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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

The mission operations planning assistant

The Mission Operations Planning Assistant (MOPA) is a knowledge-based system developed to support the planning and scheduling of instrument activities on the Upper Atmospheric Research Satellite (UARS). The MOPA system represents and maintains instrument plans at two levels of abstraction in order to keep plans comprehensible to both UARS Prinicpal Investigators and Command Management personnel. The hierarchical representation of plans also allows MOPA to automatically create detailed instrument activity plans from which spacecraft command loads may be generated. The MOPA system was developed on a Symbolics 3640 computer using the ZETALISP and ART languages. MOPA's features include a textual and graphical interface for plan inspection and modification, recognition of instrument operational constraint violations during the planning process, and consistency maintenance between the different planning levels. This paper describes the current MOPA system.

Schuetzle, James G.↗
NASA NTRS2009

Instrumentation and Performance Analysis Plans for the HIFiRE Flight 2 Experiment

Supersonic combustion performance of a bi-component gaseous hydrocarbon fuel mixture is one of the primary aspects under investigation in the HIFiRE Flight 2 experiment. In-flight instrumentation and post-test analyses will be two key elements used to determine the combustion performance. Pre-flight computational fluid dynamics (CFD) analyses provide valuable information that can be used to optimize the placement of a constrained set of wall pressure instrumentation in the experiment. The simulations also allow pre-flight assessments of performance sensitivities leading to estimates of overall uncertainty in the determination of combustion efficiency. Based on the pre-flight CFD results, 128 wall pressure sensors have been located throughout the isolator/combustor flowpath to minimize the error in determining the wall pressure force at Mach 8 flight conditions. Also, sensitivity analyses show that mass capture and combustor exit stream thrust are the two primary contributors to uncertainty in combustion efficiency.

Gruber, Mark↗
NASA NTRS1978

Space Shuttle data acquisition and processing

The techniques of minimizing the amount of Space Shuttle data processed by using real-time ground data and on board computer to prescreen the data are presented. With the advent of long duration space flight and the large amounts of data generated, it became necessary to limit the amount of data to be processed and also to present data in a manner that highlights the most important data. The Shuttle operational data system with output of 128 kilobits/sec, the developmental flight instrumentation system, and screening of data by the analysts, flight crew, or onboard computers is described, noting that by using these monitoring methods the mission evaluation team can rapidly determine time periods for which postflight data processing is required. Postflight processing systems, batch system output products, data compression techniques, the interactive computer system, and the special telemetry conversion system are discussed, and it is concluded that the combination of Shuttle on board and ground data processing systems enhances the ability to perform a functional evaluation of the Space Shuttle vehicle.

Foster, G. B., Jr.↗
DOE OSTI2016

Basic Research Needs for Innovation and Discovery of Transformative Experimental Tools

The scientific discoveries that expand the frontiers of human understanding, and that lead to the innovations of our technological world, require scientific tools and instrumentation to enable observation and manipulation of the physical world. As science advances, so too must its tools; the quest for deeper scientific insights and the drive to control chemistry and materials at the atomic and molecular levels require increasingly powerful and sophisticated instruments. A secure energy future requires technologies that use existing resources more efficiently, harness renewable resources, and efficiently store energy. The urgent demand for new energy technologies has ushered in a new era in scientific pursuit to decipher the complexity found at the core of chemical and materials processes, as articulated by the basic energy science research community in its series of Basic Research Needs (BRN) workshops. Historically, novel experimental tools and methods have been foundational in both scientific and technological advances — ranging from high-resolution microscopes that “see” atomic structures, to lithography that has enabled advances in semiconductors and computing. Today, expanding the frontiers of basic research requires new generations of instrumentation to reveal the intricacies of complex materials and chemical systems; energy systems in realistic working environments; and systems that are dynamical, far from equilibrium, and extremely heterogeneous. A concerted effort to invent, design, and build scientific instrumentation will enable new scientific breakthroughs and transformative technologies to address the most pressing energy challenges of the 21st century. To identify the highest priorities for the instrumentation innovation and development needed to address grand challenges in energy sciences, the U.S. Department of Energy’s Office of Basic Energy Sciences sponsored a workshop entitled, “Basic Research Needs for Innovation and Discovery of Transformative Experimental Tools” on June 1–3, 2016 near Washington, D.C. The workshop was attended by approximately 100 leading national and international scientific experts representing areas of basic energy sciences in chemistry, materials, physics, and biology, and included a mix of experimentalists and theorists.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Analysis and Optimization of Seismo-Acoustic Monitoring Networks with Bayesian Optimal Experimental Design

The Bayesian optimal experimental design (OED) problem seeks to identify data, sensor configurations, or experiments which can optimally reduce uncertainty. The goal of OED is to find an experiment that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge about expected data. Therefore, within the context of seismic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types, and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize the ability to locate seismic events from arrival time data of detected seismic phases. In order to do utilize Bayesian OED we must develop four elements:1. A likelihood function that describes the uncertainty of detection and travel times; 2. A Bayesian solver that takes a prior and likelihood to identify the posterior; 3. An algorithm to compute EIG; and, 4. An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we can explore many relevant questions to monitoring such as: how and what multiphenomenology data can be used to optimally reduce uncertainty, how to trade off sensor fidelity and earth model uncertainty, and how sensor types, number, and locations influence uncertainty

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

Using an instrumented manikin for Space Station Freedom analysis

One of the most intriguing and complex areas of current computer graphics research is animating human figures to behave in a realistic manner. Believable, accurate human models are desirable for many everyday uses including industrial and architectural design, medical applications, and human factors evaluations. For zero-gravity (0-g) spacecraft design and mission planning scenarios, they are particularly valuable since 0-g conditions are difficult to simulate in a one-gravity Earth environment. At NASA/JSC, an in-house human modeling package called PLAID is currently being used to produce animations for human factors evaluation of Space Station Freedom design issues. Presented here is an introductory background discussion of problems encountered in existing techniques for animating human models and how an instrumented manikin can help improve the realism of these models.

Orr, Linda↗
DOE OSTI2021

mystic : software for autonomous discovery and design under uncertainty

Throughout the diverse range of science and engineering applications, there is a growing desire to develop computational methods that can reliably predict the behavior of complex systems. Specifically, there is a strategic need for tools that can robustly forecast the behavior of complex physical systems, where data may be high-dimensional, noisy, or sparse, and models of the system may be time-dependent or include uncertainty. We use mystic to build tools that leverage statistical learning, physics-informed learning, and active learning in the efficient generation of reliably predictive surrogates for complex physical systems. mystic is a robust, proven, open-source optimization and uncertainty quantification toolkit with over a decade of use in the design and optimization of neutron instrumentation, solar-powered drones, and gasguns, and in iterative tuning of models for Raman spectroscopy and elastoplastic materials strength. Recent developments have focused on automated learning of statistically robust surrogates under uncertainty, with applications in materials in extreme environments, nanostructures, materials simulations and strength models, and the failure of shielding under particle radiation. In 2020, McKerns demonstrated active learning of optimally robust surrogates with respect to new simulated data for molecular dynamics simulations of materials mixing in warm dense matter, and is currently applying active learning to the automated steering of particle accelerator beams and the optimal design and control of quantum optical sensor instrumentation.

42 ENGINEERING↗
NASA NTRS2017

PandExo: A Community Tool for Transiting Exoplanet Science with JWST and HST

As we approach the James Webb Space Telescope (JWST) era, several studies have emerged that aim to (1) characterize how the instruments will perform and (2) determine what atmospheric spectral features could theoretically be detected using transmission and emission spectroscopy. To some degree, all these studies have relied on modeling of JWST's theoretical instrument noise. With under two years left until launch, it is imperative that the exoplanet community begins to digest and integrate these studies into their observing plans, as well as think about how to leverage the Hubble Space Telescope (HST) to optimize JWST observations. To encourage this and to allow all members of the community access to JWST & HST noise simulations, we present here an open-source Python package and online interface for creating observation simulations of all observatory-supported timeseries spectroscopy modes. This noise simulator, called PandExo, relies on some aspects of Space Telescope Science Institute's Exposure Time Calculator, Pandeia. We describe PandExo and the formalism for computing noise sources for JWST. Then we benchmark PandExoʼs performance against each instrument team's independently written noise simulator for JWST, and previous observations for HST. We find that PandExo is within 10% agreement for HST/WFC3 and for all JWST instruments.

Batalha, Natasha E.↗
DOE OSTI2013

Power consumption monitoring using additional monitoring device

Today, emphasis is placed on reducing power consumption. Computers are large consumers; therefore it is important to know the total consumption of computing systems. Since their optimal functioning requires quite strict environmental conditions, without much variation in temperature and humidity, reducing energy consumption cannot be made without monitoring environmental parameters. Thus, the present work uses a multifunctional electric meter UPT 210 for power consumption monitoring. Two applications were developed: software which carries meter readings provided by electronic and programming facilitates remote device and a device for temperature monitoring and control. Following temperature variations that occur both in the cooling system, as well as the ambient, can reduce energy consumption. For this purpose, some air conditioning units or some computers are stopped in different time slots. These intervals were set so that the economy is high, but the work's Datacenter is not disturbed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Nevada National Security Site Site-Directed Research and Development FY 2014 Annual Report

The reports contained herein are for project activities that occurred from October 2013 through September 2014. Project life cycle is indicated under the title as well as the original proposal number (in the following format: site abbreviation--ID #--originating fiscal year; e.g., STL-03-14). Each of the reports describes in detail the discoveries, achievements, and challenges encountered by our principal investigators. As SDRD, by definition, invests in “high-risk” and hopefully “high-payoff” research, the element of uncertainty is inherent. While many of our efforts are “successful” and result in positive outcomes or technology utilization, some fall short of expectations, but cannot be construed as “failure” in the negative sense. The latter is a natural and valid part of the process of advanced research and often leads to unforeseen new pathways to future discovery. Regardless, either result advances our knowledge base and increases our ability to identify solutions and/or avoid costly and unwarranted paths for future challenges. In summary, the SDRD program continues to provide an unfettered mechanism for innovation that returns multifold to our customers, to national security, and to the general public. The program is a vibrant R&D innovation engine, benefited by its discretionary pedigree, enhanced mission spectrum, committed resources, and sound competitiveness to yield maximum taxpayer benefit. The 25 projects described exemplify the creativity and ability of a diverse scientific and engineering talent base. The efforts also showcase an impressive capability and resource that can be brought to find solutions to a broad array of technology needs and applications relevant to the NNSS mission and national security. Further SDRD performance metrics can be found in the appendix at the end of this report.

36 MATERIALS SCIENCE↗
NASA NTRS1975

Doppler measurements of the ionosphere on the occasion of the Apollo-Soyuz test project. Part 1: Computer simulation of ionospheric-induced Doppler shifts

A computer simulation of the ionospheric experiment of the Apollo-Soyuz Test Project (ASTP) was performed. ASTP is the first example of USA/USSR cooperation in space and is scheduled for summer 1975. The experiment consists of performing dual-frequency Doppler measurements (at 162 and 324 MHz) between the Apollo Command Service Module (CSM) and the ASTP Docking Module (DM), both orbiting at 221-km height and at a relative distance of 300 km. The computer simulation showed that, with the Doppler measurement resolution of approximately 3 mHz provided by the instrumentation (in 10-sec integration time), ionospheric-induced Doppler shifts will be measurable accurately at all times, with some rare exceptions occurring when the radio path crosses regions of minimum ionospheric density. The computer simulation evaluated the ability of the experiment to measure changes of columnar electron content between CSM and DM (from which horizontal gradients of electron density at 221-km height can be obtained) and to measure variations in DM-to-ground columnar content (from which an averaged columnar content and the electron density at the DM can be deduced, under some simplifying assumptions).

Grossi, M. D.↗
NASA NTRS1996

Development of Minimally-Invasive Aortic Pressure and Flow Instrumentation

To better understand the mechanisms underlying the effects of microgravity on the cardiovascular system, cardiovascular models have been developed. These computational models estimate changes in cardiovascular parameters such as total peripheral resistance and systemic arterial compliance, and require high quality aortic pressure and flow measurements as their input. Many of these measurements are obtained in experimental animals and therefore the invasiveness of the instrumentation must be as kept to a minimum. These considerations are the primary motivation behind this work.

Ewert, Dan↗
DOE OSTI2025

Parallel sorting algorithm classification: is manual instrumentation necessary?

Understanding parallel algorithms is crucial for accelerating scientific simulations on complex, distributed memory, high-performance computers. Modern algorithm classification approaches learn semantics directly from source code to differentiate between algorithms, however, accessing source code is not always possible. We can learn about parallel algorithms from observing their performance, as programs running the same algorithms and using the same hardware should exhibit similar performance characteristics. We present an approach to learn algorithm classes from parallel performance data directly in order to classify algorithms without access to the source code. We extend previous work to enable classifying parallel sorting algorithms using automatic instrumentation instead of requiring manual region annotations in the source code. In this work, we design and demonstrate a study for classification of parallel sorting algorithms using parallel performance data collected from automatic instrumentation, and evaluate the performance of our new methodology on classification. We leverage Caliper to collect the performance data, Thicket for our exploratory data analysis (EDA), and PyTorch and Scikit-learn to evaluate the effectiveness of random forests, support vector machines (SVMs), decision trees, neural networks, and logistic regressions on parallel performance data. Additionally, we study noise in parallel performance data, whether the removal of noise and pre-processing of the data is necessary to accurately classify parallel sorting algorithms, and determine the effectiveness of features created from performance data. In conclusion, we demonstrate classification accuracy for these five different models of up to 97.7% across four different parallel algorithm classes.

Algorithm Classification↗
DOE OSTI2022

Enabling Modular Autonomous Feedback‐Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration

Abstract Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high‐throughput characterization, automatic analysis, and machine learning. Within a MAP, one or multiple autonomous feedback loops may aim to optimize materials for certain functional properties or to generate new insights. The scope of a given experiment campaign is defined by the range of experiment and analysis actions that are integrated into the experiment framework. Herein, the authors present a method for integrating many actions within a hierarchical experimental laboratory automation and orchestration (HELAO) framework. They demonstrate the capability of orchestrating distributed research instruments that can incorporate data from experiments, simulations, and databases. HELAO interfaces laboratory hardware and software distributed across several computers and operating systems for executing experiments, data analysis, provenance tracking, and autonomous planning. Parallelization is an effective approach for accelerating knowledge generation provided that multiple instruments can be effectively coordinated, which the authors demonstrate with parallel electrochemistry experiments orchestrated by HELAO. Efficient implementation of autonomous research strategies requires device sharing, asynchronous multithreading, and full integration of data management in experimental orchestration, which to the best of the authors’ knowledge, is demonstrated for the first time herein.

36 MATERIALS SCIENCE↗
NASA NTRS1983

Shuttle flight pressure instrumentation: Experience and lessons for the future

Flight data obtained from the Space Transportation System orbiter entries are processed and analyzed to assess the accuracy and performance of the Development Flight Instrumentation (DFI) pressure measurement system. Selected pressure measurements are compared with available wind tunnel and computational data and are further used to perform air data analyses using the Shuttle Entry Air Data System (SEADS) computation technique. The results are compared to air data from other sources. These comparisons isolate and demonstrate the effects of the various limitations of the DFI pressure measurement system. The effects of these limitations on orbiter performance analyses are addressed, and instrumentation modifications are recommended to improve the accuracy of similar fight data systems in the future.

Siemers, P. M., III↗
DOE OSTI2021

cuZ-Checker: A GPU-Based Ultra-Fast Assessment System for Lossy Compressions

Lossy compression is becoming an indispensable technique for the success of today's extreme-scale high-performance computing projects that produce vast volumes of data during scientific simulations or instrument data acquisitions. Comprehensively understanding the compression quality and performance of different lossy compressors is critical to selecting the best-fit compressors and using them properly and efficiently in practice. A few lossy compression assessment tools (e.g., Z-checker) have been developed, but none of them support the execution in a GPU environment. This is a significant gap because many recent extreme-scale applications and lossy compressors (e.g., cuSZ) can run entirely within GPUs. In this work, we develop an efficient lossy compression measuring system (called cuZ-Checker) on the GPU platform, which aims to perform the lossy compression quality and performance assessment completely within the GPU environment. Our contribution is threefold. (1) We develop a novel GPU-based lossy compression measuring framework using a computation pattern-based design approach. This approach classifies the computing-intensive metrics into three categories based on their patterns which creates large opportunities for kernel fusion and data reuse. (2) For each pattern in cuZ-Checker, we develop a CUDA kernel and provide fine-grained optimizations to boost its performance. (3) We thoroughly evaluate our cuZ-checker on a V100 GPU using four real-world scientific application datasets. Experiments show that cuZ-Checker can significantly accelerate the overall lossy compression assessment performance by 23X similar to 31X compared with the OpenMP-based multithreading CPU performance. To the best of our knowledge, this is the first lossy compression measuring system designed for GPU devices.

GPU↗
DOE OSTI2015

KINETIC EVOLUTION OF CORONAL HOLE PROTONS BY IMBALANCED ION-CYCLOTRON WAVES: IMPLICATIONS FOR MEASUREMENTS BY SOLAR PROBE PLUS

We extend the kinetic guiding-center model of collisionless coronal hole protons presented in Isenberg and Vasquez to consider driving by imbalanced spectra of obliquely propagating ion-cyclotron waves. These waves are assumed to be a small by-product of the imbalanced turbulent cascade to high perpendicular wavenumber, and their total intensity is taken to be 1% of the total fluctuation energy. We also extend the kinetic solutions for the proton distribution function in the resulting fast solar wind to heliocentric distances of 20 solar radii, which will be attainable by the Solar Probe Plus spacecraft. We consider three ratios of outward-propagating to inward-propagating resonant intensities: 1, 4, and 9. The self-consistent bulk flow speed reaches fast solar wind values in all cases, and these speeds are basically independent of the intensity ratio. The steady-state proton distribution is highly organized into nested constant-density shells by the resonant wave-particle interaction. The radial evolution of this kinetic distribution as the coronal hole plasma flows outward is understood as a competition between the inward- and outward-directed large-scale forces, causing an effective circulation of particles through the (v{sub ∥}, v{sub ⊥}) phase space and a characteristic asymmetric shape to the distribution. These asymmetries are substantial and persist to the outer limit of the model computation, where they should be observable by the Solar Probe Plus instruments.

79 ASTRONOMY AND ASTROPHYSICS↗