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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Robust control of a family of uncertain nonminimum‐phase systems via continuous‐time and sampled‐data output feedback

Summary The problem of global robust stabilization is studied by both continuous‐time and sampled‐data output feedback for a family of nonminimum‐phase nonlinear systems with uncertainty. The uncertain nonlinear system considered in this paper has an interconnect structure consisting of a driving system and a possibly unstable zero dynamics with uncertainty, ie, the uncertain driven system. Under a linear growth condition on the uncertain zero dynamics and a Lipschitz condition on the driving system, we show that it is possible to globally robustly stabilize the family of uncertain nonminimum‐phase systems by a single continuous‐time or a sampled‐data output feedback controller. The sampled‐data output feedback controller is designed by using the emulated versions of a continuous‐time observer and a state feedback controller, ie, by holding the input/output signals constant over each sampling interval. The design of either continuous‐time or sampled‐data output compensator uses only the information of the nominal system of the uncertain controlled plant. In the case of sampled‐data control, global robust stability of the hybrid closed‐loop system with uncertainty is established by means of a feedback domination method together with the robustness of the nominal closed‐loop system if the sampling time is small enough.

Lin, Wei↗
DOE OSTI2024

SRNL High and Low Activity Residue Characterization System Phase II [Poster]

The characterization system contains data sampled from 1996 to 2024 and can display any desired combination of 45 different isotopes. This system is intended to be used to quickly access historical data, generate trends for accurate future projections, and evaluate relevant unit conversion calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Object discrimination based on a swarm of agents

A configuration system for identifying a target configuration of agents for acquiring data is provided. In some embodiments, the configuration system generates sample configurations, each of which has a location within the space for each agent. The configuration system selects as the target configuration a sample configuration that is suitable to acquire data. The configuration system selects the target configuration by, for at least one or more sample configurations, directing that the agents assume the sample configuration and then acquire data when in the sample configuration. The configuration system then stores, for each sample configuration, an indication of suitability for acquiring data based on the sample configuration. The configuration system selects a sample configuration that is deemed to be suitable as the target configuration.

Beer, N. Reginald↗
DOE OSTI2021

Object discrimination based on a swarm of agents

A configuration system for identifying a target configuration of agents for acquiring data is provided. In some embodiments, the configuration system generates sample configurations, each of which has a location within the space for each agent. The configuration system selects as the target configuration a sample configuration that is suitable to acquire data. The configuration system selects the target configuration by, for at least one or more sample configurations, directing that the agents assume the sample configuration and then acquire data when in the sample configuration. The configuration system then stores, for each sample configuration, an indication of suitability for acquiring data based on the sample configuration. The configuration system selects a sample configuration that is deemed to be suitable as the target configuration.

Beer, Neil Reginald↗
DOE OSTI2024

The Data Acquisition System for Phase-III of the BeEST Experiment

The BeEST experiment is a precision laboratory search for physics beyond the standard model that measures the electron capture decay of 7 Be implanted into superconducting tunnel junction (STJ) detectors. For Phase-III of the experiment, we constructed a continuously sampling data acquisition system to extract pulse shape and timing information from 16 STJ pixels offline. Four additional pixels are read out with a fast list-mode digitizer, and one with a nuclear MCA already used in the earlier limit-setting phases of the experiment. Here, we present the performance of the data acquisition system and discuss the relative advantages of the different digitizers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Malicious activity detection in a memory

A method and apparatus for monitoring a volatile memory in a computer system. Samples of compressed data from locations in the volatile memory in the computer system are read. Data in the volatile memory is reconstructed using the samples of compressed data. The data is an image of the volatile memory. The image enables determining whether an undesired process is present in the volatile memory.

Wheeler, Jason W.↗
DOE OSTI2025

Amplitude analysis of ψ3686→γKS0KS0

Using (2712 ± 14) × 106ψ(3686) events collected with the BESIII detector, we perform the first amplitude analysis of the radiative decay ψ3686→γKS0KS0$$ \psi (3686)\to \gamma {K}_S^0{K}_S^0 $$ within the mass region MKS0KS0<2.8$$ {M}_{K_S^0{K}_S^0}<2.8 $$ GeV/c2. Employing a one-channel K-matrix approach for the description of the dynamics of the KS0KS0$$ {K}_S^0{K}_S^0 $$ system, the data sample is well described with four poles for the f0-wave and three poles for the f2-wave. The determined pole positions are consistent with those of well-established resonance states. The observed f0 and f2 states are found to be in agreement with those produced in radiative J/ψ decays. The production behaviors of f0 and f2 poles in ψ3686→γKS0KS0$$ \psi (3686)\to \gamma {K}_S^0{K}_S^0 $$ are qualified with their residues and the converted branching fractions. By comparing with J/ψ→γKS0KS0$$ J/\psi \to \gamma {K}_S^0{K}_S^0 $$ decay, the ratios Bψ3686→γf0,2BJ/ψ→γf0,2$$ \frac{\mathcal{B}\left(\psi (3686)\to \gamma {f}_{0,2}\right)}{\mathcal{B}\left(J/\psi \to \gamma {f}_{0,2}\right)} $$ are determined, which provides crucial experimental inputs on the internal structure of the f0,2 states, especially their potential mixing with glueball components.

Ablikim, M↗
DOE OSTI2022

Learning the temporal evolution of multivariate densities via normalizing flows

In this work, we propose a method to learn multivariate probability distributions using sample path data from stochastic differential equations. Specifically, we consider temporally evolving probability distributions (e.g., those produced by integrating local or nonlocal Fokker–Planck equations). Here, we analyze this evolution through machine learning assisted construction of a time-dependent mapping that takes a reference distribution (say, a Gaussian) to each and every instance of our evolving distribution. If the reference distribution is the initial condition of a Fokker–Planck equation, what we learn is the time-T map of the corresponding solution. Specifically, the learned map is a multivariate normalizing flow that deforms the support of the reference density to the support of each and every density snapshot in time. We demonstrate that this approach can approximate probability density function evolutions in time from observed sampled data for systems driven by both Brownian and Lévy noise. We present examples with two- and three-dimensional, uni- and multimodal distributions to validate the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Replacing missing data between airborne SAR coherent image pairs

For synthetic aperture radar systems, missing data samples can cause severe image distortion. When multiple, coherent data collections exist and the missing data samples do not overlap between collections, there exists the possibility of replacing data samples between collections. For airborne radar, the known and unknown motion of the aircraft prevents direct data sample replacement to repair image features. Finally, this paper presents a method to calculate the necessary phase corrections to enable data sample replacement using only the collected radar data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Sampling synchronization through GPS signals

A method uses a distributed data acquisition system with multiple, physically unconnected, data acquisition units, that can be in wireless communication with a remote host, to timestamp measurement data with sub-microsecond time base accuracy of sampling clock relative to an absolute timeframe. A current absolute time is derived from messages received from a satellite radio beacon positioning system (GPS). Measurement data is sampled by each unit at a specified sampling rate. Using hardware logic, batches of sampled data are associated with corresponding timestamps representing the absolute time at which the data was sampled. Data and timestamps may be transmitted to the host. A time offset bias is compensated by comparing timestamps against a nominal time based on start time and nominal sampling rate. The sampling clock rate may be disciplined using time pulses from the GPS receiver. An initial start of data sampling by all units can also be synchronized.

Zhuge, James Q.↗
DOE OSTI2018

Development of a Data Acquisition System for Kinetic Inductance Detectors: Wide Dynamic Range and High Sampling Rate for Astronomical Observation

Microwave kinetic inductance detectors have a variety of potential applications in astronomical observations. We built a data acquisition system for kinetic inductance detectors combining a dedicated analog board and a commercially available digital board to meet the requirements of astronomical measurements, such as observation of the cosmic microwave background. This paper reports the status of the development of the data acquisition system. We have already achieved simultaneous readout through 120 channels using a direct down-conversion method to decode the signal. A variety of software has been developed and tested using the functionalities of the system and actual detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Electronic structure prediction of multi-million atom systems through uncertainty quantification enabled transfer learning

The ground state electron density — obtainable using Kohn-Sham Density Functional Theory (KS-DFT) simulations — contains a wealth of material information, making its prediction via machine learning (ML) models attractive. However, the computational expense of KS-DFT scales cubically with system size which tends to stymie training data generation, making it difficult to develop quantifiably accurate ML models that are applicable across many scales and system configurations. Here, we address this fundamental challenge by employing transfer learning to leverage the multi-scale nature of the training data, while comprehensively sampling system configurations using thermalization. Our ML models are less reliant on heuristics, and being based on Bayesian neural networks, enable uncertainty quantification. We show that our models incur significantly lower data generation costs while allowing confident — and when verifiable, accurate — predictions for a wide variety of bulk systems well beyond training, including systems with defects, different alloy compositions, and at multi-million-atom scales. Moreover, such predictions can be carried out using only modest computational resources.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Waveform processing using neural network algorithms on the front-end electronics

In a multi-channel radiation detector readout system, waveform sampling, digitization, and raw data transmission to the data acquisition system constitute a conventional processing chain. The deposited energy on the sensor is estimated by extracting peak amplitudes, area under pulse envelopes from the raw data, and starting times of signals or time of arrivals. However, such quantities can be estimated using machine learning algorithms on the front-end Application-Specific Integrated Circuits (ASICs), often termed as “edge computing”. Edge computation offers enormous benefits, especially when the analytical forms are not fully known or the registered waveform suffers from noise and imperfections of practical implementations. In this work, we aim to predict peak amplitude from a single waveform snippet whose rising and falling edges containing only 3 to 4 samples. We thoroughly studied two well-accepted neural network algorithms, Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) by varying their model sizes. Further, to better fit front-end electronics, neural network model reduction techniques, such as network pruning methods and variable-bit quantization approaches, were also studied. By combining pruning and quantization, our best performing model has the size of 1.5 KB, reduced from 16.6 KB of its full model counterpart. It can reach mean absolute error of 0.034 comparing to that of a naive baseline of 0.135. Such parameter-efficient and predictive neural network models established feasibility and practicality of their deployment on front-end ASICs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

IMG/M: integrated genome and metagenome comparative data analysis system

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support for examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review(ER) companion system (IMG/M ER: https://img.jgi.doe.gov/ mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Search for charmed baryons in the Λ c + η system and measurement of the branching fractions of Λ c ( 2880 ) + and Λ c ( 2940 ) + decaying to Λ c + η and p D 0 relative to Σ c ( 2455 ) π

We search for excited charmed baryons in the Λ c + η system using a data sample corresponding to an integrated luminosity of 980 fb − 1 . The data were collected by the Belle detector at the KEKB e + e − asymmetric-energy collider. No significant signals are found in the Λ c + η mass spectrum, including the known Λ c ( 2880 ) + and Λ c ( 2940 ) + . Clear Λ c ( 2880 ) + and Λ c ( 2940 ) + signals are observed in the p D 0 mass spectrum. We set upper limits at 90% credibility level on ratios of branching fractions of Λ c ( 2880 ) + and Λ c ( 2940 ) + decaying to Λ c + η relative to Σ c ( 2455 ) π of < 0.13 for the Λ c ( 2880 ) + and < 1.11 for the Λ c ( 2940 ) + . We measure ratios of branching fractions of Λ c ( 2880 ) + and Λ c ( 2940 ) + decaying to p D 0 relative to Σ c ( 2455 ) π of 0.75 ± 0.03 ( stat ) ± 0.07 ( syst ) for the Λ c ( 2880 ) + and 3.59 ± 0.21 ( stat ) ± 0.56 ( syst ) for the Λ c ( 2940 ) + . Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2023

Infant burn injuries related to water heating for powdered infant formula preparation

Guidance for preparing powdered infant formula (PIF) helps to ensure it meets the nutritional needs of infants and is safe to consume. Among safety concerns is Cronobacter sakazakii contamination which can lead to serious infections and death. PIF preparation guidance varies; there is a lack of consensus on whether there is a need to boil water to inactivate potential Cronobacter and for how long to let the water cool before reconstitution. We sought to quantify the burden of burn injuries among infants related to water heating for PIF preparation. Estimating this burden may help inform preparation recommendations. Burn injuries among infants <18 months of age were identified from 2017 to 2019 National Electronic Injury Surveillance System data collected from sampled hospital emergency departments. Injuries were classified as related to PIF water heating, potentially related to PIF water heating but with undetermined causation, related to other infant feeding aspects, or unrelated to infant formula or breast milk feeding. Unweighted case counts for each injury classification were determined. Across sampled emergency departments, 7 PIF water heating injuries were seen among the 44,395 injuries reported for infants <18 months. No reported PIF water heating injuries were fatal, but 3 required hospitalization. Another 238 injuries potentially related to PIF water heating but with undetermined causation were also seen. Preparation guidance should consider both the potential risk for Cronobacter infection and the potential risk for burns.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Synchronizing data from irregularly sampled sensors

A system and method include receiving a set of sampled measurements for each of multiple sensors, wherein the sampled measurements are at irregular intervals or different rates, re-sampling the sampled measurements of each of the multiple sensors at a higher rate than one of the sensor's set of sampled measurements, and synchronizing the sampled measurements of each of the multiple sensors.

47 OTHER INSTRUMENTATION↗