Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Automated Testing”

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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Real-Time Ecodriving Control in Electrified Connected and Autonomous Vehicles Using Approximate Dynamic Programing

Connected and automated vehicles (CAVs), particularly those with a hybrid electric powertrain, have the potential to significantly improve vehicle energy savings in real-world driving conditions. In particular, the ecodriving problem seeks to design optimal speed and power usage profiles based on available information from connectivity and advanced mapping features to minimize the fuel consumption over an itinerary. This paper presents a hierarchical multilayer model predictive control (MPC) approach for improving the fuel economy of a 48 V mild-hybrid powertrain in a connected vehicle environment. Approximate dynamic programing (DP) is used to solve the receding horizon optimal control problem, whose terminal cost is approximated with the base policy obtained from the long-term optimization. The controller was tested virtually (with deterministic and Monte Carlo simulation) across multiple real-world routes, demonstrating energy savings of more than 20%. The controller was then deployed on a test vehicle equipped with a rapid prototyping embedded controller. In-vehicle testing confirm the energy savings obtained in simulation and demonstrate the real-time ability of the controller.

Automation & Control Systems↗
DOE OSTI2018

Advanced SOFC quality control and the role of manufacturing defects on stack reliability

Atrex Energy rolled out first commercial SOFC generator products in 2013. Following that we embarked on implementation of mass production in order to ramp up productivity and lower the costs in the meantime. To ensure the goal of mass production, an accurate, cost effective and consistent quality control methodology needs to be in place. The aim of this DOE funded project is to devise a machine and methodology for cell quality control using modern non-destructive testing methods and cell rejection criterion based on the empirical determination of the role of manufacturing flaws on stack degradation and reliability. The work scope encompasses two goals aimed at 1) developing automatable techniques for objective flaw detection and 2) developing an understanding of the ramifications of flaws on stack and cell reliability. By accomplishing these two goals it is likely that an advanced stage Quality Control (QC) device can be developed. This project scope encompasses: 1) Invention of a high speed automated instrument for spatial mapping of surface and sub-surface imperfections in production cells (ex situ) using modern imaging techniques. 2) Identification of rejection criteria upon which to screen cells from production by: a. Magnification of the effect of production defects on cell degradation through fabrication and testing of micro-cells which encompass these imperfections. b. The long term testing of full size production cells both as single cells and in small stacks, in order to correlate the (in situ) performance and degradation with the imperfection type (identified ex-situ) and hence be able to classify imperfections as actual defects. We first built a defect library with the cells containing imperfections classified and documented. The cells with various imperfections were tested to evaluate the imperfection potential impact on cell electrochemical performance. Evaluations were conducted on minicell, single cell and stack levels. On minicell level, pinhole, scratch, crack, contamination, and pop-out were investigated. We found: (1) none of the imperfections causes calamity type failure, (2) pinholes do not show measurable effect on minicell performance, (3) imperfection such as electrolyte abrasion, scratch, and pop out cause minicell potential to fluctuate by different degrees; the cells with such imperfections exhibit sensitivity of potential to high fuel utilization and “self healing” behavior. On single cell level we evaluated the effect of long crack and high population pinholes. The cell with a long crack does not show performance compromise at start. There is no potential fluctuation or sensitivity to high fuel utilization or catastrophic failure. The voltage degradation due to thermal cycle is slightly higher than normal cells. The cells with high population pinholes perform surprisingly as well as normal cells over a period of 3,500h. Even when subjected to cyclic load condition, the cells 4 show negligible degradation. Our cells appear to have “self immunization” feature which fends off the adversary effects of certain imperfections. Defects were also evaluated on stack level. Two stacks were made each with ten defect cells. The first stack was tested for 13,2000h under steady load condition while the second was tested for 9,000h under transient load conditions. We found: (1) voltage fluctuation and sensitivity to thermal cycle were not observed in contrast to minicell test, (2) of the various cracks examined, including longitudinal cracks, circumferential crack, crack near closed and open ends, none exhibited distinguishable impact on performance, (3) defect cells exhibited higher degradation rates on average under steady load condition; Individually some defect cells performed similarly or better than reference cells, (4) under steady load condition all the cells degrade monotonically with degradation rate increasing with time, (5) under cyclic (transient) load condition, both defect and reference cells exhibit complex dynamic behaviors, (6) fuel loss (leak) was measured occasionally for stack 1, the cells with crack showed the highest fuel loss increase, nevertheless, no correlation with performance degradation could be established with certainty, and (7) no catastrophic failure ever happened other than incremental degradation. Posttest inspection and microanalysis were carried out; the observations are summarized in what follows: (1) Electrolyte pinholes, some scratches and IC porosity became undetectable after testing. (2) The cathode covering the popout defects is intact without any cracking or delamination. (3) The scratch was covered by cathode in pristine state; Ni oxide or NiO-YSZ filled the space where electrolyte was missing. After >10,000h operation, the cathode that used to cover the scratch was missing but the size of the scratch remains unchanged; there is a fairly dense Ni oxide layer on top of the scratch. (4) All of the cracks remain their original dimensions. Current collector kept longitudinal cracks closed which mitigated the adversary effect of crack on cell performance/durability. (5) The crack at open end showed some deterioration manifested by a small oxidation zone in the vicinity of the crack. Wide spectrum of imaging techniques were surveyed and evaluated to detect tubular SOFC defects. Optical methods, with and without assistance of expression technique, were applied to detect all kinds of defects. Thermograph method in combination of CO2 leak, ultra-sound and electric potential was also extensively evaluated to detect surface and under-surface defects such as short circuit. Based on these works, laser camera has been selected to build the final QC machine vision inspection system. The Gocator laser profile sensor was setup to generate 2D surface intensity images of tubular SOFC surface which were analyzed with Sherlock machine vision software supplied by Teledyne Dalsa. The Gocator output was integrated with the Sherlock software and enabled live images to be imported by a Common Vision Blox driver. The Sherlock software was programmed to detect various surface defects from the surface intensity images generated by the Gocator. These measurements are subsequently used to make pass or fail decisions.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

redMaGiC: Selecting luminous red galaxies from the DES Science Verification data

Here, we introduce redMaGiC, an automated algorithm for selecting luminous red galaxies (LRGs). The algorithm was specifically developed to minimize photometric redshift uncertainties in photometric large-scale structure studies. redMaGiC achieves this by self-training the colour cuts necessary to produce a luminosity-thresholded LRG sample of constant comoving density. We demonstrate that redMaGiC photo-zs are very nearly as accurate as the best machine learning-based methods, yet they require minimal spectroscopic training, do not suffer from extrapolation biases, and are very nearly Gaussian. We apply our algorithm to Dark Energy Survey (DES) Science Verification (SV) data to produce a redMaGiC catalogue sampling the redshift range z ϵ [0.2, 0.8]. Our fiducial sample has a comoving space density of 10 –3 (h –1 Mpc) –3 , and a median photo-z bias (zspec – zphoto) and scatter (σz/(1 + z)) of 0.005 and 0.017, respectively. The corresponding 5σ outlier fraction is 1.4 per cent. We also test our algorithm with Sloan Digital Sky Survey Data Release 8 and Stripe 82 data, and discuss how spectroscopic training can be used to control photo-z biases at the 0.1 per cent level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Investigating the Impact of Connected Vehicle Market Share on the Performance of Reinforcement-Learning Based Traffic Signal Control

We aim to understand and explore the performance of reinforcement learning based signal control algorithms in a mixed environment with less than 100% market share of connected and automated vehicles (CAVs). Within a simulation environment, we have considered partial connectivity—less than 100% market share of CAVs—in the network and investigated the impact on the performance of the signal control algorithm. Two test networks including a four-intersection arterial in Lankershim Boulevard, CA, and a portion of downtown Springfield, IL, with 20 intersections. The first network is calibrated in the micro-simulator PTV Vissim with the US DOT provided NGSIM datasets. The results provide insights regarding the impact of the connectivity and sensing technologies on the practical implementation of traffic signal control algorithms that leverage the data sharing capability of a connected environment. For scenarios with 40% or more market share of CAVs, we observed improvement in the performance metrics—travel time, queue time, and energy consumption—with the increase in market share. Results from our experiments do not indicate any clear trend when the networks have low (less than 40%) market share of CAVs. The higher standard deviations as obtained from the statistical analyses of the performance metrics at low market share may indicate the instability of the RL controller arising from the partial (if not zero) observability of the traffic states. Further, we have conducted simplified scenario analyses to explore the impact of the market share of battery electric vehicles (BEVs) on energy consumption due to the regenerative braking feature. Our results and findings will be the foundation for the future reinforcement learning based control algorithm development that accounts for partial connectivity—less than 100% CAV market share, and the presence of BEVs in a network of connected and automated signalized intersections.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Design and Development of a Robotic Exoskeleton Device for use in Glove Boxes - 20374

Glovebox operators in nuclear facilities often operate under radioactive environment and typically perform monotonous, dull and repetitive work. This can result in muscle fatigue leading to increased levels of accidents. Current research work aims in assisting the glovebox operators by designing a novel upper limb exoskeleton device to reduce injuries and increase worker efficiency. Almost none of the commercially available hand and upper body exoskeletons are directly suitable for use in gloveboxes. This explains the novelty of the present work in developing a wearable powered robotic exoskeleton device. The device consists of electronics, motors and spring systems mounted on adjustable plates and is supported by a stationary frame behind the worker. The device is intended to be portable and adjustable according to the operator height. The elbow has a flexion movement assisted with motor control by way of a Bowden cable system. The system is floated on a spring and pulley combination that allows for extra safety and smoothness of operation. The end points are fixed near the pivot points to help minimize unwanted movement/torque. The extension movement of the upper and lower arm are assisted by gravity and a counter spring. The shoulder and upper arm movement are held in a neutral position with a spring system for counter balance allowing small movements within the glovebox. This initial concept considers only the vertical movement of the arm. The abduction and adduction movement will not be assisted or impeded by the over shoulder plate or at the forearm plate allowing for full range of motion. Several glovebox aspects such as the level of task assistance, ergonomic design, minimum hindrance in dexterity/operator movements and tear resistance for hazardous safety reasons will be considered in the design of the exoskeleton. Computer models will be simulated to test the load levels and stress conditions on the exoskeleton to enhance the designs. The exoskeleton focusses on major muscular involvement reduction through weight offset and active assistance with minimal parts and hence the device is derived with several joint links and contains both passive and active joints. The paper details the various stages in the design development and prototype testing of the exoskeleton device. Upon successful prototype device development, human testing will be conducted in a replica of the SRS-235F hot cell facility constructed at FIU-ARC. The final stage of the project will be potential testing/deployment of the exoskeleton device in one of the glovebox facilities in Savannah River Nuclear Waste site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Truck Platooning Performance with ADAS and Onboard Camera Data Describing Traffic Interactions

This project was part of the Characterizing Behaviors and Capabilities for Emerging Connected and Automated Vehicle Technologies, Sensors, and Connectivity project. The National Laboratory of the Rockies partnered with Cummins Inc. to collect data from Class 8 tractor trailer combinations in platoon (cooperative adaptive cruise control) operations on public roads in southern Indiana. Data collected include J1939 CAN bus, radar, intervehicle position, and video data. The video data could not be shared in the raw form, so they were processed to extract information on the other vehicles on the road, their relative positions, and intrusion events. This information was then columnized for modeling use and further enhanced by appending road information including road type, speed limit, altitude, and grade. The test route included free-flowing traffic, highway interchanges, and construction zones, as well as low-, medium-, and high-grade sections. Individual test conditions varied by day, with advanced driver-assistance system (ADAS) features engaged or disengaged and different combined vehicle masses tested in addition to uncontrolled variables such as weather and traffic interactions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Improving the Fuel Economy of Class 8 Military Vehicles using a Smart Cruise Control Algorithm

Connected and Automated Vehicles (CAVS) have the potential for improving fuel economy by changing the way vehicles are driven. Fuel economy can be improved through a wide range of technologies, many of which do not require Level 5 automation. One of the most promising technologies is a smart cruise control for which a speed-matching algorithm can be designed to account for fuel economy. Accounting for fuel economy in the algorithm leads to different driving behavior than simply matching the driver entered set speed. This paper describes the application of such a smart cruise control to a class 8 vehicle both in simulation and in the actual vehicle on a close test track. This paper evaluates the algorithm and describes the correlation procedure used to calibrate the model using test data from the vehicle.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Detection of regional infrasound signals using array data: Testing, tuning, and physical interpretation

This work quantifies the physical characteristics of infrasound signal and noise, assesses their temporal variations, and determines the degree to which these effects can be predicted by time-varying atmospheric models to estimate array and network performance. An automated detector that accounts for both correlated and uncorrelated noise is applied to infrasound data from three seismo-acoustic arrays in South Korea (BRDAR, CHNAR, and KSGAR), cooperatively operated by Korea Institute of Geoscience and Mineral Resources (KIGAM) and Southern Methodist University (SMU). Arrays located on an island and near the coast have higher noise power, consistent with both higher wind speeds and seasonably variable ocean wave contributions. On the basis of the adaptive F-detector quantification of time variable environmental effects, the time-dependent scaling variable is shown to be dependent on both weather conditions and local site effects. Significant seasonal variations in infrasound detections including daily time of occurrence, detection numbers, and phase velocity/azimuth estimates are documented. These time-dependent effects are strongly correlated with atmospheric winds and temperatures and are predicted by available atmospheric specifications. As a result, this suggests that commonly available atmospheric specifications can be used to predict both station and network detection performance, and an appropriate forward model improves location capabilities as a function of time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Automated nuclear cloud feature extraction from film

Chemical, biological, radiological, nuclear, and explosives incidents require rapid detection and characterization for appropriate response. For a nuclear detonation, visible-light cameras may be used to locate the cloud and characterize fallout deposition when coupled with numerical models. Films from the United States’ nuclear testing era compose the only sizeable collection of imagery depicting high-yield detonations. These films offer unique insights into characteristics of flows involving scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models for nuclear fallout transport, either as part of emergency response or forensic activities. In this work, we implement modern computer vision and machine learning techniques to identify and track the cloud automatically and subsequently determine the time dependence of some of its features. We trained a ResNet-18 image classifier on hundreds of images to categorize nuclear cloud morphology. Each category or cloud regime is determined by early cloud evolution and is associated to constitutive properties of the flow, such as distribution of vorticity. Next, we identified keypoint features using the KAZE algorithm and tracked these keypoints in the images, allowing us to determine the dimensions and velocities of the cloud across film frames. These measurements converted to real-world units provide valuable experimental data that can be used in the development and validation of nuclear cloud models. We compared the results of this method against manual cloud rise measurements from two different films. In one, our automated method accelerated the feature extraction process without sacrificing measurement accuracy.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗
DOE OSTI2018

Fission Meter Information Barrier Attribute Measurement System - NA-243 FNI/UKC FY2017 Task 1-2 Report

An SNM attribute Information Barrier (IB) system was developed for a 2011 US/UK Exercise. The system was modified and extensively tested in a 2013-2014 US-UK Measurement Campaign. This work demonstrated rapid deployment of an IB system for potential treaty use. The system utilizes an Ortec Fission Meter neutron multiplicity counter and custom computer code. The system demonstrates a proof-of-principle automated Pu-240 mass determination with an information barrier. After a software start command is issued, the system automatically acquires and downloads data, performs an analysis, and displays the results. This system conveys the results of a Pu mass threshold measurements in a way the does not reveal sensitive information. In full IB mode, only the pass/fail result is displayed as a “Mass <= Threshold Amount” or “Mass >= Threshold Amount” as shown in Figure 4. This can easily be adapted to a red/green “lights” display similar to the Detective IB system for Pu isotopics as shown in Figure 6. In test mode, more detailed information is displayed. The code can also read in, analyze, and display results from previously acquired or simulated data. Because the equipment is commercial-off-the-shelf (COTS), the system demonstrates a low-cost short-lead-time technology for treaty SNM attribute measurements. A deployed system will likely require integration of additional authentication and tamper-indicating technologies. This will be discussed for the project in this and future progress reports.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

ELECTRONIC STRUCTURE METHODS AND PROTOCOLS WITH APPLICATION TO DYNAMICS, KINETICS AND THERMOCHEMISTRY

Hydrocarbon combustion involves the reaction dynamics of a tremendous number of species beginning with many-component fuel mixtures and proceeding via a complex system of intermediates to form primary and secondary products. Combustion conditions corresponding to new advanced engines and/or alternative fuels rely increasingly on autoignition and low-temperature-combustion chemistry. In these regimes various transient radical species such as HO2, ROO·, ·QOOH, HCO, NO2, HOCO, and Criegee intermediates play important roles in determining the detailed as well as more general dynamics. A clear understanding and accurate representation of these processes is needed for effective modeling. Given the difficulties associated with making reliable experimental measurements of these systems, computation can play an important role in developing these energy technologies. Accurate calculations have their own challenges since even within the simplest dynamical approximations such as transition state theory, the rates depend exponentially on critical barrier heights and these may be sensitive to the level of quantum chemistry. Moreover, it is well-known that in many cases it is necessary to go beyond statistical theories and consider the dynamics. Quantum tunneling, resonances, radiative transitions, and non-adiabatic effects governed by spin-orbit or derivative coupling can be determining factors in those dynamics. Building upon progress made during a period of prior support through the DOE Early Career Program, this project combines developments in the areas of potential energy surface (PES) fitting and multistate multireference quantum chemistry to allow spectroscopically and dynamically/kinetically accurate investigations of key molecular systems (such as those mentioned above), many of which are radicals with strong multireference character and have the possibility of multiple electronic states contributing to the observed dynamics. An ongoing area of investigation is to develop general strategies for robustly convergent electronic structure theory for global multichannel reactive surfaces including diabatization of energy and other relevant surfaces such as dipole transition. Combining advances in ab initio methods with automated interpolative PES fitting allows the construction of high-quality PESs (incorporating thousands of high-level data) to be done rapidly through parallel processing on high-performance computing (HPC) clusters. In addition, new methods and approaches to electronic structure theory will be developed and tested through applications. This project will explore limitations in traditional multireference calculations (e.g., MRCI) such as those imposed by internal contraction, lack of high-order correlation treatment and poor scaling. Methods such as DMRG-based extended active-space CASSCF and various Quantum Monte Carlo (QMC) methods will be applied (including VMC/DMC and FCIQMC). Insight into the relative significance of different orbital spaces and the robustness of application of these approaches on leadership class computing architectures will be gained. Synergy with other components of this research program such as automated PES fitting and multireference quantum chemistry will be used to address challenges encountered by the standard approaches to computational thermochemistry (those being single-reference quantum chemistry and perturbative treatments of the anharmonic vibrational energy, which break down for some cases of electronic structure or floppy strongly coupled vibrational modes).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Guiding the choice of informatics software and tools for lipidomics research applications

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

SU-E-T-254: Development of a HDR-BT QA Tool for Verification of Source Position with Oncentra Applicator Modeling

Purpose: To develop a High Dose Rate Brachytherapy (HDR-BT) quality assurance (QA) tool for verification of source position with Oncentra applicator modeling, and to report the results of radiation source positions with this tool. Methods: We developed a HDR-BT QA phantom and automated analysis software for verification of source position with Oncentra applicator modeling for the Fletcher applicator used in the MicroSelectron HDR system. This tool is intended for end-to-end tests that mimic the clinical 3D image-guided brachytherapy (3D-IGBT) workflow. The phantom is a 30x30x3 cm cuboid phantom with radiopaque markers, which are inserted into the phantom to evaluate applicator tips and reference source positions; positions are laterally shifted 10 mm from the applicator axis. The markers are lead-based and scatter radiation to expose the films. Gafchromic RTQA2 films are placed on the applicators. The phantom includes spaces to embed the applicators. The source position is determined as the distance between the exposed source position and center position of two pairs of the first radiopaque markers. We generated a 3D-IGBT plan with applicator modeling. The first source position was 6 mm from the applicator tips, and the second source position was 10 mm from the first source position. Results: All source positions were consistent with the exposed positions within 1 mm for all Fletcher applicators using in-house software. Moreover, the distance between source positions was in good agreement with the reference distance. Applicator offset, determined as the distance from the applicator tips at the first source position in the treatment planning system, was accurate. Conclusion: Source position accuracy of applicator modeling used in 3D-IGBT was acceptable. This phantom and software will be useful as a HDR-BT QA tool for verification of source position with Oncentra applicator modeling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Rhythm

Rhythm is a small Python framework that automates Cadence Spectre simulations from the command line. Instead of creating an ADE testbench, you'll write a Rhythm Recipe, a short, readable Python script that contains each step needed to test your circuit from setting up libraries and stimulus waveforms to setting up analyses and reading the results (in Rhythm, these steps are called stages). Need to run more than one simulation? Use a Rhythm Campaign to easily sweep across corners and test conditions with a live dashboard and multithreading support.

Quinn, Adam [Fermi National Accelerator Laboratory↗
DOE OSTI2019

Real-Time Monitoring of Selenium Species in Power Plant Wastewaters via Optical Spectroscopy

Energy Research Company (ERCo) and Lehigh University are developing a new rapid sensor for measuring trace amounts of selenium in coal-fired power plant wastewater streams down to the single parts-per-billion (ppb) level. With EPA regulations pending on releases of selenium in wastewaters from power plants, plant operators are finding that commercially available technology is not suitable for ensuring compliance with the new regulations. These regulations require monitoring selenium at the single ppb level. There are several important advantages of our instrument as compared to other potential methods such as ICP-MS or ICP-OES. First, the method is rapid, allowing for analyses within minutes. Second, the method is amenable to automation, so dedicated lab personnel are not required. Third, the apparatus is compact and comprised of off-the-shelf components that are inexpensive compared to other laboratory instruments. Fourth, our instrument is designed to be used in the field and will collect data from any water source in near real time. Fifth, maintenance is minimal and finally, the cost is quite low. Furthermore, selective concentration of different ionization states of selenium was also demonstrated. Selenium is present in wastewaters in two main ionization states, +4 and +6. The fraction of each ionization state is important to know because it affects selenium treatment technologies. We were able to measure each one with a single instrument. The Phase II work plan will automate our instrument and expand the measurements to other heavy metals such as mercury and arsenic, the two other heavy metals covered in the new EPA regulations. We will also field test the instrument at an operating coal fired power plant.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Accomplishments of Sandia and Kitware CMake/CTest/CDash Contract for (FY2017-2020)

We describe the accomplishments jointly achieved by Kitware and Sandia over the fiscal years 2016 through 2020 to benefit the Advanced Scientific Computed (ASC) Advanced Technology Development and Mitigation (ATDM) project. As a result of our collaboration, we have improved the Trilinos and ATDM application developer experience by decreasing the time to build, making it easier to identify and resolve build and test defects, and addressing other issues . We have also reduced the turnaround time for continuous integration (CI) results. For example, the combined improvements likely cut the wall clock time to run automated builds of Trilinos posting to CDash by approximately 6x or more in many cases. We primarily achieved these benefits by contributing changes to the Kitware CMake/CTest/CDash suite of open source software development support tools. As a result, ASC developers can now spend more time improving code and less time chasing bugs. And, without this work, one can argue that the stabilization of Trilinos for the ATDM platforms would not have been feasible which would have had a large negative impact on an important internal FY20 L1 milestone.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Enabling a Physical Twin for Control Methods Evaluation

Advanced nuclear reactors play an important role in the energy future of the United States and the rest of the world. They are designed and operated based on a different model than that of the current operating fleet, thus enabling deployment in remote locations and allowing for safe semi-autonomous or autonomous operations. Such characteristics require the development of a new reactor control paradigm. A significant factor in the development of control technologies and methods is integration of the various technologies and methods with each other and with hardware (both reactor system hardware and control hardware). A recent workshop on control of advanced reactors identified the lack of a flexible, expandable software/hardware infrastructure to enable such integration as a key gap. A previous phase of the current effort involved developing and demonstrating the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) platform, which is capable of integrating autonomous-control-enabling technologies and methods, without the constraints imposed by existing software solutions. This platform will enable advanced reactor developers to deploy and test any developed technologies and methods by employing a common framework, and to couple them with their own models and hardware. The present phase of this effort entails using the Microreactor Automated Control System (MACS) platform, which was developed by the U.S. Department of Energy (DOE) Microreactor Program, to serve as a control method testbed. MACS can be used by advanced reactor developers to integrate their control related research activities with any reactor system. For the present effort, MACS was customized to mirror Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and COMMAND was leveraged to enable MACS to emulate the physics of MARVEL, thus positioning MACS as a physical twin of MARVEL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

When Data Analytics Meet Site Operation: Benefits and Challenges

Demand for using data analytics for energy management in buildings is rising. Such analytics are required for advanced measurement and verification, commissioning, automated fault-detection and diagnosis, and optimal control. While novel analytics algorithms continue to be developed, bottlenecks and challenges arise when deploying them for demonstration, for a number of reasons that do not necessarily have to do with the algorithms themselves. It is important for developers of new technologies to be aware of the challenges and potential solutions during demonstration. Therefore, this paper describes a recent deployment of an automated, physical model-based, FDD and optimal control tool, highlighting its design and as-operated benefits that the tool provides. Furthermore, the paper presents challenges faced during deployment and testing along with solutions used to overcome these challenges. The challenges have been grouped into four categories: Data Management, Physical Model Development and Integration, Software Development and Deployment, and Operator Use. The paper concludes by discussing how challenges with this project generalize to common cases, how they could compare to other projects in their severity, and how they may be addressed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗