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At least 253 records · Page 14

Guidance, navigation, and control subsystem for the EOS-AM spacecraft

This paper presents the preliminary design of the Guidance, Navigation, and Control (GN&C) subsystem for the EOS-AM spacecraft and specifically focuses on the GN&C Normal Mode design. First, a brief description of the EOS-AM science mission, instruments, and system-level spacecraft design is provided. Next, an overview of the GN&C subsystem functional and performance requirements, hardware, and operating modes is presented. Then, the GN&C Normal Mode attitude determination, attitude control, and navigation systems are detailed. Finally, descriptions of the spacecraft's overall jitter performance and Safe Mode are provided.

Linder, David M.↗

A review of microgravity surgical investigations

The likelihood of performing a surgical procedure in space will increase as the Soviet Mir space station is expanded and the Space Station Freedom becomes operational. A review of previous research and hardware development, performed mostly in parabolic flight both in the Soviet Union and the U.S., reveals an interest in surgical chambers to prevent cabin atmosphere contamination. Surgical techniques appear to be no more difficult than in a 1-G environment if a restraint system is used. Minimizing the changes of wound infection from the high particle count spacecraft atmosphere is an additional concern. Additional research is necessary to delineate the clinical significance of these problems and to further develop surgical techniques in microgravity.

Campbell, Mark R.↗

Visualizing Parallel Computer System Performance

Parallel computer systems are among the most complex of man's creations, making satisfactory performance characterization difficult. Despite this complexity, there are strong, indeed, almost irresistible, incentives to quantify parallel system performance using a single metric. The fallacy lies in succumbing to such temptations. A complete performance characterization requires not only an analysis of the system's constituent levels, it also requires both static and dynamic characterizations. Static or average behavior analysis may mask transients that dramatically alter system performance. Although the human visual system is remarkedly adept at interpreting and identifying anomalies in false color data, the importance of dynamic, visual scientific data presentation has only recently been recognized Large, complex parallel system pose equally vexing performance interpretation problems. Data from hardware and software performance monitors must be presented in ways that emphasize important events while eluding irrelevant details. Design approaches and tools for performance visualization are the subject of this paper.

Malony, Allen D.↗

High Speed, Low Cost Telemetry Access from Space Development Update on Programmable Ultra Lightweight System Adaptable Radio (PULSAR)

Software Defined Radio (SDR) technology has been proven in the commercial sector since the early 1990's. Today's rapid advancement in mobile telephone reliability and power management capabilities exemplifies the effectiveness of the SDR technology for the modern communications market. In contrast, the foundations of transponder technology presently qualified for satellite applications were developed during the early space program of the 1960's. Conventional transponders are built to a specific platform and must be redesigned for every new bus while the SDR is adaptive in nature and can fit numerous applications with no hardware modifications. A SDR uses a minimum amount of analog / Radio Frequency (RF) components to up/down-convert the RF signal to/from a digital format. Once the signal is digitized, all processing is performed using hardware or software logic. Typical SDR digital processes include; filtering, modulation, up/down converting and demodulation. NASA Marshall Space Flight Center (MSFC) Programmable Ultra Lightweight System Adaptable Radio (PULSAR) leverages existing MSFC SDR designs and commercial sector enhanced capabilities to provide a path to a radiation tolerant SDR transponder. These innovations (1) reduce the cost of NASA Low Earth Orbit (LEO) and Deep Space standard transponders, (2) decrease power requirements, and (3) commensurately reduce volume. A second pay-off is the increased SDR flexibility by allowing the same hardware to implement multiple transponder types simply by altering hardware logic - no change of hardware is required - all of which will ultimately be accomplished in orbit. Development of SDR technology for space applications will provide a highly capable, low cost transponder to programs of all sizes. The MSFC PULSAR Project results in a Technology Readiness Level (TRL) 7 low-cost telemetry system available to Smallsat and CubeSat missions, as well as other platforms. This paper documents the continued development and verification/validation of the MSFC SDR, called PULSAR, which contributes to advancing the state-of-the-art in transponder design - directly applicable to the SmallSat and CubeSat communities. This paper focuses on lessons learned on the first sub-orbital flight (high altitude balloon) and the follow-on steps taken to validate PULSAR. A sounding rocket launch, currently planned for 03/2015, will further expose PULSAR to the high dynamics of sub-orbital flights. Future opportunities for orbiting satellite incorporation reside in the small satellite missions (FASTSat, CubeSat. etc.).

Simms, William Herbert, III↗

3D Printing in Zero-G ISS Technology Demonstration

The National Aeronautics and Space Administration (NASA) has a long term strategy to fabricate components and equipment on-demand for manned missions to the Moon, Mars, and beyond. To support this strategy, NASA and Made in Space, Inc. are developing the 3D Printing In Zero-G payload as a Technology Demonstration for the International Space Station. The 3D Printing In Zero-G experiment will be the first machine to perform 3D printing in space. The greater the distance from Earth and the longer the mission duration, the more difficult resupply becomes; this requires a change from the current spares, maintenance, repair, and hardware design model that has been used on the International Space Station up until now. Given the extension of the ISS Program, which will inevitably result in replacement parts being required, the ISS is an ideal platform to begin changing the current model for resupply and repair to one that is more suitable for all exploration missions. 3D Printing, more formally known as Additive Manufacturing, is the method of building parts/ objects/tools layer-by-layer. The 3D Print experiment will use extrusion-based additive manufacturing, which involves building an object out of plastic deposited by a wire-feed via an extruder head. Parts can be printed from data files loaded on the device at launch, as well as additional files uplinked to the device while on-orbit. The plastic extrusion additive manufacturing process is a low-energy, low-mass solution to many common needs on board the ISS. The 3D Print payload will serve as the ideal first step to proving that process in space. It is unreasonable to expect NASA to launch large blocks of material from which parts or tools can be traditionally machined, and even more unreasonable to fly up specialized manufacturing hardware to perform the entire range of function traditionally machining requires. The technology to produce parts on demand, in space, offers unique design options that are not possible through traditional manufacturing methods while offering cost-effective, high-precision, low-unit on-demand manufacturing. Thus, Additive Manufacturing capabilities are the foundation of an advanced manufacturing in space roadmap.

Johnston, Mallory M.↗

Integrating performance data collection, analysis, and visualization

An integrated data collection, analysis, and data visualization environment is described for a specific parallel system - the Intel iPSC/2 hypercube. The data collection components of the environment encompass software event tracing at the operating system with a program level and a hardware-based performance monitoring system used to capture software events. A visualization system based on the X-window environment permits dynamic display and reduction of performance data. A performance data collection, analysis, and visualization environment makes it possible to access the effects of architectural and system software variations.

Malony, Allen D.↗

Molecular Sieve Bench Testing and Computer Modeling

The design of an efficient four-bed molecular sieve (4BMS) CO2 removal system for the International Space Station depends on many mission parameters, such as duration, crew size, cost of power, volume, fluid interface properties, etc. A need for space vehicle CO2 removal system models capable of accurately performing extrapolated hardware predictions is inevitable due to the change of the parameters which influences the CO2 removal system capacity. The purpose is to investigate the mathematical techniques required for a model capable of accurate extrapolated performance predictions and to obtain test data required to estimate mass transfer coefficients and verify the computer model. Models have been developed to demonstrate that the finite difference technique can be successfully applied to sorbents and conditions used in spacecraft CO2 removal systems. The nonisothermal, axially dispersed, plug flow model with linear driving force for 5X sorbent and pore diffusion for silica gel are then applied to test data. A more complex model, a non-darcian model (two dimensional), has also been developed for simulation of the test data. This model takes into account the channeling effect on column breakthrough. Four FORTRAN computer programs are presented: a two-dimensional model of flow adsorption/desorption in a packed bed; a one-dimensional model of flow adsorption/desorption in a packed bed; a model of thermal vacuum desorption; and a model of a tri-sectional packed bed with two different sorbent materials. The programs are capable of simulating up to four gas constituents for each process, which can be increased with a few minor changes.

Mohamadinejad, Habib↗

DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives

We present a new parallel algorithm for probabilistic graphical model optimization. The algorithm relies on data-parallel primitives (DPPs), which provide portable performance over hardware architecture. We evaluate results on CPUs and GPUs for an image segmentation problem. Compared to a serial baseline, we observe runtime speedups of up to 13X (CPU) and 44X (GPU). We also compare our performance to a reference, OpenMP-based algorithm, and find speedups of up to 7X (CPU).

97 MATHEMATICS AND COMPUTING↗

FPGA-based HPC accelerators: An evaluation on performance and energy efficiency

Hardware specialization is a promising direction for the future of digital computing. Reconfigurable technologies enable hardware specialization with modest non-recurring engineering cost, but their performance and energy efficiency compared to state-of-the-art processor architectures remain an open question. In this article, we use FPGAs to evaluate the benefits of building specialized hardware for numerical kernels found in scientific applications. In order to properly evaluate performance, we not only compare Intel Arria 10 and Xilinx U280 performance against Intel Xeon, Intel Xeon Phi, and NVIDIA V100 GPUs, but we also extend the Empirical Roofline Toolkit (ERT) to FPGAs in order to assess our results in terms of the Roofline model. We show design optimization and tuning techniques for peak FPGA performance at reasonable hardware usage and power consumption. As FPGA peak performance is known to be far less than that of a GPU, we also benchmark the energy efficiency of each platform for the scientific kernels comparing against microbenchmark and technological limits. Results show that while FPGAs struggle to compete in absolute terms with GPUs on memory- and compute-intensive kernels, they require far less power and can deliver nearly the same energy efficiency.

97 MATHEMATICS AND COMPUTING↗

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Autonomous Flow Electrochemistry for Accelerated Catalyst Discovery

Our objective is to develop an Autonomous Chemical Experimentation (ACE) platform that accelerates discovery of new catalytic transformations and other energy-relevant chemical reactions and processes. We intentionally designed ACE to be highly modular, both with respect to its rapid deployment to different chemistries and experimental workflows as well as incorporation of a wide range of different AI algorithms. In addition to the development of the core software architecture, initial efforts were made to incorporate Large Language Models to provide human-interpretable reasoning of the optimizer’s actions, and to develop a user-friendly graphical interface for experimental researchers. ACE was demonstrated using a flow electrocatalysis platform containing an inline FTIR spectrometer for real-time analysis and quantification of the reaction outcome. Human-in-the-loop experiments were performed in which a human researcher conducted an experiment using electrode potentials suggested by ACE, then fed the spectral data back to ACE for decision making. After confirming the successful function of the optimizer, efforts were next directed to automation of the hardware and performed full autonomy tests using three reactions: catalytic oxidation of formate, catalytic oxidation of cyclohexanol, and oxidation of hydroquinone. These studies confirm that ACE can close the loop between reaction execution, analysis, and optimization. They also reveal that more improved product detection methods will be essential for ACE to make well-informed decisions for reactions with low conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spinstand demonstration of areal density enhancement using two-dimensional magnetic recording (invited)

Exponential growth of the areal density has driven the magnetic recording industry for almost sixty years. But now areal density growth is slowing down, suggesting that current technologies are reaching their fundamental limit. The next generation of recording technologies, namely, energy-assisted writing and bit-patterned media, remains just over the horizon. Two-Dimensional Magnetic Recording (TDMR) is a promising new approach, enabling continued areal density growth with only modest changes to the heads and recording electronics. We demonstrate a first generation implementation of TDMR by using a dual-element read sensor to improve the recovery of data encoded by a conventional low-density parity-check (LDPC) channel. The signals are combined with a 2D equalizer into a single modified waveform that is decoded by a standard LDPC channel. Our detection hardware can perform simultaneous measurement of the pre- and post-combined error rate information, allowing one set of measurements to assess the absolute areal density capability of the TDMR system as well as the gain over a conventional shingled magnetic recording system with identical components. We discuss areal density measurements using this hardware and demonstrate gains exceeding five percent based on experimental dual reader components.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Duong, Tuan A.↗

Hardware-based Advanced Electromagnetic Transient Simulation for A Large-Scale PV Plant in Real Time Digital Simulator

Power electronics-based resources, such as high-voltage direct current (HVdc) substations, photovoltaic (PV) plants, wind plants, electric vehicle charging stations, and energy storage systems, are increasingly being integrated within the power grid. Recently, multiple reports have emphasized the necessity for high-fidelity electromagnetic transient (EMT) simulations of these large-scale power electronics-based resources to accurately understand their behavior in power grids. However, performing hardware-based EMT simulations with high-fidelity models for such large power electronics systems is challenging due to the small time-step requirements and the involvement of a large number of states. This paper presents the implementation of hardware-based high-fidelity EMT dynamic model of a large-scale PV plant, accomplished through custom model development using the specific-C language in real-time digital simulator hardware (RTDS) and software (RSCAD).

Choi, Jongchan↗

Performance Testing of a Liquid Metal Pump for In-Space Power Systems

Fission surface power (FSP) systems could be used to provide power on the surface of the moon, Mars, or other planets and moons of our solar system. Fission power systems could provide excellent performance at any location, including those near the poles or other permanently shaded regions, and offer the capability to provide on demand power at any time, even at large distances from the sun. Fission-based systems also offer the potential for outposts, crew and science instruments to operate in a power-rich environment. NASA has been exploring technologies with the goal of reducing the cost and technical risk of employing FSP systems. A reference 40 kWe option has been devised that is cost-competitive with alternatives while providing more power for less mass anywhere on the lunar surface. The reference FSP system is also readily extensible for use on Mars, where it would be capable of operating through global dust storms and providing year-round power at any Martian latitude. Detailed development of the FSP concept and the reference mission are documented in various other reports. The development discussed in this paper prepares the way for testing of the Technology Demonstration Unit (TDU), which is a 10 kWe end-to-end test of FSP technologies intended to raise the entire FSP system to technology readiness level (TRL) 6. The Early Flight Fission Test Facility (EFF-TF) was established by NASA s Marshall Space Flight Center (MSFC) to provide a capability for performing hardware-directed activities to support multiple in-space nuclear reactor concepts by using a nonnuclear test methodology. This includes fabrication and testing at both the module/component level and at near prototypic reactor components and configurations allowing for realistic thermal-hydraulic evaluations of systems. The liquid-metal pump associated with the FSP system must be compatible with the liquid NaK coolant and have adequate performance to enable a viable flight system. Idaho National Laboratory (INL) was tasked with the modeling, design, and fabrication of an ALIP suitable for the FSP reference mission. A prototypic ALIP was fabricated under the direction of INL and shipped to MSFC for inclusion in the Technology Demonstration Unit (TDU), a quarter-scale end-to-end reactor simulator system that is scheduled for testing at NASA-GRC. Before inclusion in the TDU, the ALIP was tested in the ALIP test circuit (ATC), which is a rig developed and operated at MSFC for the specific purpose of providing accurate quantification of liquid metal pump performance. Data showing the pump performance curves (pressure, flowrate, and pump efficiency) are presented for various operating power levels, demonstrating the full performance envelope of the pump.

Polzin, Kurt↗

Comparing three generations of D-Wave quantum annealers for minor embedded combinatorial optimization problems

Abstract Quantum annealing (QA) is a novel type of analog computation that aims to use quantum mechanical fluctuations to search for optimal solutions of Ising problems. QA in the transverse Ising model, implemented on D-Wave quantum processing units, are available as cloud computing resources. In this study we report concise benchmarks across three generations of D-Wave quantum annealers, consisting of four different devices, for the NP-hard discrete combinatorial optimization problems unweighted maximum clique and unweighted maximum cut on random graphs. The Ising, or equivalently quadratic unconstrained binary optimization, formulation of these problems do not require auxiliary variables for order reduction, and their overall structure and weights are not highly variable, which makes these problems simple test cases to understand the sampling capability of current D-Wave quantum annealers. All-to-all minor embeddings of size 52, with relatively uniform chain lengths, are used for a direct comparison across the Chimera, Pegasus, and Zephyr device topologies. A grid-search over annealing times and the minor embedding chain strengths is performed in order to determine the level of reasonable performance for each device and problem type. Experiment metrics that are reported are approximation ratios for non-broken chain samples, chain break proportions, and time-to-solution for the maximum clique problem instances. How fairly the quantum annealers sample optimal maximum cliques, for instances which contain multiple maximum cliques, is quantified using entropy of the measured ground state distributions. The newest generation of quantum annealing hardware, which has a Zephyr hardware connectivity, performed the best overall with respect to approximation ratios and chain break frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Lightweight Detection of Cache Conflicts

In memory hierarchies, caches perform an important role in reducing average memory access latency. Minimizing cache misses can yield significant performance gains. As set-associative caches are widely used in modern architectures, capacity and conflict cache misses co-exist. These two types of cache misses require different optimization strategies. While cache misses are commonly studied using cache simulators, state-of-the-art simulators usually incur hundreds to thousands of times a program’s execution runtime. Moreover, a simulator has difficulty in simulating complex real hardware. To overcome these limitations, measurement methods are proposed to directly monitor program execution on real hardware via performance monitoring units. However, existing measurement-based tools either focus on capacity cache misses or do not distinguish capacity and conflict cache misses. In this paper, we design and implement CCProf, a lightweight measurement-based profiler that identifies conflict cache misses and associates them with program source code and data structures. CCProf incurs moderate runtime overhead that is at least an order of magnitude lower than simulators. With the evaluation on a number of representative programs, CCProf is able to guide optimizations on cache conflict misses and obtain nontrivial speedups.

Roy, Probir↗

International Neuroscience Initiatives through the Lens of High-Performance Computing

Neuroscience initiatives aim to develop new technologies and tools to measure and manipulate neuronal circuits. In this paper, to deal with the massive amounts of data generated by these tools, the authors envision the co-location of open data repositories in standardized formats together with high-performance computing hardware utilizing open source optimized analysis codes.

60 APPLIED LIFE SCIENCES↗