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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
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 OSTI2010

Global Radiological Source Sorting, Tracking, and Monitoring Project: Phase I Final Report

As a proof of concept tested in an operational context, the Global Radiological Source Sorting, Tracking, and Monitoring (GRadSSTraM) Project successfully demonstrated that radio frequency identification (RFID) and Web 2.0* technologies can be deployed to track controlled shipments between the United States and the European Union. Between November 2009 and May 2010, a total of 19 shipments were successfully shipped from Oak Ridge National Laboratory (ORNL) by the U.S. Postal Service (USPS) and tracked to their delivery at England's National Physical Laboratory (NPL) by the United Kingdom Royal Mail. However, the project can only be viewed as a qualified success as notable shortcomings were observed. Although the origin and terminus of all RFID-enabled shipments were recorded and no shipments were lost, not all the waypoints between ORNL and NPL were incorporated into the pilot. Given limited resources, the project team was able to install RFID listeners/actuators at three waypoints between the two endpoints. Although it is likely that all shipments followed the same route between ORNL and NPL, it cannot be determined beyond question that all 19 shipments were routed on identical itineraries past the same three waypoints. The pilot also raises the distinct possibility that unattended RFID tracking alone, without positive confirmation that a tagged item has been properly recorded by an RFID reader, does not meet a rigorous standard for shipping controlled items. Indeed, the proof of concept test strongly suggests that a multifaceted approach to tracking may be called for, including tracking methods that are capable of reading and accepting multiple inputs for individual items [e.g., carrier-provided tracking numbers, Universal Product Codes (UPCs), and RFID tags]. For controlled items, another apparent requirement is a confirmation feature, human or otherwise, which can certify that an item's RFID tag, UPC, or tracking number has been recorded.

42 ENGINEERING↗
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↗
DOE OSTI2015

Used Fuel Cask Identification through Neutron Profile

Currently, most spent fuel is stored near reactors. An interim consolidated fuel storage facility would receive fuel from multiple sites and store it in casks on site for decades. For successful operation of such a facility there is need for a way to restore continuity of knowledge if lost as well as a method that will indicate state of fuel inside the cask. Used nuclear fuel is identifiable by its radiation emission, both gamma and neutron. Neutron emission from fission products, multiplication from remaining fissile material, and the unique distribution of both in each cask produce a unique neutron signature. If two signatures taken at different times do not match, either changes within the fuel content or misidentification of a cask occurred. It was found that identification of cask loadings works well through the profile of emitted neutrons in simulated real casks. Even casks with similar overall neutron emission or average counts around the circumference can be distinguished from each other by analyzing the profile. In conclusion, (1) identification of unaltered casks through neutron signature profile is viable; (2) collecting the profile provides insight to the condition and intactness of the fuel stored inside the cask; and (3) the signature profile is stable over time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Sequential Bayesian Parameter Estimation of Stochastic Dynamic Load Models

In this paper we focus on the parameter estimation of dynamic load models with stochastic terms-in particular, load models where protection settings are uncertain, such as in aggregated air conditioning units. We show how the uncertainty in the aggregated protection characteristics can be formulated as a stochastic differential equation with process noise. We cast the parameter inversion within a Bayesian parameter estimation framework, and we present methods to include process noise. We demonstrate the benefits of considering stochasticity in the parameter estimation and the risks of ignoring it.

Bayesian Statistics↗