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This fact sheet describes a grid-interactive efficient building technology that is undergoing field validation tests through DOE's National Labs. It summarizes the technology application (Synapse software from Kinetic Buildings) and the characteristics of the field validation site.
One major path for clearance of large amount of waste arising from the decommission of nuclear power plants is based on measurement with large clearance monitors (also known as free release measurement facilities). These devices utilize multi-detector plastic scintillator arrays (large clearance monitors can consist of up to 24 plastic scintillators) to offer both, extremely low minimum detectable activities (MDA) and short measurement times for waste packages weighing up to one metric ton. However, a major problem with these devices is to obtain nuclide specific efficiencies, especially for geometrically complex large waste packages. Normal procedure for estimating the efficiency is to device dummy waste packages and attach point sources with well-known activities to unfavourable positions in these packages. In accordance with this procedure, calibration factors can be derived in a radiological conservative way. Devising such test dummies is not always possible and the procedure is prone to generating large measurement uncertainties. In this publication, we propose a new method to derive calibration factors by means of the Los Alamos National Laboratory (LANL) simulation tool Monte Carlo N-Particle (MCNP) and a statistical-phenomenological model for the detector characterization. In a multi-step approach, first the detector response for a distribution of activity in a waste package is calculated and subsequently the detectors are mathematically characterized. Applying state of the art statistical and optimizing procedures, parameters for the detector response are derived in a self-consistent way. This also allows to rigorously propagate the uncertainties to the final calculated calibration factors according to the Guide to the Expression of Uncertainty in Measurement (GUM supplement 1). To validate the derived parameters for the detector characterization a minimally invasive experimental setup was devised and installed into the large clearance monitor. It consisted of an aluminum swivel arm which could position point sources to the relevant coordinates. The so collected measurement data not only allowed to investigate the precision of the calculated calibration factors, but also to probe the location of concentrated activity sources in the waste package. Furthermore, data on measurements with dummy waste packages were collected to test the reproducibility of well-known calibration factors. We present the software tool SIStec, which will provide an intuitive user-interface to generate and simulate waste package models and execute the above-mentioned method. Using SIStec, different scenarios for the distribution of activity in the waste package can be probed. This will also allow to optimize the clearance process on various levels. For example, measurement time for pre-measurements can be reduced in exchange for unfavourable calibration factors, which would still allow to meet the regulator limits for clearance. (authors)
Many Savannah River Site (SRS) liquid waste facility operations depend upon repetitive engineering calculations and operator actions. Although these calculations and actions are formalized in technical reports and paper procedures, they can still be vulnerable to data entry errors, calculation errors, equipment alignment errors, and occasional changes caused by different people performing these activities. Savannah River Remediation (SRR) is using computer automation to reduce these error precursors by standardizing repetitive calculations and by performing plant alignment checks for repetitive operation processes. Data entry can be automated, calculation methodologies can be standardized, and computers can check to see that predefined plant conditions exist before equipment operation. In addition to improving quality, the time required for these activities to generate technical reports, to perform independent reviews, and to perform equipment alignment checks can be significantly reduced. In the case of operator-performed calculations, error precursors involve distractions that can occur over a multi-page paper procedure, confusing displays and controls from equipment, mathematical errors, complacency, and unfamiliarity with the procedure among many others. Repetitive engineering calculations suffer from similar error precursors and are often compounded by high workloads, lack of proficiency, lack of standard methodology, mental shortcuts, and biases. Web-based computer applications can eliminate many of these precursors through standardization. Calculation methods are fixed, inputs are fixed, and computer checks can highlight potentially wrong inputs and outputs. Automated calculations are performed almost instantaneously once input is provided. Operators and engineers can spend more time focusing on the results than on the process to achieve the results. Similarly, when operators use repetitive procedures involving equipment manipulation, the same error precursors apply. Automated operation sequences and equipment checks can be programmed into the distributed control system to provide standard operating processes that reduce and eliminate error precursors. This paper describes how SRR incorporates Human Performance Improvement (HPI) principles when automating calculations and operation processes. Computer applications will be reviewed in detail, highlighting the software development life-cycle that includes requirements gathering, prototyping, design, development, testing, and implementation. (authors)
This document contains all relevant code and descriptions of working components of CCPDVANALYSIS software toolkit.
The Department of Energy (DOE) nuclear complex includes many hazardous and challenging environments that must be inspected remotely and routinely for structural integrity evaluation and long-term planning purposes. The H-Canyon Air Exhaust (HCAEX) Tunnel is an example of such an environment where a biannual inspection is currently performed. Presently inspections are performed by teleoperated robotic crawlers which provide low-res video feedback to the structural engineers. Advanced sensors: including Lidar and panospheric hi-res cameras have the potential to provide additional valuable data in future inspections. The primary goal of the sensor suite is to provide an internal 3D map of the HCAEX tunnel. Possible sensors were a stereo camera, a 3D Lidar, or a 2D Lidar that would need to be spun around. The issues with the stereo camera were that it does not have a large field-of-view and that its depth information was not nearly as accurate as even the baseline Lidars. The Hokuyo UTM-30LX-EW shown below provides a 270 deg. FOV with high accuracy and resolution while the largest FOV on a 3D Lidar is 40 deg. This was the reason a 2D Lidar was chosen over the 3D Lidar. Even though the 2D Lidar requires additional components and software to generate a 3D map, its FOV advantage is too great given that the HCAEX tunnel is a relatively confined space. Along with the Lidar, a camera sensor, IMU sensor, pan-tit unit, and on board computer needed to be identified. The two panospheric cameras allow for full 360 deg. FOV. The IMU will give data on the state of the robot inside the tunnel. The computer is used to gather and process data on board and to control the pan-tilt system. Mounts were designed and 3D printed to build the prototype of the sensor suite. It was designed to have the Lidar on top With its full FOV free while having the camera below and as close to together as possible while still leaving much of their FOV visible. The design also managed the cables such that they were unlikely to be damaged if in tension and so that they did not intrude much on the cameras vision. The sensor tree developed for the H-Canyon tunnel inspection project produces a large quantity of camera and Lidar data. a postprocessing pipeline was created to facilitate the analysis of these data. The pipeline follows the following routine: 1) Registration - Salient local features in subsequent scans are identified and used to align the scans With one another. This allows production of a single cohesive map of the tunnel. 2) Sensor Fusion - RGB camera data is 'painted' onto the depth data created by the Lidar. 3) Segmentation - Individual surfaces from within the scene are segmented out separately for individual analysis. 4) Degradation Analysis - Automatic mapping of local deviation from the plane in position or surface normal is performed, as is detection of exposed rebar using Lidar return intensity. 2) Obstacle Detection - Lidar data is also used in real time to detect obstacles in the environment. This could give feedback to the operator to successfully drive in the tunnel. 6) Graphic User Interface - a custom GUI was created to facilitate customer use of the system. The system provides real-time feedback from both the cameras and Lidar. The Lidar point-cloud data is also used for obstacle detection. As the Lidar spins, various algorithms are run to analyze the current 'slice' and obstacles in the environment are determined and registered on a cost-map. A Graphical User Interface (GUI) was developed to allow the user to easily command the crawler to set the rotational speed of the Lidar, perform a scan, and register and save the 3D generated cloud after a scan is done. For the good of the crawler, a critical aspect of the GUI design is to allow the user to cancel a scan any time after it is commanded and before it is saved. The sensor trees depth accuracy was evaluated in comparison to a high end commercial FARO Terrestrial Laser Scanner (TLS) with specifications for millimeter accuracy at distances above 10 m. For the purposes of these tests, the depth measurements produced by the TLS were taken as ground truth. Example test wall panels were scanned with the TLS and postprocessed with its proprietary software, and subsequently scanned with the sensor tree system. The two scans were manually aligned and for each point in the output cloud from the sensor tree, the distance to the nearest ground truth point in the FARO cloud was determined. 98.7% of all produced points were within the specified target range of 6 mm, with an average deviation of 1.75 mm. The test walls used have an overall in-wall depth variation of around 40 mm.
The Radiological Toolbox software developed by Oak Ridge National Laboratory (ORNL) for U. S. Nuclear Regulatory Commission (NRC) is designed to provide electronic access to the vast and varied data that underlies the field of radiation protection. These data represent physical, chemical, anatomical, physiological, and mathematical parameters detailed in various handbooks which a health physicist might consult while in his office. The initial motivation for the software was to serve the needs of the health physicist away from his office and without access to his handbooks; e.g., NRC inspectors. The earlier releases of the software were widely used and accepted around the world by not only practicing health physicist but also those within educational programs. This release updates the software to accommodate changes in Windows operating systems and, in some aspects, radiation protection. This release has been tested on Windows 7 and 8 and on 32- and 64-bit machines. The nuclear decay data has been updated and thermal neutron capture cross sections and cancer risk coefficients have been included. This document and the software’s user’s guide provide further details and documentation of the information captured within the Radiological Toolbox.
The following report documents the final development, assembly, and initial testing of the gamma-ray emission tomography assessment system (GRETA-1) for post-irradiation examination of irradiated fuel. It includes descriptions of the system components, including the high-purity germanium gamma-ray detector, the surrounding shield and collimator, the sample scanning hardware, and the control and collection software package. A series of MCNP6 simulations were performed that modeled a fuel rod scan to test image reconstruction algorithms with a complex and understood source distribution. A bench-top scan of isotopic check sources was also performed and analyzed using standard image reconstruction algorithms. The system is currently awaiting deployment at Idaho National Laboratory’s Hot Fuel Examination Facility.
A high-voltage pulsed power supply (HVPPS) has been designed, prototyped, and tested for driving an eddy current actuated propellant valve for the International Thermonuclear Experimental Reactor (ITER) disruption mitigation system. The high-voltage (HV) dc supply output voltage is software programmable, and the energy storage capacitor bank can be readily reconfigured as 200, 400, 600, and 800 μ F, enabling testing and optimization of both the valve drive and valve systems. Multiple system parameters are monitored before, during, and after each firing of the valve. The system parameters are both displayed and stored for further analysis. Control of the setup, firing sequence, and data collection is automated using a LabVIEW-based control program. The programmability and reconfigurability of this system collectively provide a flexible and robust platform for system refinement and optimization. In this article, a summary of the system will be provided including operational sequences, HV switching and associated triggering methods and circuits, and results measured while firing a solid frozen pellet. Additionally, planned refinement activities toward meeting all requirements for ITER integration will be discussed.
has been widely accepted that software virtualization has a big negative impact on high-performance computing (HPC) application performance. This work explores the potential use of Infiniband hardware virtualization in an OpenNebula cloud towards the efficient support of MPI-based workloads. We have implemented, deployed, and tested an Infiniband network on the FermiCloud private Infrastructure-as-a-Service (IaaS) cloud. To avoid software virtualization towards minimizing the virtualization overhead, we employed a technique called Single Root Input/Output Virtualization (SRIOV). Our solution spanned modifications to the Linux’s Hypervisor as well as the OpenNebula manager. We evaluated the performance of the hardware virtualization on up to 56 virtual machines connected by up to 8 DDR Infiniband network links, with micro-benchmarks (latency and bandwidth) as well as w a MPI-intensive application (the HPL Linpack benchmark).
Network modeling is a powerful tool to enable rapid analysis of complex systems that can be challenging to study directly using physical testing. Here, two approaches are considered: emulation and simulation. The former runs real software on virtualized hardware, while the latter mimics the behavior of network components and their interactions in software. Although emulation provides an accurate representation of physical networks, this approach alone cannot guarantee the characterization of the system under realistic operative conditions. Operative conditions for physical networks are often characterized by intrinsic variability (payload size, packet latency, etc.) or a lack of precise knowledge regarding the network configuration (bandwidth, delays, etc.); therefore uncertainty quantification (UQ) strategies should be also employed. UQ strategies require multiple evaluations of the system with a number of evaluation instances that roughly increases with the problem dimensionality, i.e., the number of uncertain parameters. It follows that a typical UQ workflow for network modeling based on emulation can easily become unattainable due to its prohibitive computational cost. In this paper, a multifidelity sampling approach is discussed and applied to network modeling problems. The main idea is to optimally fuse information coming from simulations, which are a low-fidelity version of the emulation problem of interest, in order to decrease the estimator variance. By reducing the estimator variance in a sampling approach it is usually possible to obtain more reliable statistics and therefore a more reliable system characterization. Several network problems of increasing difficulty are presented. For each of them, the performance of the multifidelity estimator is compared with respect to the single fidelity counterpart, namely, Monte Carlo sampling. For all the test problems studied in this work, the multifidelity estimator demonstrated an increased efficiency with respect to MC.
This technical report describes testing to evaluate the gamma spectroscopy tool, Melusine, under development by Pacific Northwest National Laboratory. The goal was to verify that the software can successfully be used to provide accurate results and statistical uncertainties for the detection of isotopes of interest and their activities. Of special interest were spectra similar to those produced by radionuclide stations that contribute to the Comprehensive Nuclear Test Ban Treaty Organization’s International Monitoring System. Two data sets were used to test Melusine’s capabilities. The first was the result of a multi-lab calibration effort based on neutron activations produced at the University of California at Davis. The second was taken from the Proficiency Test Exercises conducted by the CTBTO directly in 2005. In 37 of 42 cases, Melusine produced results in agreement with the best answer presently available, in most cases with calculated uncertainties comparable to or better than competing analyses. In fact, Melusine technically provided one more result than CTBTO’s PTE analyses that agreed with the “book answer” (Monte Carlo simulation). Despite these promising results, the Melusine software is still under development. Effort is especially needed to simplify its analysis process, improve stability, and provide user documentation. Some significant analysis tasks require further vetting, such as those to address summing effects. However, our test results indicate that Melusine’s calculations as presently implemented are sound and can be used to reliably analyze spectra from the CTBTO’s radionuclide stations.
The electricity system in California, from generation through loads, must be prepared for high renewable penetration and increased electrification of end uses while providing increased resilience and lower operating cost. California has an aggressive renewable portfolio standard that is complemented by world-leading greenhouse gas goals. The goal of this project was to evaluate methods of enabling fast demand response (DR) signaling to small loads for low-cost site enablement. We used OpenADR 2.0 to meet telemetry requirements for providing ancillary services, and we used a variety of low-cost devices coupled with open-source software to enable an end-to-end fast DR. The devices, architecture, implementation, and testing of the system is discussed in this report. We demonstrate that the emerging Internet of Things (IoT) and Smart Home movements provide an opportunity for diverse small loads to provide fast, low-cost demand response. We used Internet-connected lights, thermostats, load interruption devices, and water heaters to demonstrate an ecosystem of controllable devices. The system demonstrated is capable of providing fast load shed for between 20 dollars and $300 per kilowatt (kW) of available load. The wide range results from some loads may have very low cost but also very little shed capability (a 10 watt [W] LED light can only shed a maximum of 10 W) while some loads (e.g., water heaters or air conditioners) can shed several kilowatts but have a higher initial cost. These costs, however, compare well with other fast demand response costs, with typically are over $100/kilowatt of shed. We contend these loads are even more attractive than their price suggests because many of them will be installed for energy efficiency or non-energy benefits (e.g., improved lighting quality or controllability), and the ability to use them for fast DR is a secondary benefit. Therefore the cost of enabling them for DR may approach zero if a software-only solution can be deployed to enable fast DR after devices are installed for other reasons. We recommend that the DR research community continue to engage with the IoT community to encourage the use of documented and open development interfaces. A library of device drivers and machine-readable interface specifications would significantly reduce the burden on users or system integrators for deploying systems in large numbers of buildings in California.
As high performance computing technology progresses toward the progressively more extreme scales required to address critical computational problems of both national and global interest, power and cooling for these extreme scale systems is becoming a growing concern. A standardized methodology for testing system requirements under maximal system load and validating system environmental capability to meet those requirements is critical to maintaining system stability and minimizing power and cooling risks for high end data centers. Moreover, accurate testing permits the high end data center to avoid issues of under- or over-provisioning power and cooling capacity saving resources and mitigating hazards. Previous approaches to such testing have employed an ad hoc collection of tools, which have been anecdotally perceived to produce a heavy system load. In this report, we present SystemBurn, a software tool engineered to allow a system user to methodically create a maximal system load on large scale systems for the purposes of testing and validation.
As high performance computing technology progresses toward the progressively more extreme scales required to address critical computational problems of both national and global interest, power and cooling for these extreme scale systems is becoming a growing concern. A standardized methodology for testing system requirements under maximal system load and validating system environmental capability to meet those requirements is critical to maintaining system stability and minimizing power and cooling risks for high end data centers. Moreover, accurate testing permits the high end data center to avoid issues of under- or over-provisioning power and cooling capacity saving resources and mitigating hazards. Previous approaches to such testing have employed an ad hoc collection of tools, which have been anecdotally perceived to produce a heavy system load. In this report, we present SystemBurn, a software tool engineered to allow a system user to methodically create a maximal system load on large scale systems for the purposes of testing and validation.
This study investigates the potential of DUSTRAN, a dust dispersion modeling system developed by Pacific Northwest National Laboratory, to model the transport of sea salt aerosols (SSA). Results from DUSTRAN simulations run with historical meteorological data were compared against privately-measured chloride data at the near coastal Maine Yankee Nuclear Power Plant (NPP) and the Environmental Protection Agency-measured CASTNET data from Acadia National Park (NP). The comparisons have provided both encouragement as to the practical value of DUSTRAN’s CALPUFF model and suggestions for further software development opportunities. All modeled concentrations were within one order of magnitude of those measured and a few test cases showed excellent agreement between modeled and measured concentrations. However, there is a lack of consistency in discrepancy which may be due to inaccurate extrapolation of meteorological data, underlying model physics, and the source term. Future research will refine the software to better capture physical phenomena. Overall, results indicate that with parameter refinement, DUSTRAN has the potential to simulate atmospheric chloride transport from known sources to inland sites for the purpose of determining the corrosion susceptibility of various structures, systems, and components at the site.
The Spallation Neutron Source (SNS) has developed a vertical test area (VTA) for the testing and qualification of superconducting radio frequency cavities. The associated RF System successfully supported the initial commissioning of the VTA system and has been utilized for cavity testing at both 4 and 2 K. As operational experience was gained, improvements to the RF system were implemented to better utilize the dynamic range of the system, and software updates and additions were made to meet operational needs. The system continues to evolve as we gain better understanding of the testing needs.
The general objective of our project has been to investigate the ability of Independent Distribution System Operators (IDSOs), functioning as linkage agents for Integrated Transmission and Distribution (ITD) systems, to facilitate the flexible availability and usage of reserve in support of ITD system operations. This general objective is in accordance with Order 2222 of the U.S. Federal Energy Regulatory Commission (FERC), titled “Participation of Distributed Energy Resource Aggregations in Markets Operated by Regional Transmission Organizations and Independent System Operators”. The Final Rule for FERC Order 2222 was issued on September 17, 2020. The primary contribution of our project is that we have formulated an innovative energy management Transactive Energy Design (TES) approach for ITD systems that provides promising support for our project objective. Specifically, we have developed a new type of IDSO-managed TES design for distribution system operations, as well as new types of swing contracts permitting IDSOs to participate in transmission system operations as providers of reserve harnessed from distribution system resources in return for appropriate compensation. Together, these design elements constitute a scalable market-based approach facilitating efficient reserve procurement for ITD system operations from a fuller range of power resources. The efficacy of our approach has been demonstrated by means of detailed conceptual analyses as well as test case simulations. To implement the latter, we have developed the ITD TES Platform V2.0, a computational platform that permits the modeling and software implementation of ITD system operations over time. The Electric Reliability Council of Texas (ERCOT) energy region has been used as the empirical anchor for the development of this platform. Our conceptual and test-case work has been reported in a Wiley/IEEE Press book, two refereed book chapters, and seven refereed journal articles. The key components comprising the ITD TES Platform V2.0 have been released as documented open-source software at online GitHub repositories.
Combining the stress factors of the natural environment into a single test for photovoltaic modules requires fewer modules, fewer parallel tests, and makes it possible to discover potential weaknesses that are not known textbfa priori in new module designs. In this work, we present the necessary textbfhardware and textbfsoftware capabilities for developing, implementing, and performing Combined-Accelerated Stress Testing (C-AST) protocols for photovoltaic modules, using off-the-shelf equipment and accessible software development tools, with the aim of supporting the development of C-AST capabilities by the photovoltaic community.