The AMTRAN sampler system instruction manual
Instruction manual for efficient utilization of automatic mathematical translator /AMTRAN/ SAMPLER software - online remote terminal computer system
INSTRUCTION↗
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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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Electronic heterodyne moire deflectometry: A method for transient and three dimensional density fields measurements
Effects of diffraction and nonlinear photographic emulsion characteristics on the performance of deferred electronic heterodyne moire deflectometry are investigated. The deferred deflectometry is used for measurements of nonsteady phase objects where it is difficult to complete the analysis of the field in real time. The sensitivity, accuracy and resolution of the system are calculated and it is shown that they are weakly affected by diffraction and by nonlinear recording. The feactures of the system are significantly improved compared with the conventional deferred intensity moire technique, and are comparable with the online heterodyne moire. The system was evaluated experimentally by deferred measurements of the refractive index gradients of a weak phase object consisting of a large KD*P crystal. This was done by photographing the phase object through a Ronchi grating and analyzing the tranparency with the electronic heterodyne readout system. The results are compared with the measurements performed on the same phase object with online heterodyne moire deflectometry and with heterodyne holographic interferometry methods. Some practical considerations for system improvement are discussed.
Stricker, Josef↗
Evaluating lightweight unsupervised online IDS for masquerade attacks in CAN
Vehicular controller area networks (CANs) are susceptible to masquerade attacks by malicious adversaries. In masquerade attacks, adversaries silence a targeted ID and then send malicious frames with forged content at the expected timing of benign frames. As masquerade attacks could seriously harm vehicle functionality and are the stealthiest attacks to detect in CAN, recent work has devoted attention to compare frameworks for detecting masquerade attacks in CAN. However, most existing works report offline evaluations using CAN logs already collected using simulations that do not comply with the domain’s real-time constraints. Here we contribute to advance the state of the art by presenting a comparative evaluation of four different non-deep learning (DL)-based unsupervised online intrusion detection systems (IDS) for masquerade attacks in CAN. Our approach differs from existing comparative evaluations in that we analyze the effect of controlling streaming data conditions in a sliding window setting. In doing so, we use realistic masquerade attacks being replayed from the ROAD dataset. We show that although evaluated IDS are not effective at detecting every attack type, the method that relies on detecting changes in the hierarchical structure of clusters of time series produces the best results at the expense of higher computational overhead. We discuss limitations, open challenges, and how the evaluated methods can be used for practical unsupervised online CAN IDS for masquerade attacks.
Anomaly detection↗
Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm
This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.
Brenner, Martin J.↗
Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System
The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.
Williams-Hayes, Peggy S.↗
An exploration of online-simulation-driven portfolio scheduling in Workflow Management Systems
Workflow Management Systems used to automate the execution of scientific workflow applications on parallel and distributed computing platforms must make scheduling decisions at runtime. A large number of workflow scheduling algorithms have been proposed in the literature, but often these algorithms are evaluated based on simplifying assumptions that may not hold in practice. Furthermore, published algorithm evaluation and/or comparison results are necessarily only for a subset of all possible scenarios, and thus may not include scenarios relevant to particular use-cases. Consequently, it is difficult for Workflow Management Systems (WMSs) developers to decide which scheduling algorithm should be implemented. To obviate this difficulty, one possible approach is to implement a portfolio of scheduling algorithms and select the most effective algorithm at runtime. One method for performing this selection is to run an online simulation for each algorithm in the portfolio. The algorithm that leads to the best performance, in simulation, is selected for future use. The above simulation-driven portfolio scheduling (SDPS) approach has been proposed in a few parallel and distributed computing contexts. The main objective of this work is to evaluate the feasibility and potential merit of SDPS if implemented in WMSs. Here we perform this evaluation using simulated WMS executions, where the simulations are instantiated from real-world platform and workflow configurations. Our main finding is that SDPS is on par with or outperforms an approach in which a single algorithm is used, where this algorithm is the one that performs best on average across all our experimental scenarios. Furthermore, we find that SDPS remains an attractive proposition even in the presence of high levels of simulation error and for simulators with relatively low levels of sophistication. In many of our experimental scenarios we find that mitigating simulation error at runtime can further improve performance. Finally, we show that simulation overhead can be made sufficiently low for SDPS to be feasible in practice.
97 MATHEMATICS AND COMPUTING↗
FLYING SERVING: On-the-Fly Parallelism Switching for Large Language Model Serving
Production LLM serving must simultaneously deliver high throughput, low latency, and sufficient context capacity under non-stationary traffic and mixed request requirements. Data parallelism (DP) maximizes throughput by running independent replicas, while tensor parallelism (TP) reduces per-request latency and pools memory for long-context inference. However, existing serving stacks typically commit to a static parallelism configuration at deployment; adapting to bursts, priorities, or long-context requests is often disruptive and slow. We present Flying Serving, a vLLM-based system that enables online DP-TP switching without restarting engine workers. Flying Serving makes reconfiguration practical by virtualizing the state that would otherwise force data movement: (i) a zero-copy Model Weights Manager that exposes TP shard views on demand, (ii) a KV Cache Adaptor that preserves request KV state across DP/TP layouts, (iii) an eagerly initialized Communicator Pool to amortize collective setup, and (iv) a deadlock-free scheduler that coordinates safe transitions under execution skew. Across three popular LLMs and realistic serving scenarios, Flying Serving improves performance by up to 4.79 × under high load and 3.47 × under low load while supporting latency- and memory-driven requests.
Gao, Shouwei [ORNL]↗
IMS Rapid Response 2024 Summary Report: A Machine Learning Potential for the Periodic Table
Stockpile stewardship and nuclear waste remediation are inherently chemically complex, involving practically the full diversity of the periodic table, but existing methods are too expensive or not functional for a large diversity of atom types. Overall, the field of machine learning interatomic potentials (MLIPs) has advanced dramatically in 2024 with large high-accuracy datasets existing for bulk, surface, and organic chemical systems and new online leaderboards for diverse chemistry. To participate in, and bring LANL interests into this ecosystem, here, we have built upon existing technologies created by LANL to create a framework capable of creating machine learning interatomic potentials (MLIPs) for over 90 atom types. Our results have created a massively diverse coordination complex training dataset more than 3 times the size of existing datasets, parallelized MLIP training over multiple GPUs, enabling the training of an MLIP spanning the periodic table at 20 times the speed of prior training on 32 GPUs. These advances are substantial towards creation on foundational MLIPs for LANL-specific application areas.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Pilot climate data system user's guide
Instructions for using the Pilot Climate Data System (PCDS), an interactive, scientific data management system for locating, obtaining, manipulating, and displaying climate-research data are presented. The PCDS currently provides this supoort for approximately twenty data sets. Figures that illustrate the terminal displays which a user sees when he/she runs the PCDS and some examples of the output from this system are included. The capabilities which are described in detail allow a user to perform the following: (1) obtain comprehensive descriptions of a number of climate parameter data sets and the associated sensor measurements from which they were derived; (2) obtain detailed information about the temporal coverage and data volume of data sets which are readily accessible via the PCDS; (3) extract portions of a data set using criteria such as time range and geographic location, and output the data to tape, user terminal, system printer, or online disk files in a special data-set-independent format; (4) access and manipulate the data in these data-set-independent files, performing such functions as combining the data, subsetting the data, and averaging the data; and (5) create various graphical representations of the data stored in the data-set-independent files.
Reph, M. G.↗
The Navajo Learning Network and the NASA Life Sciences/AFOSR Infrastructure Development Project
The NSF-funded Navajo Learning Network project, with help from NASA Life Sciences and AFOSR, enabled Dine College to take a giant leap forward technologically - in a way that could never had been possible had these projects been managed separately. The combination of these and other efforts created a network of over 500 computers located at ten sites across the Navajo reservation. Additionally, the college was able to install a modern telephone system which shares network data, and purchase a new higher education management system. The NASA Life Sciences funds further allowed the college library system to go online and become available to the entire campus community. NSF, NASA and AFOSR are committed to improving minority access to higher education opportunities and promoting faculty development and undergraduate research through infrastructure support and development. This project has begun to address critical inequalities in access to science, mathematics, engineering and technology for Navajo students and educators. As a result, Navajo K-12 education has been bolstered and Dine College will therefore better prepare students to transfer successfully to four-year institutions. Due to the integration of the NSF and NASA/AFOSR components of the project, a unified project report is appropriate.
Source record↗
The NPG 7120.5A Electronic Review Process
The use of electronics to review a document is well within the technical realm of today's state-of-the-art workplace. File servers and web site interaction are common tools for many NASA employees. The electronic comment processing described here was developed for the NPG 7120.5A review to augment the existing NASA Online Directives Information System (NODIS). The NODIS system is NASA's official system for formal review, approval and storage of NASA Directives. The electronic review process worked so well that NASA and other agencies may want to consider it as one of our "best practices." It was participatory decision making at its very best, a process that attracted dozens of very good ideas to improve the document as well as the way we can be managing projects far more effectively. The revision of NPG 7120.5A has significant implications for the way all elements of the Agency accomplish program and project management. Therefore, the review of NPG 7120.5A was an Agencywide effort with high visibility, heavy participation and a short schedule. The level of involvement created interest in supplementing the formal NODIS system with a system to collect comments efficiently and to allow the Centers and Codes to review and consolidate their comments into the official system in a short period of time. In addition, the Program Management Council Working Group (PMCWG), responsible for the revision of the document and the disposition of official comments, needed an electronic system to manage the disposition of comments, obtain PMCWG consensus on each disposition, and coordinate the disposition with the appropriate Headquarters Code that had submitted the official comment. The combined NASA and contractor talents and resources provided a system that supplemented the NODIS system and its operating personnel to produce a thorough review and approval of NPG 7120.5A on April 3, 1998, 7.5 months from the start of the process. The original six-month schedule is indicated. All milestones occurred on time, except for completion of comment disposition, which required an additional 30 days. Approval of the document occurred sixteen days after completion of the "Purple Package."
McBrayer, Robert↗
Testing the Archivas Cluster (Arc) for Ozone Monitoring Instrument (OMI) Scientific Data Storage
The Ozone Monitoring Instrument (OMI) launched on NASA's Aura Spacecraft, the third of the major platforms of the EOS program on July 15,2004. In addition to the long term archive and distribution of the data from OM1 through the Goddard Earth Science Distributed Active Archive Center (GESDAAC), we are evaluating other archive mechanisms that can archive the data in a more immediately available method where it can be used for futher data production and analysis. In 2004, Archivas, Inc. was selected by NASA s Small Business Innovative Research (SBIR) program for the development of their Archivas Cluster (ArC) product. Arc is an online disk based system utilizing self-management and automation on a Linux cluster. Its goal is to produce a low cost solution coupled with the ease of management. The OM1 project is an application partner of the SBIR program, and has deployed a small cluster (5TB) based on the beta Archwas software. We performed extensive testing of the unit using production OM1 data since launch. In 2005, Archivas, Inc. was funded in SBIR Phase II for further development, which will include testing scalability with the deployment of a larger (35TB) cluster at Goddard. We plan to include Arc in the OM1 Team Leader Computing Facility (TLCF) hosting OM1 data for direct access and analysis by the OMI Science Team. This presentation will include a brief technical description of the Archivas Cluster, a summary of the SBIR Phase I beta testing results, and an overview of the OMI ground data processing architecture including its interaction with the Phase II Archivas Cluster and hosting of OMI data for the scientists.
Tilmes, Curt↗
4DoF Drift Free Navigation Using Inertial Cues and Optical Flow
In this paper, we describe a novel approach in fusing optical flow with inertial cues (3D acceleration and 3D angular velocities) in order to navigate a Micro Aerial Vehicle (MAV) drift free in 4DoF and metric velocity. Our approach only requires two consecutive images with a minimum of three feature matches. It does not require any (point) map nor any type of feature history. Thus it is an inherently failsafe approach that is immune to map and feature-track failures. With these minimal requirements we show in real experiments that the system is able to navigate drift free in all angles including yaw, in one metric position axis, and in 3D metric velocity. Furthermore, it is a power-on-and-go system able to online self-calibrate the inertial biases, the visual scale and the full 6DoF extrinsic transformation parameters between camera and IMU.
reconnissance↗
Enhancing NASA Earth Science Data Discovery from Scientific Publications
Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.
Irina V Gerasimov↗
Globe Teachers Guide and Photographic Data on the Web
The task of managing the GLOBE Online Teacher s Guide during this time period focused on transforming the technology behind the delivery system of this document. The web application transformed from a flat file retrieval system to a dynamic database access approach. The new methodology utilizes Java Server Pages (JSP) on the front-end and an Oracle relational database on the backend. This new approach allows users of the web site, mainly teachers, to access content efficiently by grade level and/or by investigation or educational concept area. Moreover, teachers can gain easier access to data sheets and lab and field guides. The new online guide also included updated content for all GLOBE protocols. The GLOBE web management team was given documentation for maintaining the new application. Instructions for modifying the JSP templates and managing database content were included in this document. It was delivered to the team by the end of October, 2003. The National Geophysical Data Center (NGDC) continued to manage the school study site photos on the GLOBE website. 333 study site photo images were added to the GLOBE database and posted on the web during this same time period for 64 schools. Documentation for processing study site photos was also delivered to the new GLOBE web management team. Lastly, assistance was provided in transferring reference applications such as the Cloud and LandSat quizzes and Earth Systems Online Poster from NGDC servers to GLOBE servers along with documentation for maintaining these applications.
Kowal, Dan↗
Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System
The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team is to develop and flight-test control systems that use neural network technology to optimize the performance of the aircraft under nominal conditions as well as stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to the baseline aerodynamic derivatives in flight. This set of open-loop flight tests was performed in preparation for a future phase of flights in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed a pitch frequency sweep and an automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. An examination of flight data shows that addition of the flight-identified aerodynamic derivative increments into the simulation improved the pitch handling qualities of the aircraft.
Williams, Peggy S.↗
Identifiability and characterization of transmon qutrits through Bayesian experimental design
Robust control of a quantum system is essential to utilize the current noisy quantum hardware to its full potential, such as quantum algorithms. To achieve such a goal, a systematic search for an optimal control for any given experiment is essential. The design of optimal control pulses requires accurate numerical models and, therefore, accurate characterization of the system parameters. We present an online Bayesian approach for quantum characterization of qutrit systems, which automatically and systematically identifies optimal experiments that provide maximum information on the system parameters, thereby greatly reducing the number of experiments that need to be performed on the quantum testbed. Unlike most characterization protocols that provide point-estimates of the parameters, the proposed approach is able to estimate their probability distribution. The applicability of the Bayesian experimental design technique was demonstrated on test problems, where each experiment was defined by a parameterized control pulse. In addition to this, we also present an approach for iterative pulse extension, which is robust under uncertainties in transition frequencies and coherence times, and shot noise, despite being initialized with wide uninformative priors. Furthermore, we provide a mathematical proof of the theoretical identifiability of the model parameters and present conditions on the quantum state under which the parameters are identifiable. The proof and conditions for identifiability are presented for both closed and open quantum systems using the Schrödinger equation and the Lindblad master equation, respectively.
97 MATHEMATICS AND COMPUTING↗
Web-based Decision Support System Tools: the Soil and Water Assessment Tool Online Visualization and Analyses (SWATOnline) and NASA Earth Observation Data Downloading and Reformatting Tool (NASAaccess)
The current influx of climate related information required scientists to communicate their findings to decision makers in governments, disaster preparedness organizations, and the general public. The Soil and Water Assessment Tool (SWAT) is a powerful modelling tool that allows scientists to simulate many of the physical processes involved in the water cycle. This article presents the design, methods and development efforts to overcome some of the limitations of the previously developed SWAT visualization software programs by creating a set of modular web applications that can be duplicated, customized, and run. Moreover, this article features a web application development tool for climate data retrieval. The NASAaccess fetches, extracts and reformats climate data from the National Aeronautics and Space Administration servers and outputs data compatible with hydrological models. This work has the potential to increase the SWAT's model impact on non-technically trained stakeholders and decision makers charged with water and climate management.
Tethys↗