Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Instrument optimization”

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.

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

At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
NASA NTRS2026

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, constraint programming, or manual planning. We present a scalable deep reinforcement learning framework developed and deployed for NASA’s Carruthers Geocorona Observatory mission. Our framework introduces a macro-action abstraction known as activity blocks coupled with dynamic action-masking to navigate the intractably large search space and strictly enforce complex power, thermal, and instrument constraints. The resulting architecture generates globally feasible schedules with overwhelming probability, establishes operational trust, and executes a full training cycle in under six hours, circumventing the need for policy robustness by enabling rapid, on-demand retraining. Further, resulting schedules outperform baseline heuristics in scheduled science quality. The deep reinforcement learning framework was deployed as the default operational scheduler for the Carruthers Geocorona Observatory mission from the outset of the mission, demonstrating that deep reinforcement learning can be trusted for real spacecraft operations under complex, evolving constraints.

Geocorona↗
DOE OSTI2024

Digital Twin Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derate while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1976

Analytical display design for flight tasks conducted under instrument meteorological conditions

Paramount to proper utilization of electronic displays is a method for determining pilot-centered display requirements. Display design should be viewed fundamentally as a guidance and control problem which has interactions with the designer's knowledge of human psychomotor activity. From this standpoint, reliable analytical models of human pilots as information processors and controllers can provide valuable insight into the display design process. A relatively straightforward, nearly algorithmic procedure for deriving model-based, pilot-centered display requirements was developed and is presented. The optimal or control theoretic pilot model serves as the backbone of the design methodology, which is specifically directed toward the synthesis of head-down, electronic, cockpit display formats. Some novel applications of the optimal pilot model are discussed. An analytical design example is offered which defines a format for the electronic display to be used in a UH-1H helicopter in a landing approach task involving longitudinal and lateral degrees of freedom.

Hess, R. A.↗
NASA NTRS1999

Development of a Portable, Ground-based Ozone Lidar Instrument for Tropospheric Ozone Research and Educational Training

The objective of this research project is to develop a portable, eye-safe, ground-based ozone lidar instrument specialized for ozone differential absorption lidar (DIAL) measurements in the troposphere. This research project directly supports the goal of NASA's Earth Science Enterprise to understand the distribution and budget of tropospheric ozone (objective 1.5 of the Earth Science Strategic Enterprise Plan, 1998-2002). It can participate in ground validation experiments for TES, a tropospheric ozone satellite mission due to be launched in 2002. It can also be utilized for correlative ground measurements in future GTE (Global Tropospheric Experiment) and space-based ozone lidar missions, such as ORACLE. Multiple ground-based ozone lidar systems would improve the data obtained through current ozone-sonde networks. This prototype instrument could to serve as the basic unit for these and other future monitoring projects requiring multi-instrument networks, such as that proposed for the Global Tropospheric Ozone Project (GTOP). GTOP is currently being formulated by a scientific panel of the International Global Atmospheric Chemistry Project to meet its goal to better understand the processes that control the global distribution of tropospheric ozone. In order for the lidar to be widely deployed in networks, it must be fairly easy to use and maintain as well as being cost-competitive with a ground station launching ozonesondes several times a day. A second 2-year grant to continue this effort with students participating in ground tests and system improvements has been awarded by the Office of Equal Employment Opportunities (OEOP). This project also supports existing NASA lidar missions through its development of advanced, compact lidar technology. Innovations in both transmitters and receivers have been made in this project. Finally, this system could be modified in the future to probe more deeply into the stratosphere. This could be accomplished by increasing the emitted energy or optimizing the wavelengths for this purpose. In addition to NASA, this system has applications to the EPA, NOAA, and the DOD. An AFOSR grant has been awarded based on the results of this effort to fund advanced transmitter development at medium (20-40 mJ) energies. A second proposal to the DOD with a letter of support from Air Force Research Laboratory, has been submitted to extend this uv laser technology to 100 mJ levels. Thus, this project has enabled students and faculty at Hampton University to begin to develop research efforts in support of the mission of the DOD. This instrument will be based at Hampton University (HU) to meet our educational goal to train students in lidar technology as well as atmospheric ozone data analysis and interpretation. It will be also available for off-site measurement campaigns and will serve as a test bed for further instrument development. Later development beyond this grant to extend the scientific usefulness of the instrument may include incorporation of an aerosol channel and upgrading the laser to make stratospheric ozone measurements. Seven undergraduates, three graduate students, and one postdoctoral. researcher (formerly an HU student) have been active participants in this research effort.

Chyba, Thomas↗
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↗
DOE OSTI2021

A fitting algorithm for optimizing ion implantation energies and fluences

In this work we describe a method to automatically generate an ion implantation recipe, a set of energies and fluences, to produce a desired defect density profile in a solid using the fewest required energies. We simulate defect density profiles for a range of ion energies, fit them with an appropriate function, and interpolate to yield defect density profiles at arbitrary ion energies. Given Ν energies, we then optimize a set of Ν energy-fluence pairs to match a given target defect density profile. Finally, we find the minimum Ν such that the error between the target defect density profile and the defect density profile generated by the Ν energy-fluence pairs is less than a given threshold. Inspired by quantum sensing applications with nitrogen-vacancy centers in diamond, we apply our technique to calculate optimal ion implantation recipes to create uniform-density 1 μm surface layers of 15 N or vacancies (using 4 He).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Incident beam optics optimization for the single crystal neutron diffractometer Pioneer with a polarized beam option

Pioneer, a next-generation single-crystal neutron diffractometer, is under development for Oak Ridge National Laboratory’s Second Target Station. Designed to address a wide range of scientific questions, Pioneer will deliver homogeneous neutron beams with customizable size and divergence and provide a polarized beam option. This article introduces its incident beam optics, highlighting the optimization methodology and the simulated performance. Pioneer will utilize a modified elliptical-straight guide for neutron transport and deploy slit packages and insertable apertures to control beam size and divergence. The optimized guide geometry matches the optimal-and-full-sample-illumination condition, and the beam control system effectively filters out unwanted neutrons while preserving the desired ones. In addition, we have found that polygon-approximated guides provide satisfactory transport efficiency and beam homogeneity, eliminating the need for truly curved guides. Further, to enhance neutronics performance and reduce cost, the coatings of supermirror elements are individually optimized to the lowest half-integer m-values that are sufficient to deliver the desired neutrons. After evaluating polarizing V-cavities and 3 He spin filters over the default polarized wavelength band of 1.2–5.5 Å, we selected a translatable multichannel polarizing V-cavity as the incident beam polarizer. Strategically placed at a location where the beam divergence is low and a large in-guide gap has negligible impact on transport efficiency, the optimized V-cavity achieves an average P 2 T of ~35%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Fundamental cosmology from ANDES precision spectroscopy

ABSTRACT Fundamental cosmology observations, such as the detection of the redshift drift and tests of the universality of physical laws, are key science and design drivers of the ArmazoNes high Dispersion Echelle Spectrograph (ANDES), an Extremely Large Telescope instrument. While separate forecasts for each of them have been reported, we have developed Fisher matrix based forecast tools combining both of these observables. We demonstrate the synergies between the two ANDES data sets, quantifying the improvements in cosmology and fundamental physics parameter constraints for two separate theoretical paradigms. We publicly release this forecast code, which is one of the tools for the optimization of the ANDES observing strategy.

Marques, C. M. J.↗
DOE OSTI2021

Offline Arterial Signal Timing Optimization for Closely Spaced Intersections

The stop-and-go driving behavior at a busy arterial causes a significant amount of fuel waste and emissions that could be reduced. For closely spaced intersections, the traditional bottom-up signal timing approach could fail under high volumes when the queues reach the upstream intersections. A well-coordinated arterial should manage the queue length to prevent the control from failing. Traditionally, coordination among signalized intersections for an arterial means finding the good offsets for each intersection. The control of the intersections along an arterial can also be coordinated by optimizing splits. Splits impact the capacity of an intersection. Similar to the highway, the capacity drop could cause growing queues. This work is based on the Virtual Phase-Link (VPL) model, a street traffic model designed for online traffic model predictive control, to obtain a top-down offline arterial signal timing. The VPL-based model can guarantee capacity consistency in intersections along an arterial. We, therefore, adopted the VPL-based model and developed an offline signal timing optimization approach. The proposed timing derived from the VPL-based offline signal timing optimization showed very good results in simulation. We also collected field experiment data, which demonstrated overall energy reductions and speed improvements on some sections of the study arterial.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Analysis of useful ion yield for the Mg dopant in GaN by quadrupole—SIMS

The authors present a quantitative secondary ion mass spectrometry (SIMS) analysis of the useful ion yield of magnesium dopant in a gallium nitride matrix. A quadrupole SIMS instrument was used to analyze an Mg-doped GaN sample grown by metal organic chemical vapor deposition. Oxygen (O2+) was used as the primary ion beam and its energy was varied in the range from 0.5 to 5 kV with and without oxygen flooding near the sample. The results of the analysis can be used to determine the primary beam energies for optimal magnesium sensitivity.

Senevirathna, M. K. Indika (ORCID:0000000243575029↗
DOE OSTI2021

Predictive Data Analytics Framework Using Advanced Test Reactor Acoustic Data

Although a nuclear reactor is a hostile environment for sensing and electrical communications, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure (AMI) has been installed at the Advanced Test Reactor (ATR) nozzle trench area to record acoustic signals that has the ability to capture different operating regime of the reactor. This AMI includes ATR in-pile structural components, coolant, acoustic receivers, primary coolant pumps (PCP) as signal sources, a data acquisition system, and signal-processing algorithms, enabling real-time. This report will discusses development of recursive Fast Fourier Transform approach to process in real-time acoustic signals, application of short time Fast Fourier Transform to the ATR brush data to understand the vibration level and to develop spectrograms for different primary coolant pump combinations. The combination of primary coolant pumps for normal and power axial locator mechanism of ATR are different and generates different signatures. These acoustic signatures were used to develop machine learning approaches to automatically classify different operating regimes. This lay the foundation for predictive analytic framework that can be leverage by ATR to optimize their operation and maintenance. The path forward involves continued engagement with ATR and expanded implementation of AMI and predictive framework at ATR and other facilities within INL and at other experimental reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference

Efficient machine learning implementations optimized for inference in hardware have wide-ranging benefits, depending on the application, from lower inference latency to higher data throughput and reduced energy consumption. Two popular techniques for reducing computation in neural networks are pruning, removing insignificant synapses, and quantization, reducing the precision of the calculations. In this work, we explore the interplay between pruning and quantization during the training of neural networks for ultra low latency applications targeting high energy physics use cases. Techniques developed for this study have potential applications across many other domains. We study various configurations of pruning during quantization-aware training, which we term quantization-aware pruning, and the effect of techniques like regularization, batch normalization, and different pruning schemes on performance, computational complexity, and information content metrics. We find that quantization-aware pruning yields more computationally efficient models than either pruning or quantization alone for our task. Further, quantization-aware pruning typically performs similar to or better in terms of computational efficiency compared to other neural architecture search techniques like Bayesian optimization. Surprisingly, while networks with different training configurations can have similar performance for the benchmark application, the information content in the network can vary significantly, affecting its generalizability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Improved Particle Heat Transfer by way of Bimodal Particle Distributions for High Temperature Solar Thermal Energy

High temperature solar thermal facilities are looking to increase operating temperatures through novel heat transfer media, one such being solid particles. These particles operating at high temperatures will require transferring their thermal energy into another working fluid like supercritical carbon dioxide which can be used in advanced power cycles. Achieving high heat transfer between the particles and supercritical carbon dioxide is essential to high efficiency and low-cost operation. Therefore, optimizing the thermal conductivity of these particles is one potential way to ensure high performance. Traditionally, unimodal particle distributions have been employed in high temperature particle solar power plants. However, ambient temperature testing of bimodal particle distributions has revealed a superior thermal conductivity when compared to its unimodal counterpart at the same temperature. This data was obtained by certified, off-the-shelf instruments that can effectively simulate the conditions a particle would be exposed to in a high temperature solar thermal system. Data obtained in this way suggests that the increased thermal conductively imputed by a bimodal particle distribution is significant at working temperatures in solar facilities. Furthermore, the thermal conductivity of these bimodal particle distributions peaks when the best combination of large and small particles is applied. At high temperatures, binary particle distributions are compared to monodispersed distributions of larger particles where heat transfer is more prolific due to the increased surface radiation. Various thermal conductivity, porosity and heat exchanger models are explored in conjunction with data acquired up to 700 C.

Stout, Dallin (ORCID:0009000294586091)↗
NASA NTRS1982

Design concept for an optimized earth radiation budget sensor

The Earth Radiation Budget Program has the objective to measure and model the terrestrial radiation budget and obtain a better understanding of the climate and its changes. A multisensor, multisatellite system with high and midinclination orbits will be needed for implementing this program. Various approaches for conducting sensing operations have been evaluated. The present investigation considers a method of sampling with a unique multidirectional array mosaic sensor to fulfill the requirements of earth radiation budget measurements. Previous and present generation earth radiation budget (ERB) satellite instruments are discussed, and attention is given to instrument design tradeoffs and the baseline instrument concept.

Carman, S. L.↗
NASA NTRS1992

Efficient Two-Dimensional-FFT Program

Program computes 64 X 64-point fast Fourier transform in less than 17 microseconds. Optimized 64 X 64 Point Two-Dimensional Fast Fourier Transform combines performance of real- and complex-valued one-dimensional fast Fourier transforms (FFT's) to execute two-dimensional FFT and coefficients of power spectrum. Coefficients used in many applications, including analyzing spectra, convolution, digital filtering, processing images, and compressing data. Source code written in C, 8086 Assembly, and Texas Instruments TMS320C30 Assembly languages.

Miko, J.↗
NASA NTRS1992

Lightning Imaging Sensor (LIS) for the Earth Observing System

Not only are scientific objectives and instrument characteristics given of a calibrated optical LIS for the EOS but also for the Tropical Rainfall Measuring Mission (TRMM) which was designed to acquire and study the distribution and variability of total lightning on a global basis. The LIS can be traced to a lightning mapper sensor planned for flight on the GOES meteorological satellites. The LIS consists of a staring imager optimized to detect and locate lightning. The LIS will detect and locate lightning with storm scale resolution (i.e., 5 to 10 km) over a large region of the Earth's surface along the orbital track of the satellite, mark the time of occurrence of the lightning, and measure the radiant energy. The LIS will have a nearly uniform 90 pct. detection efficiency within the area viewed by the sensor, and will detect intracloud and cloud-to-ground discharges during day and night conditions. Also, the LIS will monitor individual storms and storm systems long enough to obtain a measure of the lightning flashing rate when they are within the field of view of the LIS. The LIS attributes include low cost, low weight and power, low data rate, and important science. The LIS will study the hydrological cycle, general circulation and sea surface temperature variations, along with examinations of the electrical coupling of thunderstorms with the ionosphere and magnetosphere, and observations and modeling of the global electric circuit.

Christian, Hugh J.↗
NASA NTRS2013

Reconstruction of Orion Engineering Development Unit (EDU) Parachute Inflation Loads

The process of reconstructing inflation loads of Capsule Parachute Assembly System (CPAS) has been updated as the program transitioned to testing Engineering Development Unit (EDU) hardware. The equations used to reduce the test data have been re-derived based on the same physical assumptions made by simulations. Due to instrumentation challenges, individual parachute loads are determined from complementary accelerometer and load cell measurements. Cluster inflations are now simulated by modeling each parachute individually to better represent different inflation times and non-synchronous disreefing. The reconstruction procedure is tailored to either infinite mass or finite mass events based on measurable characteristics from the test data. Inflation parameters are determined from an automated optimization routine to reduce subjectivity. Infinite mass inflation parameters have been re-defined to avoid unrealistic interactions in Monte Carlo simulations. Sample cases demonstrate how best-fit inflation parameters are used to generate simulated drag areas and loads which favorably agree with test data.

Ray, Eric S.↗