SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This paper introduces an improved method for designing the class of CMOS VLSI asynchronous sequential circuits introduced in the paper by Sterling R. Whitaker and Gary K. Maki, 'Self Arbitrated VLSI Asynchronous Circuits.' Of main interest here is the simple design by inspection rules that arise from these circuits. This paper presents a variation on these circuits which reduces the number of transistors required.
Aerospace neural circuits must be adaptive, offer a practical size-performance ratio, and be environmentally robust. Our approach to building such circuits combines asynchronous design with a new fuzzy/neural classifier model. Asynchronous circuits offer many design advantages for neural hardware and our hybrid fuzzy/neural model, using mainly min and max operators, promises a low circuit complexity. The general approach is described and a description of a use of rule-induction to further reduce circuit complexity is described.
While conventional analog modems employ some kind of clock wave regenerator circuit for synchronous timing recovery, in sampled modem receivers the timing is recovered asynchronously to the incoming data stream, with no adjustment being made to the input sampling rate. All timing corrections are accomplished by digital operations on the sampled data stream, and timing recovery is asynchronous with the uncontrolled, input A/D system. A good timing error measurement algorithm is a zero crossing tracker proposed by Gardner. Digital, speech rate (2400 - 4800 bps) M-PSK modem receivers employing Gardner's zero crossing tracker were implemented and tested and found to achieve BER performance very close to theoretical values on the AWGN channel. Nyguist pulse shaped modem systems with excess bandwidth factors ranging from 100 to 60 percent were considered. We can show that for any symmetric M-PSK signal set Gardner's NDA algorithm is free of pattern jitter for any carrier phase offset for rectangular pulses and for Nyquist pulses having 100 percent excess bandwidth. Also, the Nyquist pulse shaped system is studied on the mobile satellite channel, where Doppler shifts and multipath fading degrade the pi/4-DQPSK signal. Two simple modifications to Gardner's zero crossing tracker enable it to remain useful in the presence of multipath fading.
This paper describes the recognition of implicit serialization due to coarse-grain, synchronous communication and demonstrates the conversion to asynchronous communication for the exchange of boundary condition information in the Thin-Layer Navier Stokes 3-Dimensional Multi Block (TLNS3DMB) code. The implementation details of using asynchronous communication is provided including buffer allocation, message identification, and barrier control. The IBM SP2 was used for the tests presented.
In support of satellite-ATM interoperability, researchers at the NASA Lewis Research Center performed asynchronous transfer mode (ATM) quality-of-service experiments using MPEG-2 (ATM application layer 5, AAL5) over ATM over an emulated satellite link. The purpose of these experiments was to determine the free-space link quality necessary to use the ATM protocol to transmit high-quality multimedia information. The experimental results have been submitted to various International Telecommunications Union (ITU) study groups in order to improve and modify current standards and recommendations for the telecommunications industry. Quality-of-service parameters for Class I, stringent class requirements for ITU-T I.356 are currently being debated. The experimental results presented will help to establish these quality-of-service thresholds. This material will also be useful in the development of the ITU-R WP-4B's Draft Preliminary New Recommendation on the Transmission of Asynchronous Transfer Mode Traffic via Satellite (Rec. S.atm).
A parallel Particle Swarm Optimization (PSO) algorithm is presented. Particle swarm optimization is a fairly recent addition to the family of non-gradient based, probabilistic search algorithms that is based on a simplified social model and is closely tied to swarming theory. Although PSO algorithms present several attractive properties to the designer, they are plagued by high computational cost as measured by elapsed time. One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. Previous parallel PSO algorithms were mostly implemented in a synchronous manner, where all design points within a design iteration are evaluated before the next iteration is started. This approach leads to poor parallel speedup in cases where a heterogeneous parallel environment is used and/or where the analysis time depends on the design point being analyzed. This paper introduces an asynchronous parallel PSO algorithm that greatly improves the parallel e ciency. The asynchronous algorithm is benchmarked on a cluster assembled of Apple Macintosh G5 desktop computers, using the multi-disciplinary optimization of a typical transport aircraft wing as an example.
As humans plan for missions beyond the reach of real-time communication supported by terrestrially-based crews (i.e., increasingly earth-independent spaceflight missions), we need to consider how to maximize this effectiveness despite asynchronous communication with Earth. Medical events – especially those involving the sparing of life, limb, or eyesight - often need to be acted on immediately, in real-time. Often the expertise necessary to successfully complete such action covers an enormous range of training that is unrealistic to expect from crews engaged in exploration spaceflight. Thus, the medical support paradigm for asynchronous environments must account for both the limitations and coordinate seamlessly among ground-based expertise, the need for real-time interventions, and the limited crew time and knowledge resources.
A system-level performance evaluation of Geiger-mode avalanche photodiode (GmAPD) arrays requires accurate measurement and prediction of the background rate of the device due to dark counts and other spurious detection events. Since a GmAPD detector reports only a binary value and timestamp associated with an avalanche event, dark count rates are typically measured by averaging thousands of frames to support a statistically significant measurement. For both synchronous and asynchronous detector, the Poisson distributed background rates are referenced to the time each pixel is armed. Unlike for synchronous GmAPD imagers where all the pixels are armed to an array-wide arm signal, an asynchronous pixel operates independently from its neighboring pixels; requiring the background rates to be calculated using an interarrival histogram. For both types of imagers, the background rate is typically evaluated by fitting an exponential distribution to a fixed window within a measured histogram of time intervals between detection events However, if the statistics of the background rate are insufficient – whether that is due to low population sizes, saturation, or a large dynamic range of population size across the array, the pixel, or array-wide, performance metrics may report results with varying accuracy. This paper reports on an implementation of an algorithm that evaluates GmAPD background rates based on statistical metrics rather than fixed windows. The algorithm functions by determining the appropriate integration window within the interarrival time histogram based on a per-pixel count rate set by a predetermined tolerable measurement error. The implementation of the algorithm allows us to characterize GmAPD arrays with orders of magnitude spread in background rates across the detector using common statistical parameters.
Cooperative practices will likely be foundational to future digitally enabled airspace operations characterized by decentralized and asynchronous decision-making. This paper explores the implementation of cooperative practices in high-altitude airspace. The digitally enabled operations framework, under exploratory investigation by NASA as a potential new operating mode, which is enabled and dependent on digital technologies and information sharing, may create new operational possibilities for a wide range of vehicle types and missions. An essential element of the operating mode framework under investigation, cooperative practices, could empower operators to manage critical functions such as deconfliction, equitable airspace usage, and demand-capacity balancing. The use of cooperative practices would involve asynchronous flight information sharing and decentralized conflict management by operators, representing a major change from traditional air traffic services that use synchronous surveillance information to support centralized decision-making by air traffic controllers. This paper details three key components for implementing cooperative practices for decentralized, digitally enabled operations: (a) intent modeling and sharing, (b) conflict detection, and (c) cooperative deconfliction.
Airline pilots must anticipate potential threats to passenger safety and efficient flight. Such anticipation needs to occur at both the system and individual levels, yet no formal training for these anticipatory behaviors currently exists. The emerging field of resilience engineering provides a framework to explore this problem. Given the complex nature of this problem, the assessment portion of the project constituted a challenge. Simulator time is expensive as simulators are costly to run, and they are extremely limited in number. Also, by the nature of their work, pilots as a group are hard to connect with in person; thus, asynchronous methods were adopted. Further, to ensure that authentic pilot behaviors were observed, task-based scenarios were used rather than focus group or interview protocols. This session explores the design of asynchronous learning and a measure for assessing pilot anticipatory behaviors outside of a simulator to help design learning opportunities for pilots. The scenario-based and active assessment items will be discussed in detail, and demonstrations of these items will be shared. These items constitute the bulk of the challenge for this work. At the time of this writing, data is being collected to assess the effectiveness of the interactive training module and validate the measures. This data will be analyzed and presented as part of the session. This will include any linkages between the scenario-based and traditional assessment items.
With the increasing penetration level of renewable power, the power systems’ inertias are decreasing. To ensure that the frequency is above the threshold of the under frequency load shedding, one effective way is to share the spinning reserves among asynchronous AC grids through HVDC systems. In this paper, a coordinated frequency regulation scheme that enables spinning reserves sharing is proposed for such hybrid AC/DC grids. This scheme is a communication-free method that consists of the droop control, the inertia emulation control and the frequency safety control. The combined response of the three controls can increase not only the frequency nadir but also the settled frequency of the disturbed grid. In addition, the hysteresis comparators and the power injection limits are adopted in the frequency regulation scheme to reduce the coupling effect among AC grids. Thus, under small and harmless disturbance, the frequency regulation scheme will be inactive; the disturbance in strong AC grids would not affect the weak AC systems. The frequency regulation scheme coordinates well with the automatic generation control of the grids. Furthermore, the feasibility and effectiveness of the proposed frequency regulation scheme are verified through simulation studies.
Abstract Solving large-scale inverse problems using deep-learning algorithms have become an essential part of modern research and industrial applications. The complexity of the underlying inverse problem may require the utilization of high performance computing systems which poses a challenge on the algorithmic design of the inverse problem solver. Most deep learning algorithms require, due to their design, custom parallelization techniques in order to be resource efficient while showing a reasonable convergence. In this paper we introduce a S calable A synchronous G enerative I nverse P roblem S olver (SAGIPS) on high-performance computing systems. We present a workflow that utilizes an asynchronous ring-allreduce algorithm to transfer the gradients of the generator network across multiple GPUs. Experiments with a scientific proxy application demonstrate that SAGIPS shows near linear weak scaling, together with a convergence quality that is comparable to traditional methods. The approach presented here allows leveraging Generative Adverserial Network across multiple GPUs, promising advancements in solving complex inverse problems at scale.
This paper investigates the problem of state estimation for distribution networks with asynchronous sensors comprising of a mix of smart meters and phasor measurement units (PMUs) with multiple sampling and reporting rates. We consider two independent scenarios of state estimation and tracking, with either voltages or currents as states. With these two sets, we investigate estimation under (a) full data, assuming all measurements are available and (b) limited data, where an online algorithmic approach is adopted to estimate the possibly time-varying states by processing measurements as and when available. The proposed algorithm, inspired by the classical Stochastic Gradient Descent (SGD) approach updates the states based on the previous estimate and the newly available measurements. Finally, we demonstrate the estimation and tracking efficacy through numerical simulations on the IEEE-37 test network, while also highlighting how estimation with currents as states leads to faster convergence.
This paper presents an integration study for the recent power electronic-based fast-frequency response technology, "asynchronous grid connection" which operates as an aggregator for behind-the-meter resources and distributed generators. Both technical feasibility and techno-economic viability studies are presented. The fast-frequency response characteristics, validated against Power Hardware-in-the-Loop experiments, are integrated into an IEEE 9- bus system in DigSilent PowerFactory for system-level dynamic analysis. It demonstrates that droop-based control enhancements to local distributed generators allow their aggregation to provide grid-supporting functionalities and participate in the ancillary service markets. To this end, a long-term simulation embedding the system within the ancillary service market framework of PJM has been performed. The fast-frequency response regulation is subsequently used to calculate the potential revenue and project the results on a 15-year investment horizon. Finally, the techno-economic analysis provides recommendations for enhancements to access the full potential of distributed generators on a technical and regulatory level.
The worst case timing margin of a synchronous design implemented with a field-programmable gate array (FPGA) is easy to perform using available FPGA design tools. However, it may be difficult to impossible to verify that worst case timing requirements are met for complex asynchronous logic design.
A method for the design of decentralized asynchronous controllers for spacecraft formations is presented.
This viewgraph presentation gives an overview of the Consultative Committee for Space Data Systems (CCSDS) Asynchronous Message Service (AMS). The topics include: 1) Key Features; 2) A single AMS continuum; 3) The AMS Protocol Suite; 4) A multi-continuum venture; 5) Constraining transmissions; 6) Security; 7) Fault Tolerance; 8) Performance of Reference Implementation; 9) AMS vs Multicast (1); 10) AMS vs Multicast (2); 11) RAMS testing exercise; and 12) Results.
Asynchronous evolutionary algorithms are becoming increasingly popular as a means of making full use of many processors while solving computationally expensive search and optimization problems. These algorithms excel at keeping large clusters fully utilized, but may sometimes inefficiently sample an excess of fast-evaluating solutions at the expense of higher-quality, slow-evaluating ones. We introduce a steady-state parent selection strategy, SWEET (“Selection whilE EvaluaTing”), that sometimes selects individuals that are still being evaluated and allows them to reproduce early. This gives slow-evaluating individuals that have higher fitnesses an increased ability to multiply in the population. We find that SWEET appears effective in simulated take-over time analysis, but that its benefit is confined mostly to early in the run, and our preliminary study on an autonomous vehicle controller problem that involves tuning a spiking neural network proves inconclusive.