual testbed for evaluating the performance of stochastic load scheduling. In this evaluation, we considered representatives of uncertain variables with different dynamic patterns and included 100 realizations of the considered uncertainty in the evaluation to better catch the probability distribution of the control performance. The evaluation results suggest that deterministic load scheduling can reduce the operating energy cost by 18% but its performance can be affected by uncertainty. Stochastic load scheduling can further decrease the operating energy cost under uncertainty compared to deterministic load scheduling. We also found that the effectiveness of stochastic load scheduling in handling uncertainty is not directly associated with the number of uncertainty scenarios that are considered in its formulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Loading, electromyograph, and motion during exercise

A system is being developed to gather kineto-dynamic data for a study to determine the load vectors applied to bone during exercise on equipment similar to that used in space. This information will quantify bone loading for exercise countermeasures development. Decreased muscle loading and external loading of bone during weightlessness results in cancellous bone loss of 1 percent per month in the lower extremities and 2 percent per month in the calcaneous. It is hypothesized that loading bone appropriately during exercise may prevent the bone loss. The system consists of an ergometer instrumented to provide position of the pedal (foot), pedaling forces on the foot (on the sagittal plane), and force on the seat. Accelerometers attached to the limbs will provide acceleration. These data will be used as input to an analytical model of the limb to determine forces on the bones and on groups of muscles. EMG signals from activity in the muscles will also be used in conjunction with the equations of mechanics of motion to be able to discern forces exerted by specific muscles. The tasks to be carried out include: design of various mechanical components to mount transducers, specification of mechanical components, specification of position transducers, development of a scheme to control the data acquisition instruments (TEAC recorder and optical encoder board), development of a dynamic model of the limbs in motion, and development of an overall scheme for data collection analysis and presentation. At the present time, all the hardware components of the system are operational, except for a computer board to gather position data from the pedals and crank. This board, however, may be put to use by anyone with background in computer based instrumentation. The software components are not all done. Software to transfer data recorded from the EMG measurements is operational, software to drive the optical encoder card is mostly done. The equations to model the kinematics and dynamics of motion of the limbs have been developed, but they have not yet been implemented in software. Aside from the development of the hardware and software components of the system, the methodology to use accelerometers and encoders and the formulation of the appropriate equations are an important contribution to the area of biomechanics, particularly in space applications.

Figueroa, Fernando↗