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The Mars Pathfinder mission, scheduled for launch in December, 1996, will use an airbag system to safely deliver a lander to the Martian surface. The airbag landing system has undergone a comprehensive test program during its evolution from initial design phase to final qualification and acceptance testing.
The increasing scale and complexity of scientific applications are rapidly transforming the ecosystem of tools, methods, and workflows adopted by the high-performance computing (HPC) community. Big data analytics and deep learning are gaining traction as essential components in this ecosystem in a variety of scenarios, such as, steering of experimental instruments , acceleration of high-fidelity simulations through surrogate computations, and guided ensemble searches. In this context, the batch job model traditionally adopted by the supercomputing in-frastructures needs to be complemented with support to schedule opportunistic on-demand analytics jobs, leading to the problem of efficient preemption of batch jobs with minimum loss of progress. In this paper, we design and implement a simulator, CoSim, that enables on-the-fly analysis of the trade-offs arising between delaying the start of opportunistic on-demand jobs, which leads to longer analytics latency, and loss of progress due to preemption of batch jobs, which is necessary to make room for on-demand jobs. To this end, we propose an algorithm based on dynamic programming with predictable performance and scalability that enables supercomputing infrastructure schedulers to analyze the aforementioned trade-off and take decisions in near real-time. Compared with other state-of-art approaches using traces of the Theta pre-Exascale machine, our approach is capable of finding the optimal solution, while achieving high performance and scalability.
A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.
The Solar Dynamic Ground Test Demonstration (SDGTD) successfully demonstrated a solar-powered closed Brayton cycle system in a relevant space thermal environment. In addition to meeting technical requirements the project was completed 4 months ahead of schedule and under budget. The following conclusions can be supported: 1. The component technology for solar dynamic closed Brayton cycle technology has clearly been demonstrated. 2. The thermal, optical, control, and electrical integration aspects of systems integration have also been successfully demonstrated. Physical integration aspects were not attempted as these tend to be driven primarily by mission-specific requirements. 3. System efficiency of greater than 15 percent (all losses fully accounted for) was demonstrated using equipment and designs which were not optimized. Some preexisting hardware was used to minimize cost and schedule. 4. Power generation of 2 kWe. 5. A NASA/industry team was developed that successfully worked together to accomplish project goals. The material presented in this report will show that the technology necessary to design and fabricate solar dynamic electrical power systems for space has been successfully developed and demonstrated. The data will further show that achieved results compare well with pretest predictions. The next step in the development of solar dynamic space power will be a flight test.
Reduced scale wind turbines can be extremely cost-effective to test new rotor concepts since prototype costs are heavily dependent on the rotor diameter. Ideally, the scaled model would have the same non-dimensional deflections, dynamics, and control behavior as the full-scale model. This would provide a high-fidelity demonstration of the full-scale performance, which is ideal if the full-scale turbine has significant aeroelastic interactions. To this end, servo-aero-gravo-elastic (SAGE) scaling is developed and applied to a 13-MW turbine that is scaled to a 20% scale model. The scaling preserves the tip-speed ratio, the rotor speed normalized by the flapping frequency, and the tip deflections normalized by the blade length. In addition, the controller employs the same control structure (gain-scheduled pitch control and variable speed torque control) and is scaled dynamically (e.g., matching non-dimensional time constant of the pitch angle, etc.). Furthermore, the thrust, gravity, and centrifugal moments are scaled such that the load angles are preserved as a function of a non-dimensional wind speed. However, the environmental scaling must consider differences in Reynolds number (since this parameter cannot be held constant) and subsequent changes in the axial induction factor. While the presented results showcase these differences during operational conditions, the non-dimensional tip deflections remain comparable through all wind speed ranges, indicating the viability of the SAGE scaling method in matching full-scale aeroelastic responses.
Parallel processing of symbolic computations on a message-passing multi-processor presents one challenge: To effectively utilize the available processors, the load must be distributed uniformly to all the processors. However, the structure of these computations cannot be predicted in advance. go, static scheduling methods are not applicable. In this paper, we compare the performance of two dynamic, distributed load balancing methods with extensive simulation studies. The two schemes are: the Contracting Within a Neighborhood (CWN) scheme proposed by us, and the Gradient Model proposed by Lin and Keller. We conclude that although simpler, the CWN is significantly more effective at distributing the work than the Gradient model.
Increasing deployment of distributed energy resources intensifies interactions among electric, gas, heating, and cooling systems. Inherent uncertainties ranging from internal parameters to external inputs also impose significant challenges on system operation. A coordinated scheduling method is, therefore, desired for facilitating efficient operation of multi-energy microgrids under multiple uncertainties. In this paper, a deterministic coordinated scheduling model is developed first with detailed modeling of system dynamics and device parameters to fully characterize complex interactions among multi-energy carriers. Then, a hybrid stochastic-interval method is proposed to account for heterogeneous uncertainties in decisions of operational strategies. Specifically, performance and efficiency uncertainties of distributed energy resources, and injection uncertainty of renewable sources and multienergy demands are characterized by interval-based uncertain operation regions and probability distributions, respectively. A scenario-based two-stage algorithm is developed to solve the problem so that multiple uncertainties are preserved in the entire decision-making process. Moreover, adjustable operational strategies are determined to hedge uncertainty by considering operators’ risk preferences. The validity of the proposed method is verified by comprehensive case studies on a test system.
A dynamic control policy known as 'threshold queueing' is defined for scheduling customers from a Poisson source on a set of two exponential servers with dissimilar service rates. The slower server is invoked in response to instantaneous system loading as measured by the length of the queue of waiting customers. In a threshold queueing policy, a specific queue length is identified as a 'threshold,' beyond which the slower server is invoked. The slower server remains busy until it completes service on a customer and the queue length is less than its invocation threshold. Markov chain analysis is employed to analyze the performance of the threshold queueing policy and to develop optimality criteria. It is shown that probabilistic control is suboptimal to minimize the mean number of customers in the system. An approximation to the optimum policy is analyzed which is computationally simple and suffices for most operational applications.
Six Jet A fuels, with varying compositions, were tested for low temperature flowability in a 190-liter simulator tank that modeled a section of a wing tank of a wide-body commercial airplane. The insulated tank was chilled by circulating coolant through the upper and lower surfaces. Flow-ability was determined as a function of fuel temperature by holdup, the fraction of unflowable fuel remaining in the tank after otherwise complete withdrawal. In static tests with subfreezing tank conditions, hold up varied with temperature and fuel composition. However, a general correlation of two or three classes of fuel type was obtained by plotting holdup as a function of the difference between freezing point and boundary-layer temperature, measured 0.6 cm above the bottom tank surface. Dynamic conditions of vibrations and slosh or rate of fuel withdrawal had very minor effects on holdup. Tests with cooling schedules to represent extreme, cold-day flights showed, at most, slight holdup for any combination of fuel type or dynamic conditions. Tests that superimposed external fuel heating and recirculation during the cooldown period indicates reduced hold up by modification of the low-temperature boundary layer. Fuel heating was just as effective when initiated during the later times of the tests as when applied continuously.
This paper describes the flight test evaluation of an advanced digital helicopter flight control system. The controller was designed using an optimal control design procedure for a fully coupled lateral and longitudinal vehicle model. Explicit integrals of the guidance error were included to produce a type 1 characteristic. Gain scheduling was used to account for changes in the vehicle dynamics. The digital controller was exercised by combining it with state estimators, a trajectory generator, and a closed-loop guidance algorithm to form a helicopter autoland system. A CH-47 tandem rotor helicopter was equipped with sensors, on-board digital flight computers, and electrohydraulic actuators. The system was exercised by automatically flying straight-in descending decelerating trajectories typcial of VFR manual landing approaches. A description of the test-ground facilities, the flight hardware and software, and the velocity and position tracking performance is included.
The authors describe an intelligent tool designed to aid managers of software development projects in planning, managing, and controlling the development process of medium- to large-scale software projects. Its purpose is to reduce uncertainties in the budget, personnel, and schedule planning of software development projects. It is based on dynamic model for the software development and maintenance life-cycle process. This dynamic process is composed of a number of time-varying, interacting developmental phases, each characterized by its intended functions and requirements. System dynamics is used as a modeling methodology. The resulting Software LIfe-Cycle Simulator (SLICS) and the hybrid expert simulation system of which it is a subsystem are described.
A real-time software controller that successfully integrates domain-based and resource-based control reasoning to perform task execution in a dynamically changing environment is described. The design of the controller is based on the concept of partitioning the process to be controlled into a set of tasks, each of which achieves some process goal. It is assumed that, in general, there are multiple ways (tasks) to achieve a goal. The controller dynamically determines current goals and their current criticality, choosing and scheduling tasks to achieve those goals in the time available. It incorporates rule-based goal reasoning, a TMS-based criticality propagation mechanism, and a real-time scheduler. The controller has been used to build a knowledge-based situation assessment system that formed a major component of a real-time, distributed, cooperative problem solving system built under DARPA contract. It is also being employed in other applications now in progress.
The NDE of Orbiter Vehicle-102 tile bonds, performed in August 1991, is described. The evaluation was carried out in order to help NASA develop fast, reliable methods to diagnose problems in tile bonding other than the present 'pull' and 'wiggle' tests. The NDE did not find any indication of bond problems, and all bonds were classified as 'nominal'. The feasibility of using NDE techniques in a dynamic, real-world environment without interfering with Shuttle rework schedules is shown. The data will be useful in verifying analytical models of tile behavior developed at the University of Central Florida. The need for a tile test bed containing known tile misbonds is suggested.
A set of programs was written to test the functionality and performance of the Alsys Ada implementation of the Catalogue of Interface Features and Options (CIFO), a set of optional Ada packages for real-time applications. No problems were found with the task id, preemption control, or shared-data packages. Minor problems were found with the dispatching control, dynamic priority, events, non-waiting entry call, semaphore, and scheduling packages. The Alsys implementation is derived mostly from Release 2 of the CIFO standard, but includes some of the features of Release 3 and some modifications unique to Alsys. Performance measurements show that the semaphore and shared-data features are an order-of-magnitude faster than the same mechanisms using an Ada rendezvous. The non-waiting entry call is slightly faster than a standard rendezvous. The existence of errors in the implementation, the incompleteness of the documentation from the published standard impair the usefulness of this implementation. Despite those short-comings, the Alsys CIFO implementation might be of value in the development of real-time applications.
Managing trajectory separation is critical to ensuring accessibility, efficiency, and safety in the unmanned airspace. The notion of geo-fences is an emerging concept, where distance buffers enclose individual trajectories and areas of operation in order to manage the airspace. Currently, the Air Traffic Management system for commercial travel defines static distance buffers around the aircraft; however, commercial UASs are envisioned to operate in significantly closer proximity to other UAS requiring a geo-fence for spacing operations. The geo-fence size can be determined based on vehicle performance characteristics, state of the airspace, weather, and other unforeseen events such as emergency or disaster response. Calculation of the geo-fence size could be determined as part of pre-flight planning and during real-time operations. A largely non-homogeneous fleet of UASs will be operating in low altitude and will likely be commercially developed. Due to intellectual property concerns, the operators may not provide detailed specifications of the control system to UTM. In addition, the huge variety of UAS makes modeling each control system prohibitive and flight data for these vehicles may not exist. Therefore, a generalized, simple geo-fence sizing algorithm must be developed such that it does not rely on detailed knowledge of the vehicle control system, accounts for the presence of urban winds, and is sufficiently accurate. In this work, two simple models are investigated to determine its feasibility as an adequate means for calculating the geo-fence size. The vehicle data used in this work are provided by UAS manufactures who have partnered with NASA's UTM project and some publicly available websites. The first model utilizes wind data processed from the NOAA HRRR (Hourly Rapid Refresh) product and Sonar Annemometer data provided by San Jose State. The second model utilizes OpenFOAM which is a CFD code used to generate a wind field for flow around a single building. The key vehicle performance parameters can include UAS response time to disturbances, command to actuation latency, control system rate limits, time to recovery to desired path, and aerodynamics. It was found that the first model provides an initial understanding of geo-fence sizing, but does not provide enough accuracy to provide UTM with an efficient means of scheduling vehicles. The results of the second model reveal that modeling UAS controls systems with a linearized plant and gain scheduled PID controller does not allow capture the UAS flight dynamics within a significant envelope of the wind disturbances.
Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as “open-loop” models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo (Merged soil Moisture) and six estimates from the HBV (Hydrologiska Byråns Vattenbalansavdelning) model with three precipitation inputs (ERA5, IMERG, and MSWEP) with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5 cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. We found that application of the Soil Wetness Index (SWI) smoothing filter resulted in improved performance for all satellite products. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3E SWI , SMOS SWI , AMSR2 SWI , and ASCAT SWI , with the L-band-based SMAPL3E SWI (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCI SWI ), MeMo performed better on average (median R of 0.72 versus 0.67), probably due to the inclusion of SMAPL3E SWI . The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale.
In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.
The problem of multiprogram scheduling on a single processor is studied from the viewpoint of the characteristics peculiar to the program functions that need guaranteed service. It is shown that an optimum fixed priority scheduler possesses an upper bound to processor utilization which may be as low as 70 percent for large task sets. It is also shown that full processor utilization can be achieved by dynamically assigning priorities on the basis of their current deadlines. A combination of these two scheduling techniques is also discussed.