Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “system identification”

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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Optimizing the Performance of Radionuclide Identification Software in the Hunt for Nuclear Security Threats

The Radionuclide Analysis Kit (RNAK), my team’s most recent nuclide identification software, is entering the testing phase. A question arises: will removing rare nuclides from the software’s library improve its overall performance? An affirmative response indicates fundamental errors in the software’s framework, while a negative response confirms the effectiveness of the software’s key machine learning algorithms. After thorough testing, I found that the performance of RNAK cannot be improved with the library choice effect, thus verifying the effectiveness of RNAK’s algorithms—multiple linear regression, Bayesian network using the Viterbi algorithm, and branch and bound search.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Signatures of Extended Storage of Used Nuclear Fuel Comprehensive Final Report

This report serves as a comprehensive overview of the Extended Storage of Used Nuclear Fuel work performed for the Material Protection, Accounting and Control Technologies campaign under the Department of Energy Office of Nuclear Energy. This paper describes a signature based on the source and fissile material distribution found within a population of used fuel assemblies combined with the neutron absorbers found within cask design that is unique to a specific cask with its specific arrangement of fuel. The paper describes all the steps used in producing and analyzing this signature from the beginning to the project end.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Signatures of Extended Storage of Used Nuclear Fuel in Casks

As the amount of used nuclear fuel continues to grow, more and more used nuclear fuel will be transferred to storage casks. A consolidated storage facility is currently in the planning stages for storing these casks, where at least 10,000 MTHM of fuel will be stored. This site will have potentially thousands of casks once it is operational. A facility this large presents new safeguards and nuclear material accounting concerns. A new signature based on the distribution of neutron sources and multiplication within casks was part of the Department of Energy Office of Nuclear Energy’s Material Protection, Account and Control Technologies (MPACT) campaign. Under this project we looked at fingerprinting each cask's neutron signature. Each cask has a unique set of fuel, with a unique spread of initial enrichment, burnup, cooling time, and power history. The unique set of fuel creates a unique signature of neutron intensity based on the arrangement of the assemblies. The unique arrangement of neutron sources and multiplication produces a reliable and unique identification of the cask that has been shown to be relatively constant over long time periods. The work presented here could be used to restore from a loss of continuity of knowledge at the storage site. This presentation will show the steps used to simulate and form this signature from the start of the effort through its conclusion in September 2016.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Test Plan for Cask Identification Detector

This document serves to outline the testing of a Used Fuel Cask Identification Detector (CID) currently being designed under the DOE-NE MPACT Campaign. A bench-scale prototype detector will be constructed and tested using surrogate neutron sources. The testing will serve to inform the design of the full detector that is to be used as a way of fingerprinting used fuel storage casks based on the neutron signature produced by the used fuel inside the cask.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Ducted Assembly Steady-State Heat Transfer Software (DASSH)

The Ducted Assembly Steady-State Heat transfer software (DASSH) is being developed at Argonne National Laboratory to perform a steady-state thermal fluids calculation to determine the coolant flow and temperature distribution for a hexagonal reactor core configuration with ducted assemblies. DASSH is intended to be used in the early stages of the reactor design process when assembly components can be undefined or are undergoing considerable design changes. DASSH provides a rapid assessment of the temperature and flow distribution to allow quick characterization of the system and identification of problem areas. This document is a guide for DASSH users. It summarizes the core capabilities of DASSH and highlights differences between DASSH and SE2-ANL. Instructions for obtaining and installing DASSH are provided along with some guidelines and recommendations for newer Python users. It covers the structure of the input file, provides directions for running DASSH, describes the various output files produced by the code, and provides instructions for visualizing data. Examples demonstrating various DASSH options are included. DASSH is under active development, so it is anticipated that this guide will grow and evolve as the code is updated.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Formal Experimentation and Analysis of Handheld RFID Readers as a Tool for Nuclear Material Accounting

Commercial, off-the-shelf Radio Frequency Identification (RFID) systems have been successfully deployed for inventory tracking in numerous industries, but their viability in the tracking of complex environments containing nuclear material is less understood. Of primary interest in this setting is a RFID tracking system for nuclear material accounting which can reliably identify as many tags as possible with high accuracy, while also reducing an operator’s exposure to radiation. In this work, we develop a formal statistical approach to identify relevant handheld RFID reader settings which optimize tagging performance. To achieve this goal, we design a full factorial split-plot experiment for a static shelf configuration scene with 50 randomly placed nuclear material containers affixed with RFID tags. We use Bayesian inference to fit a second-order response surface model which expresses the probability of a successful match for each container as a function of the experimental factors. Such effects are allowed to vary across individual containers and the containers’ population in its entirety to estimate overall effects. Uncertainties of estimates and predictions are quantified via their corresponding posterior distributions. Following extensive model checking and validation, the fitted model is used to identify experimental factors which maximize matching probabilities at both the container-level and for the full shelf configuration scene. We also analyze sensitivity of performance to relevant factors.

25 ENERGY STORAGE↗
DOE OSTI2025

Design, Optimization, and Control of a 100 kW Electric Traction Motor Meeting or Exceeding DOE 2025 Targets

The overall objective of the electric motor portion of the Electric Drives Technology consortium is to research, develop, and test electric motors for use in electric vehicle applications capable of a peak power greater than 100 kW, power density greater than or equal to 50 kW/l, and a cost less than 3.3 $/kW. To meet the electric traction motor power density and cost targets a number of approaches were pursued simultaneously throughout the course of this project which address all of the major volumetric power density variables. The specific research thrusts at the Illinois Institute of Technology (IIT) are the following: multiphysics design for increased power density through maximum utilization of active materials, synthesis of electric machine windings and PM flux barriers with controlled space harmonics, high slot fill windings for increased current loadings or efficiency, aggressive cooling strategies, and design studies and prototype construction of candidate electric machines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Optimal Adsorbents for Low-Cost Storage of Natural Gas and Hyd: Computational Identification, Experimental Demonstration, and System-Level Projection

This research program will develop best-in-class natural gas (NG) and hydrogen adsorbents based on metal-organic frameworks (MOFs). More specifically, high-throughput computational screening coupled to machine learning will be used to identify MOFs that simultaneously achieve high usable gravimetric and volumetric capacities for methane and hydrogen. The most promising materials pinpointed by computation will be synthesized and characterized experimentally. In addition, the final stage of the project will critically evaluate the use of methane as a model for NG and consider which structural features are most important in making a viable NG storage system.

03 NATURAL GAS↗
DOE OSTI2024

Privacy-Preserving Real-Time Action Detection in Intelligent Vehicles Using Federated Learning-Based Temporal Recurrent Network

This study introduces a privacy-preserving approach for the real-time action detection in intelligent vehicles using a federated learning (FL)-based temporal recurrent network (TRN). This approach enables edge devices to independently train models, enhancing data privacy and scalability by eliminating central data consolidation. Our FL-based TRN effectively captures temporal dependencies, anticipating future actions with high precision. Extensive testing on the Honda HDD and TVSeries datasets demonstrated robust performance in centralized and decentralized settings, with competitive mean average precision (mAP) scores. The experimental results highlighted that our FL-based TRN achieved an mAP of 40.0% in decentralized settings, closely matching the 40.1% in centralized configurations. Notably, the model excelled in detecting complex driving maneuvers, with mAPs of 80.7% for intersection passing and 78.1% for right turns. These outcomes affirm the model’s accuracy in action localization and identification. The system showed significant scalability and adaptability, maintaining robust performance across increased client device counts. The integration of a temporal decoder enabled predictions of future actions up to 2 s ahead, enhancing the responsiveness. Our research advances intelligent vehicle technology, promoting safety and efficiency while maintaining strict privacy standards.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Heat Transfer, Refrigeration and Heat Pumps

The Special Issue entitled “Heat Transfer, Refrigeration and heat Pumps” accepted papers covering a wide range of topics related to heat pumps, thermal energy storage, and low-Global Warming Potential (GWP) alternative refrigerants. Heat pumps play a vital role in providing space conditioning and water heating while utilizing the energy of the environment. Since heat pumps use renewable thermal energy from the environs to provide the desired utility, they contribute to the portfolio of technologies that mitigate carbon footprint. The heat pump may be considered a truly renewable technology if the electricity it uses comes entirely from a renewable source. More accurately, a heat pump is a “low carbon technology”. These perspectives make heat pumps an indispensable option for the future in order to reduce the nocuous human impact on the environment. More efficient heat pumping technologies are being developed for the residential, commercial, and industrial sectors of the economy. Another R&D thrust is heat pumps for cold climates. Hardware components, use of low-GWP refrigerants, and identification of systemic inefficiencies are active research areas. This article is a synopsis of the papers submitted to the Special Issue.

42 ENGINEERING↗
DOE OSTI2022

Motion tomography via occupation kernels

The goal of motion tomography is to recover a description of a vector flow field using measurements along the trajectory of a sensing unit. In this paper, we develop a predictor corrector algorithm designed to recover vector flow fields from trajectory data with the use of occupation kernels developed by Rosenfeld et al. [9,10]. Specifically, we use the occupation kernels as an adaptive basis; that is, the trajectories defining our occupation kernels are iteratively updated to improve the estimation in the next stage. Initial estimates are established, then under mild assumptions, such as relatively straight trajectories, convergence is proven using the Contraction Mapping Theorem. We then compare the developed method with the established method by Chang et al. [5] by defining a set of error metrics. Here, we found that for simulated data, where a ground truth is available, our method offers a marked improvement over [5]. For a real-world example, where ground truth is not available, our results are similar results to the established method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Optimal SCR Control Using Data-Driven Models

We present an optimal control solution for the urea injection for a heavy-duty diesel (HDD) selective catalytic reduction (SCR). The approach taken here is useful beyond SCR and could be applied to any system where a control strategy is desired and input-output data is available. For example, the strategy could also be used for the diesel oxidation catalyst (DOC) system. In this paper, we identify and validate a one-step ahead Kalman state-space estimator for downstream NOx using the bench reactor data of an SCR core sample. The test data was acquired using a 2010 Cummins 6.7L ISB production engine with a 2010 Cummins production aftertreatment system. We used a surrogate HDD federal test procedure (FTP), developed at Michigan Technological University (MTU), which simulates the representative transients of the standard FTP cycle, but has less engine speed/load points. The identified state-space model is then used to develop a tunable cost function that simultaneously minimizes NOx emissions and urea usage. The cost function is quadratic and univariate, thus the minimum can be computed analytically. We show the performance of the closed-loop controller in using a reduced-order discrete SCR simulator developed at MTU. Our experiments with the surrogate HDD-FTP data show that the strategy developed in this paper can be used to identify performance bounds for urea dose controllers.

diesel, emmissions, control, environment, modeling↗
NASA NTRS1969

Programmed schedule holds for improving launch vehicle holds

Baseline definition and system optimization are used for the analysis of programmed holds developed through prelaunch system analysis. Identification of design specifications for ground support equipment and maintenance concepts, and design specifications are used to describe the functional utilization of the overall flow process.

Gralow, F. H.↗