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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Trigger-DAQ and Slow Controls Systems in the Mu2e Experiment

The muon campus program at Fermilab includes the Mu2e experiment that will search for a charged-lepton flavor violating processes where a negative muon converts into an electron in the field of an aluminum nucleus, improving by four orders of magnitude the search sensitivity reached so far. Mu2e's Trigger and Data Acquisition System (TDAQ) uses otsdaq as its solution. Developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under the-hood, for event transfer, filtering, and processing. otsdaq is an online DAQ software suite with a focus on flexibility and scalability, while providing a multi-user, web-based, interface accessible through the Chrome or Firefox web browser. The detector Read Out Controller (ROC), from the tracker and calorimeter, stream out zero-suppressed data continuously to the Data Transfer Controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes froma Cosmic Ray Ve to System (CRV). A Detector Control System (DCS) for monitoring, controlling, alarming, and archiving has been developed using the Experimental Physics and Industrial Control System (EPICS) Open Source Platform. The DCS System has also been itegrated into otsdaq. The installation of the TDAQ and the DCS systems in the Mu2e building is planned for 2021-2022, and a prototype has been built at Fermilab's Feynman Computing Center. We report here on the developments and achievements of the integration of Mu2e's DCS system into the online otsdaq software.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Methods and systems for detection of man-in-the-middle attacks for SCADA communication networks and applications of same

A system for detecting MITM for SCADA communication networks includes secure substation-substation communication links for providing secure and reliable paths to exchange OT data between substations for OT data consistency check; a SIB in each substation for sampling CT and PT measurements to calculate voltage magnitude and phase angle thereof; a S&C server in each substation coupled to the SIB for receiving the voltage magnitude and phase angle from the SIB and obtaining a packet carrying active power flow in transmission lines between two substations and a time stamp; an IDS server placed in a SCADA center for collecting the packet of each substation sent by the S&C server; analyzing the received packet from every adjacent substation; inspecting the payload of the received packet; and triggering an intrusion alarm to a SCADA operator when the power flow is not the same as the payload of the packets.

McCann, Roy A.↗
DOE OSTI2020

Pilot Study for Determining HVAC Fault Prevalence from Fault Monitoring Data

HVAC faults in U.S. commercial buildings are estimated to waste 0.7 quads of energy annually and many companies have deployed software at scale for fault detection and diagnosis (FDD). Yet the lack of comprehensive published data on fault prevalence makes it difficult for researchers, software developers, and building operators to target the most important types of faults and accelerate the widespread deployment of this technology. A multi-lab effort is underway to quantify the prevalence of commercial building HVAC faults. This paper describes initial analysis conducted on over 2-years of FDD data from 12 campus buildings to inform the methodology and data collection strategy of the full study. The analysis found a large variability in fault prevalence across different buildings, pieces of equipment, and fault types, many duplicate fault alarms, and challenges in validating faults with secondary data sources such as manually entered work order data. This paper also discusses the requirements for a successful full study, which necessitates the acquisition of a large, diverse dataset, from buildings that vary in end-use, climate region, and installed FDD software platform, as well as robust validation data easily linked to the FDD data. It is especially important to perform this analysis on data from multiple FDD providers and building owners to ensure that the results are agnostic to the software methodology used and building-specific settings. Future work will present the results of the full study, which will contain data from several different partner organizations, spanning a large proportion of U.S. climate zones.

Newman, Sarah F.↗
DOE OSTI2022

Next-Generation Cobalt-Free Cathodes – A Prospective Solution to the Battery Industry's Cobalt Problem*

Lithium-ion batteries are over-reliant on cobalt-containing cathodes. Current projections estimate hundreds of millions of electric vehicles (EVs) will be on the road by 2050, and this ever-growing demand threatens to deplete global cobalt reserves at an alarming rate. Moreover, cobalt supply-chain issues have significantly increased cobalt prices throughout the last decade. As such, energy storage research and development need to reduce reliance on cobalt to meet ever-growing demands for lithium-ion batteries. This chapter summarizes the science/technology gaps and potential of numerous cobalt-free Li-ion cathodes, including layered, spinel, olivine, and disordered rocksalt systems. Despite the promising performance of these Co-free cathodes, scale-up and manufacturing bottlenecks associated with these materials must also be addressed to enable widespread adoption in commercial batteries. Overall, this review broadly highlights the enormous promise of “zero-cobalt” Li-ion batteries to enable sustainable production of EVs in the coming decades.

Muralidharan, Nitin↗
DOE OSTI2022

Study of Classifiers for U-235 Source Signatures Using Gamma Spectral Measurements

Signatures associated with low-level U-235 sources are studied from a classification analytics perspective, using NaI gamma-ray spectral measurements from detectors located at various distances from the source. Data sets collected at a shielded facility are utilized, wherein the source is introduced via a conduit into a formation of 21 NaI detectors deployed over 6 x 6 meters area in a formation of two concentric circles and one spiral. The activity levels in the spectral regions associated with potential U-235 signatures are estimated as counts at 1 second intervals, and are used as features to train classifiers for detecting the presence of the source. Eight different classifiers are trained and tested using the background and source measurements collected over multiple experimental runs. As expected, the classifier performance improved overall as measurements from the detectors closer to source are used, but also revealed unexpectedly low performance by two detectors that are identically produced and configured as others. Six of eight classifiers have an overall comparable performance, for example, three of them achieved zero training error and 99% detection at 4% false alarm rate for a detector located 1.3 meters away from the source. Also, larger training sets led to improved classification performance across all classifiers, and interestingly, the classifiers with the minimum training error did not necessarily achieve the highest classification performance on test data.

Rao, Nageswara↗
DOE OSTI2022

Evaluation of Oak Ridge National Laboratory Health Physics Research Reactor Operation Data for Critical Benchmark Creation [Abstract]

The Oak Ridge National Laboratory (ORNL) Health Physics Research Reactor (HPRR) was a research reactor designed and built at ORNL in 1961. The critical assembly was using a highly enriched uranium and molybdenum alloy as the fuel, and it could be operated in steady-state or burst modes. The reactor was used for about 25 years to produce a lot of publications related to dosimetry, radiobiology and radiation detectors testing before its decommissioning in 1987. In recent years, the idea of using legacy operation data from the to create a valuable critical accident alarm system shielding benchmark arose. Such a benchmark has been submitted to the International Criticality Safety Benchmark Experiment Project (ICSBEP) Technical Review Group for a potential inclusion in the 2022 version of the handbook. Another way to use the valuable data from the operation of the HPRR is to evaluate the feasibility of the creation of a subcritical or prompt supercritical benchmark for inclusion in the ICSBEP or the International Reactor Physics Experiments Evaluation Project (IRPhEP) handbooks. To initiate a burst, the HPRR had to be operated in a slightly subcritical state for a few minutes. Then, the insertion of the burst control rod would greatly increase the reactivity of the system and start the burst. No critical configuration of the HPRR critical assembly could be located. The only information available concerns stable subcritical and prompt supercritical states, found in a burst experiments’ logbook. In the recovered logbook pages, information about 8 different bursts is available. The information includes the rods positions before and during a burst, the recorded subcritical reactor period and reactivity, and the burst fission yield derived from the temperature elevation sulfur pellet irradiation analysis. By using the HPRR logbook information and the as-built drawings of the critical assembly, a highly detailed model of the HPRR was created with SCALE 6.2.4/KENO-VI. Eight KENO-VI models were created to replicate the sub-critical assembly configurations described in the eight bursts from the recovered logbook pages. KENO-VI calculates k eff and it can be linked to a reactivity value in cents by using the delayed neutron fraction B eff , also calculated by KENO-VI. KENO-VI can also be used to model the prompt super-critical configurations of the HPRR and to assess the similarity with the burst measurements by comparing the calculated k eff and the measured fission yields between each burst. Unfortunately, high uncertainty exist and the obtained discrepancies between experiments and calculation results are high, compromising the creation of a valuable critical benchmark from HPRR operation data. The reasons of the discrepancies and potential ways to solve them are explored.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

CAAS-3S Radiation Testing for Y-12 and UPF with Godiva-IV

The Y-12 National Security Complex and the Uranium Processing Facility (UPF) selected the Mirion CAAS-3S as the Criticality Accident Alarm System for UPF and for Y-12 facilities replacing their legacy CAAS as part of efforts to extend the facility lifespans. As part of this process, the CAAS-3S system was exposed to a high radiation dose and dose rate during reactor testing with the Godiva-IV fast burst reactor. The reactor testing was designed around preliminary analyses that determined Y-12 and UPF requirements, and simulations of the radiation field within the reactor facility were used to determine reactor operating parameters, CAAS equipment locations, and the design of a neutron shield wall. This paper presents the design and results of the testing, and discusses how the test results were interpreted by criticality safety engineers at Y-12 and UPF.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Automated cryogenic refilling system

An improved system and method for the automated refilling of cryogenic helium is provided. In one embodiment, the system includes a dewar in fluid communication with a liquid helium cryostat through a cryogen transfer line. A controller regulates operation of a three-way valve to pre-cool the transfer line and to cause gaseous helium to flow to the dewar and force liquid helium through the transfer line into the cryostat. The controller is coupled to the output of a cryogenic level sensor, such that the controller regulates the helium liquid level within the cryostat. During filling cycles, the dewar liquid level is also monitored by the cryogenic level sensor and an alarm sounds if the dewar liquid level is undesirably low. Between filling cycles, the controller is operable to ventilate the dewar through a solenoid vent valve in fixed time intervals to ensure the dewar pressure is sufficiently low so as to not bleed liquid helium into the cryostat.

Ruiz-Rodriguez, Mariano M.↗
DOE OSTI2021

HP in Cybersecurity: CyOTE

The U.S. Department of Energy’s (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER), through the Cybersecurity for the Operational Technology Environment (CyOTE) Program, worked with energy sector asset owners and operators (AOOs), partners, and Idaho National Laboratory (INL) to develop capabilities for AOOs to independently detect adversarial tactics, techniques, and procedures (TTPs) within their operational technology (OT) environments. Unlike the approach taken with commercial security solutions, CyOTE seeks to tie anomalies in cyber operations to a cyber-attack. By stringing together multiple techniques in the OT environment, AOOs can identify attack campaigns with ever decreasing impacts. The CyOTE methodology applies fundamental concepts of perception and comprehension to a universe of knowns and unknowns increasingly disaggregated into observables, anomalies, and triggering events. MITRE’s ATT&CK® Framework for Industrial Control Systems (ICS) is used as a common lexicon to identify a set of triggering events related to three Use Cases – Alarm Logs, Human-Machine Interface (HMI), and Remote Logins – which together account for 87 percent of the techniques commonly used by adversaries. The CyOTE methodology is also appropriate for OT-related anomalies perceived outside the three Use Cases, such as through the energy system itself.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Using High-Resolution NSRDB Data to Evaluate Cloud Mask Forecast from WRF-Solar EPS

Validating spatiotemporal distributions of cloud forecasts using numerical weather prediction (NWP) models is difficult as this requires high-quality cloud-property at significantly high spatial and temporal resolution over extended periods of time. Observations of cloud properties, such as cloud mask, cloud optical thickness, and cloud type, are vital for assessing the capability of NWP models to forecast various types of clouds. Using the National Solar Radiation Database (NSRDB), this research evaluates ensemble cloud-mask predictions from the WRF-Solar ensemble prediction system (WRF-Solar EPS). From the WRF-Solar EPS, day-ahead solar forecasts for the contiguous United States (CONUS) for 2018 are simulated. Given the NSRDB data is accessible at a resolution of 2 km, we can calculate the cloud fraction across the 9-km grid of WRF-Solar EPS. This allows us to spatially assess the cloud-mask forecasts using two methods against the high-resolution NSRDB: (a) considering all 2-km NSRDB clouds in the forecast domain (EMAll), and (b) using a minimum cloud fraction threshold of 50% to designate a pixel as cloudy (EMP50). The low-resolution cloud masks from WRF-Solar EPS are evaluated directly against the cloud-resolving scale gridded observations from NSRDB using EMAll. With EMP50, we presume that scenes with less than 50% cloud cover from the 2-km NSRDB are clear. Thus, this assessment approach allows for a fair comparison with WRF-Solar EPS resolved to a 9-km grid. A method of point-by-point verification is used to evaluate dichotomous (yes/no) cloud mask predictions against the NSRDB. For each pixel of model extent, cloud frequency and traditional metrics (e.g., probability of detection, false alarm rate, and hit rate, etc.) are computed and compared with satellite-derived data sets. Mismatched cloud frequency (MCF) is computed to measure the present capability of WRF-Solar EPS in representing various types of clouds, which are categorized using three levels of cloud top height (CTH) and cloud optical depth (COD) across entire CONUS. Preliminary results show that the WRF-Solar EPS provides MCF values ranging from 9% to 46%, 16% to 33%, and 8% to 27% for low-level, middle-level, and high-level clouds, respectively, for three CTHs. The model produces MCFs ranging from 27% to 46%, 13% to 34%, and 8% to 19% for thin, medium-thickness, and thick clouds, respectively, for three CODs. The presentation will include a detailed description of the current outcomes as well as potential future extensions. The evaluation approach established in this study is readily extensible to the evaluation of cloud predictions from different ensemble NWP models. In addition, the findings of the suggested evaluation technique aid in identifying model weaknesses and will ultimately lead to advances in WRF-Solar EPS's skill in predicting clouds and solar irradiance.

cloud mask forecast↗
DOE OSTI2023

Operational Focused Data Analytics for Optimizing Radiation Portal Monitor-Based Nuclear Smuggling Detection Systems at Global Ports of Entry

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence has deployed a fleet of radiation portal monitors (RPMs) across the world at global ports of entry including seaports, airports, and land border crossings. These RPMs are integrated into radiation detection systems (RDS) that also include fixed cameras, optical character recognition (OCR) systems, primary scanning systems (e.g., X-ray or gamma-ray), and secondary scanning systems (e.g., spectroscopic radiation portal monitors, portable radiation detection systems). The data from these sensing technologies is collected at the Central Alarm Station (CAS) where servers and computers reside to control and operate the system. Operators utilize the data collected by the CAS and declared cargo information to make decisions on how to respond to an alarm.This work explores the use of CAS-located data, looking at both the sensor data streams and operator inputs, to perform analysis which supports customs and border protection agencies to improve training capability and operational effectiveness. We focus on analyzing site level effectiveness and behavior by rolling up CAS-located data collected from individual occurrences. To-date, more than 15 sites (e.g., seaports, airports, border crossings) have been analyzed in this manner with the goal of understanding system operations to verify effectiveness and recommend potential improvements. This work first aims to provide background information on relevant CAS-located data sources and our current operational system analytics process including example results. After summarizing our current analytic techniques, we discuss how the future data analytics systems can provide key benefits to improving operational performance while minimizing the burden these detection systems place on operators.

Kuhn, Michael↗
DOE OSTI2020

WIPP Safety Significant Confinement Ventilation System (SSCVS) HEPA Filtration System - 20165

Construction and major equipment fabrication are underway for a new ventilation exhaust system at the Waste Isolation Pilot Plant (WIPP). The new system will provide continuous High Efficiency Particulate Air (HEPA) filtration of the exhaust from the WIPP underground while meeting the ventilation demands for expanded waste emplacement and mining operations over the next 40 years. The integrated system design provides for reducing the salt, clay and diesel particulates from the exhaust airflow from the mine, prior to full filtration using Nuclear Safety Significant HEPA filters. The SSCVS design and equipment provides for continuous HEPA filtration over a wide range of operating and environmental conditions. The new exhaust system connects to the existing underground exhaust shaft, and the exhaust air flows from the underground through Salt Reduction Units (SRUs) to protect the final filter banks from excessive moisture and rapid salt/dust buildup. Each of the six (6) SRUs consists of a demister to remove entrained moisture, a dry salt remover unit to filter approximately 90% of the entrained salt/dust, and an automated water treatment system to periodically clean the demisters and to remove salt from the SRU filters. At the maximum expected exhaust flowrate of 540,000 Cubic Feet per Minute (CFM) / 255 Cubic Meters per Second (m{sup 3}/s), five (5) salt removal units will be in operation with one unit in standby or maintenance. An in-line variable frequency drive booster fan will offset pressure losses through each SRU and reduce the relative humidity of the air exiting the SRUs. In the event of a high radiation alarm from the underground Continuous Air Monitors (CAMs), the SRUs will be automatically bypassed, which places the SRS and building outside of the Safety Significant confinement boundary. From the SRUs, the exhaust is directed to the HEPA filter banks located in the New Filter Building. The exhaust system is designed to provide continuous HEPA filtration prior to release to the exhaust stack. There are 22 HEPA filter banks rated at 27,000 CFM / 12.75 m{sup 3}/s each. Each filter bank has two stages of pre-filters and two stages of HEPA filters. The filtered air from each of the 22 filter banks discharges into a common concrete plenum, which is maintained under a negative pressure by the main exhaust fans. Six 1,000 HP variable frequency drive exhaust fans are provided on the south side of the plenum. At the maximum expected exhaust flow of 540,000 CFM, four exhaust fans and twenty filter banks will be in operation. The fans discharge vertically to a separate concrete exhaust plenum. The filtered exhaust is routed from the exhaust plenum to a 125-foot-tall exhaust stack via a 13-foot diameter duct. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Application of the ANSI/ANS-8.3-2022 Minimum Accident to Tube Vault Storage

In support of planned site activities, the existing basis for criticality safety in nuclear facilities is being revisited. One such technical basis is the demonstration of Criticality Accident Alarm System (CAAS) coverage in tube vaults at Y-12 National Security Complex. The configuration of the vaults places significant shielding between the source and the detector stations and is dissimilar to drum storage or other processes. This paper describes tube vault storage at Y-12, describes the basis for the application of the 2022 minimum accident for system design (MASD) to the analysis, and presents how the accident is implemented in the analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Development of A Hardware-In-the-Loop (HIL) Testbed for Cyber-Physical Security in Smart Buildings

As smart buildings move towards open communication technologies, providing access to the Building Automation System (BAS) through the building's intranet, or even remotely through the Internet, has become a common practice. However, BAS was historically developed as a closed environment and designed with limited cyber-security considerations. Thus, smart buildings are vulnerable to cyber-attacks with the increased accessibility. This study introduces the development and capability of a Hardware-in-the-Loop (HIT) testbed for testing and evaluating the cyber-physical security of typical BASs in smart buildings. The testbed consists of three subsystems: (1) a real-time HIL emulator simulating the behavior of a virtual building as well as the Heating, Ventilation, and Air Conditioning (HVAC) equipment via a dynamic simulation in Modelica; (2) a set of real HVAC controllers monitoring the virtual building operation and providing local control signals to control HVAC equipment in the HIL emulator; and (3) a BAS server along with a web-based service for users to fully access the schedule, setpoints, trends, alarms, and other control functions of the HVAC controllers remotely through the BACnet network. The server generates rule-based setpoints to local HVAC controllers. Based on these three subsystems, the HIL testbed supports attack/fault-free and attack/fault-injection experiments at various levels of the building system. The resulting test data can be used to inform the building community and support the cyber-physical security technology transfer to the building industry.

Li, Guowen↗
DOE OSTI2023

Control Systems Design for STS Accelerator

The Second Target Station (STS) Project will expand the capabilities of the existing Spallation Neutron Source (SNS), with a suite of neutron instruments optimized for long wavelengths. A new accelerator transport line will be built to deliver one out of four SNS pulses to the new target station. The Integrated Control Systems (ICS) will provide remote control, monitoring, OPI, alarms, and archivers for the accelerator systems, such as magnets power supply, vacuum devices, and beam instrumentation. The ICS will upgrade the existing Linac LLRF controls to allow independent operation of the FTS and STS and support different power levels of the FTS and STS proton beam. The ICS accelerator controls are in the phase of preliminary design for the control systems of magnet power supply, vacuum, LLRF, Timing, Machine protection system (MPS), and computing and machine network. The accelerator control systems build upon the existing SNS Machine Control systems, use the SNS standard hardware and EPICS software, and take full advantage of the performance gains delivered by the PPU Project at SNS.

Yan, Jay↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collectedunder structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore,their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distanceto the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensembleof trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fittingobserved in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inversephysical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of thesource strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations ofunderlying regression methods.

Rao, Nageswara↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collected under structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore, their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distance to the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensemble of trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fitting observed in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inverse physical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of the source strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations of underlying regression methods.

Rao, Nageswara↗
DOE OSTI2021

Persistent Acoustic Sensing for Monitoring A Reactor Facility - Oral Presentation

Measurements over the past few years, taking place within the Multi-Informatics for Nuclear Operations Scenarios (MINOS) project, show that infrasound and low-frequency acoustic monitoring can detect, and often quantify, activities that occur on-site at a large research reactor. Observable activities include: crane translation, lifting, and lowering; differentiation between loaded and unloaded crane operations; access door opening and closing; vehicle operations; and cooling tower fan operation. Advanced data analytic and spectral feature extraction methods can be used to interpret selected signatures to reach a deeper understanding of different reactor activities. These measurements are being conducted using a network of smartphones that continuously operate in conjunction with cloud-based architectures. A recent addition to the system is the development and deployment of a real-time, cloud-based analytic framework that supports near-real-time alarming which can facilitate tip-and-cue protocols. This paper will present recent research advances in this area including studies to explore the transferability of learned parameters from one smartphone to another, the detectability of events from multiple sensors at different locations simultaneously, and the feasibility of porting analytical tools directly to the smartphones to allow edge computing with optimized configurations.

42 ENGINEERING↗