SEARCH · Search NASA

Results for “reduce task”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,405 records · Page 78

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗

DOE OSTI2016

Staggered scheduling of sensor estimation and fusion for tracking over long-haul links

Networked sensing can be found in a multitude of real-world applications. Here, we focus on the communication-and computation-constrained long-haul sensor networks, where sensors are remotely deployed over a vast geographical area to perform certain tasks. Of special interest is a class of such networks where sensors take measurements of one or more dynamic targets and send their state estimates to a remote fusion center via long-haul satellite links. The severe loss and delay over such links can easily reduce the amount of sensor data received by the fusion center, thereby limiting the potential information fusion gain and resulting in suboptimal tracking performance. In this paper, starting with the temporal-domain staggered estimation for an individual sensor, we explore the impact of the so-called intra-state prediction and retrodiction on estimation errors. We then investigate the effect of such estimation scheduling across different sensors on the spatial-domain fusion performance, where the sensing time epochs across sensors are scheduled in an asynchronous and staggered manner. In particular, the impact of communication delay and loss as well as sensor bias on such scheduling is explored by means of numerical and simulation studies that demonstrate the validity of our analysis.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

A Study of the Trade-off Between Reducing Precision and Reducing Resolution for Data Analysis and Visualization

There presently exist two dominant strategies to reduce data sizes in analysis and visualization: reducing the precision of the data, e.g., through quantization, or reducing its resolution, e.g., by subsampling. Both have advantages and disadvantages and both face fundamental limits at which the reduced information ceases to be useful. The paper explores the additional gains that could be achieved by combining both strategies. In particular, we present a common framework that allows us to study the trade-off in reducing precision and/or resolution in a principled manner. We represent data reduction schemes as progressive streams of bits and study how various bit orderings such as by resolution, by precision, etc., impact the resulting approximation error across a variety of data sets as well as analysis tasks. Additionally, we compute streams that are optimized for different tasks to serve as lower bounds on the achievable error. Scientific data management systems can use the results proposed in this paper as guidance on how to store and stream data to make efficient use of the limited storage and bandwidth in practice.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Evaluation of Radiation Proofing Polyethylene: Use of Oxygen Scavenging Additives

The degradation of polyethylene (PE) from radiation sources with both thermal and nuclear interactions show sensitivities towards oxygen and air. Characterization of the sensitivities in both inert and oxygenated atmospheres can be characterized by thermogravimetric analysis (TGA). Under argon, the thermal degradation of PE follows a random scission pathway that has activation energy of ~229 kJ mol -1 . The activation energy of PE is reduced by ~30% when 1% air is added to the inert argon atmosphere, illustrating the impact of oxygen on the degradation of PE. This effort seeks to diminish degradation of PE waste containment bags and extend their lifetime, thereby, reducing the cost and worker exposure risk. The project evaluated the use of oxygen scavenger nanoparticles to mitigate the deteriorating effects of oxygen on polymer physical properties and reduce polymer degradation. The thermal degradation of PE composites with various additives were tested and two additives showed promising results approaching the activation energy of pristine PE in an inert atmosphere. This activity was sponsored by the EM Office of Technology Development through SRNL’s Technical Task Plan SR091701.

36 MATERIALS SCIENCE↗

DOE OSTI2021

PV Performance Modeling and Stakeholder Engagement (Q1 FY2021 Project Report))

The objectives of this project are as follows: 1) Reduce uncertainty in PV performance models by developing and validating new and improved models and submodes. 2) Create and manage an open source repository of modeling functions and data. 3) Build and grow the PV Performance Modeling Collaborative 4) Represent the US in the IEA PVPS Task 13 Working group.

14 SOLAR ENERGY↗

DOE OSTI2022

Unified Language Frontend for Physic-Informed AI/ML

Artificial intelligence and machine learning (AI/ML) are becoming important tools for scientific modeling and simulation as in several other fields such as image analysis and natural language processing. ML techniques can leverage the computing power available in modern systems and reduce the human effort needed to configure experiments, interpret and visualize results, draw conclusions from huge quantities of raw data, and build surrogates for physics based models. Domain scientists in fields like fluid dynamics, microelectronics and chemistry can automate many of their most difficult and repetitive tasks or improve the design times by use of the faster ML-surrogates. However, modern ML and traditional scientific highperformance computing (HPC) tend to use completely different software ecosystems. While ML frameworks like PyTorch and TensorFlow provide Python APIs, most HPC applications and libraries are written in C++. Direct interoperability between the two languages is possible but is tedious and error-prone. In this work, we show that a compiler-based approach can bridge the gap between ML frameworks and scientific software with less developer effort and better efficiency. We use the MLIR (multi-level intermediate representation) ecosystem to compile a pre-trained convolutional neural network (CNN) in PyTorch to freestanding C++ source code in the Kokkos programming model. Kokkos is a programming model widely used in HPC to write portable, shared-memory parallel code that can natively target a variety of CPU and GPU architectures. Our compiler-generated source code can be directly integrated into any Kokkosbased application with no dependencies on Python or cross-language interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Interpolation as a means of shift selection for multilevel Monte Carlo with lattice displacements

The calculation of disconnected diagram contributions to physical signals is a computationally expensive task in Lattice QCD. To extract the physical signal, the trace of the inverse Lattice Dirac operator, a large sparse matrix, must be stochastically estimated. Because the variance of the stochastic estimator is typically large, variance reduction techniques must be employed. Multilevel Monte Carlo (MLMC) methods reduce the variance of the trace estimator by utilizing a telescoping sequence of estimators. Frequency Splitting is one such method that uses a sequence of inverses of shifted operators to estimate the trace of the inverse of the lattice Dirac operator, however there is no a priori way to select the shifts that minimize the cost of the multilevel trace estimation. We present a sampling and interpolation scheme that is able to predict the variances associated with Frequency Splitting under displacements of the underlying space time lattice. The interpolation scheme is able to predict the variances to high accuracy and therefore choose shifts that correspond to an approximate minimum of the cost for the trace estimation. We show that Frequency Splitting with the chosen shifts displays significant speedups over multigrid deflation

Whyte, Travis↗

NASA NTRS1982

Flight tests for the assessment of task performance and control activity

The tests were performed with the helicopters BO 105 and UH-1D. Closely connected with tactical demands the six test pilots' task was to minimize the time and the altitude over the obstacles. The data reduction yields statistical evaluation parameters describing the control activity of the pilots and the achieved task performance. The results are shown in form of evaluation diagrams. Additionally dolphin tests with varied control strategy were performed to get more insight into the influence of control techniques. From these test results recommendations can be derived to emphasize the direct force control and to reduce the collective to pitch crosscoupling for the dolphin.

Pausder, H. J.↗

NASA NTRS1985

Multimode Acoustic Research

There is a need for high temperature containerless processing facilities that can efficiently position and manipulate molten samples in the reduced gravity environment of space. The goal of the research is to develop sophisticated high temperature manipulation capabilities such as selection of arbitrary axes rotation and rapid sample cooling. This program will investigate new classes of acoustic levitation in rectangular, cylindrical and spherical geometries. The program tasks include calculating theoretical expressions of the acoustic forces in these geometries for the excitation of up to three acoustic modes (multimodes). These calculations are used to: (1) determine those acoustic modes that produce stable levitation, (2) isolate the levitation and rotation capabilities to produce more than one axis of rotation, and (3) develop methods to translate samples down long tube cylindrical chambers. Experimental levitators will then be constructed to verify the stable levitation and rotation predictions of the models.

Barmatz, M.↗

NASA NTRS1988

Human workload in aviation

The application of human-factors analysis techniques to the evaluation of aircraft-crew workloads is discussed in an introductory overview. Consideration is given to the importance of workload for safety, crew size, automation, and certification; the definition and measurement of workload, physical vs mental workloads, subjective ratings, secondary tasks, biocybernetic measures, and attention and workload. Recent studies of pilot and ATC workloads are reviewed, and typical data are presented in graphs. Future trends are discussed, and it is predicted that increased cockpit automation will eventually require new methods to maintain operator attention rather than reduce workload.

Kantowitz, Barry H.↗

NASA NTRS1999

Muscle Deoxygenation Causes Muscle Fatigue

Muscle fatigue is a common musculoskeletal disorder in the work place, and may be a harbinger for more disabling cumulative trauma disorders. Although the cause of fatigue is multifactorial, reduced blood flow and muscle oxygenation may be the primary factor in causing muscle fatigue during low intensity muscle exertion. Muscle fatigue is defined as a reduction in muscle force production, and also occurs among astronauts who are subjected to postural constraints while performing lengthy, repetitive tasks. The objectives of this research are to: 1) develop an objective tool to study the role of decreased muscle oxygenation on muscle force production, and 2) to evaluate muscle fatigue during prolonged glovebox work.

Murthy, G.↗

NASA NTRS1997

Pilot Non-Conformance to Alerting System Commands During Closely Spaced Parallel Approaches

Cockpit alerting systems monitor potentially hazardous situations, both inside and outside the aircraft. When a hazard is projected to occur, the alerting system displays alerts and/or command decisions to the pilot. However, pilots have been observed to not conform to alerting system commands by delaying their response or by not following the automatic commands exactly. This non-conformance to the automatic alerting system can reduce its benefit. Therefore, a need exists to understand the causes and effects of pilot non-conformance in order to develop automatic alerting systems whose commands the pilots are more likely to follow. These considerations were examined through flight simulator evaluations of the collision avoidance task during closely spaced parallel approaches. This task provided a useful case-study because the effects of non-conformance can be significant, given the time-critical nature of the task. A preliminary evaluation of alerting systems identified non-conformance in over 40% of the cases and a corresponding drop in collision avoidance performance. A follow-on experiment found subjects' alerting and maneuver selection criteria were consistent with different strategies than those used by automatic systems, indicating the pilot may potentially disagree with the alerting system if the pilot attempts to verify automatic alerts and commanded avoidance maneuvers. A final experiment found supporting automatic alerts with the explicit display of its underlying criteria resulted in more consistent subject reactions. In light of these experimental results, a general discussion of pilot non-conformance is provided. Contributing factors in pilot non-conformance include a lack of confidence in the automatic system and mismatches between the alerting system's commands and the pilots' own decisions based on the information available to them. The effects of non-conformance on system performance are discussed. Possible methods of reconciling mismatches are given, and design considerations for alerting systems which alleviate the problem of non-conformance are provided.

Pritchett, Amy Ruth↗

NASA NTRS2011

Multi-Axis Identifiability Using Single-Surface Parameter Estimation Maneuvers on the X-48B Blended Wing Body

The problem of parameter estimation on hybrid-wing-body type aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aero- dynamic control effectors that act in coplanar motion. This fact adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of system inputs must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, asymmetric, single-surface maneuvers are used to excite multiple axes of aircraft motion simultaneously. Time history reconstructions of the moment coefficients computed by the solved regression models are then compared to each other in order to assess relative model accuracy. The reduced flight-test time required for inner surface parameter estimation using multi-axis methods was found to come at the cost of slightly reduced accuracy and statistical confidence for linear regression methods. Since the multi-axis maneuvers captured parameter estimates similar to both longitudinal and lateral-directional maneuvers combined, the number of test points required for the inner, aileron-like surfaces could in theory have been reduced by 50%. While trends were similar, however, individual parameters as estimated by a multi-axis model were typically different by an average absolute difference of roughly 15-20%, with decreased statistical significance, than those estimated by a single-axis model. The multi-axis model exhibited an increase in overall fit error of roughly 1-5% for the linear regression estimates with respect to the single-axis model, when applied to flight data designed for each, respectively.

Ratnayake, Nalin A.↗

NASA NTRS2015

Update on Risk Reduction Activities for a Liquid Advanced Booster for NASA's Space Launch System

The stated goals of NASA's Research Announcement for the Space Launch System (SLS) Advanced Booster Engineering Demonstration and/or Risk Reduction (ABEDRR) are to reduce risks leading to an affordable Advanced Booster that meets the evolved capabilities of SLS; and enable competition by mitigating targeted Advanced Booster risks to enhance SLS affordability. Dynetics, Inc. and Aerojet Rocketdyne (AR) formed a team to offer a wide-ranging set of risk reduction activities and full-scale, system-level demonstrations that support NASA's ABEDRR goals. For NASA's SLS ABEDRR procurement, Dynetics and AR formed a team to offer a series of full-scale risk mitigation hardware demonstrations for an affordable booster approach that meets the evolved capabilities of the SLS. To establish a basis for the risk reduction activities, the Dynetics Team developed a booster design that takes advantage of the flight-proven Apollo-Saturn F-1. Using NASA's vehicle assumptions for the SLS Block 2, a two-engine, F-1-based booster design delivers 150 mT (331 klbm) payload to LEO, 20 mT (44 klbm) above NASA's requirements. This enables a low-cost, robust approach to structural design. During the ABEDRR effort, the Dynetics Team has modified proven Apollo-Saturn components and subsystems to improve affordability and reliability (e.g., reduce parts counts, touch labor, or use lower cost manufacturing processes and materials). The team has built hardware to validate production costs and completed tests to demonstrate it can meet performance requirements. State-of-the-art manufacturing and processing techniques have been applied to the heritage F-1, resulting in a low recurring cost engine while retaining the benefits of Apollo-era experience. NASA test facilities have been used to perform low-cost risk-reduction engine testing. In early 2014, NASA and the Dynetics Team agreed to move additional large liquid oxygen/kerosene engine work under Dynetics' ABEDRR contract. Also led by AR, the objectives of this work are to demonstrate combustion stability and measure performance of a 500,000 lbf class Oxidizer-Rich Staged Combustion (ORSC) cycle main injector. A trade study was completed to investigate the feasibility, cost effectiveness, and technical maturity of a domestically produced Atlas V engine that could also potentially satisfy NASA SLS payload-to-orbit requirements via an advanced booster application. Engine physical dimensions and performance parameters resulting from this study provide the system level requirements for the ORSC risk reduction test article. The test article is scheduled to complete critical design review this fall and begin testing in 2017. Dynetics has also designed, developed, and built innovative tank and structure assemblies using friction stir welding to leverage recent NASA investments in manufacturing tools, facilities, and processes, significantly reducing development and recurring costs. The full-scale cryotank assembly was used to verify the structural design and prove affordable processes. Dynetics performed hydrostatic and cryothermal proof tests on the assembly to verify the assembly meets performance requirements. This paper will discuss the ABEDRR engine task and structures task achievements to date and the remaining effort through the end of the contract.

Crocker, Andrew M.↗

NASA NTRS2015

Pathfinder Lander Rover Recharge System, and MARCO POLO Controls and ACME Regolith Feed System Controls and Integration

This project stems from the Exploration, Research, and Technology Directorate (UB) Projects Division, and one of their main initiatives is the "Journey to Mars". Landing on the surface of Mars which is millions of miles away is an incredibly large challenge. The terrain is covered in boulders, deep canyons, volcanic mountains, and spotted with sand dunes. The robotic lander is a kind of spacecraft with multiple purposes. One purpose is to be the protective shell for the Martian rover and absorb the impact from the landing forces; another purpose is to be a place where the rovers can come back to, actively communicate with, and recharge their batteries from. Rovers have been instrumental to the Journey to Mars initiative. They have been performing key research on the terrain of the red planet, trying to unlock the mysteries of the land for over a decade. The rovers that will need charging will not all have the same kind of internal battery either. RASSOR batteries may differ from the PbAC batteries inside Red Rover's chassis. NASA has invested heavily in the exploration of the surface of Mars. A driving force behind further exploration is the need for a more efficient operation of Martian rovers. One way is to reduce the weight as much as possible to reduce power consumption given the same mission parameters. In order to reduce the mass of the rovers, power generation, communication, and sample analysis systems currently onboard Martian rovers can be moved to a stationary lander deck. Positioning these systems from the rover to the Lander deck allows a taskforce of smaller, lighter rovers to perform the same tasks currently performed by or planned for larger rovers. A major task in transferring these systems to a stationary lander deck is ensuring that power can be transferred to the rovers.

Internship↗

NASA NTRS2018

Command and Control Software Development

The future of the National Aeronautics and Space Administration (NASA) depends on its innovation and efficiency in the coming years. With ambitious goals to reach Mars and explore the vast universe, correct steps must be taken to ensure our space program reaches its destination safely. The interns in the Exploration Systems and Operations Division at the Kennedy Space Center (KSC) have been tasked with building command line tools to ease the process of managing and testing the data being produced by the ground control systems while its recording system is not in use. While working alongside full-time engineers, we were able to create multiple programs that reduce the cost and time it takes to test the subsystems that launch rockets to outer space.

Wallace, Michael↗

NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗

DOE OSTI2017

IEA Wind Task 37: Systems Modeling Framework and Ontology for Wind Turbines and Plants

This presentation will provide an overview of progress to date in the development of a system modeling framework and ontology for wind turbines and plants as part of the larger IEA Wind Task 37 on wind energy systems engineering. The goals of the effort are to create a set of guidelines for a common conceptual architecture for wind turbines and plants so that practitioners can more easily share descriptions of wind turbines and plants across multiple parties and reduce the effort for translating descriptions between models; integrate different models together and collaborate on model development; and translate models among different levels of fidelity in the system.

17 WIND ENERGY↗