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DOE OSTI2016

A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting

The National Center for Atmospheric Research (NCAR) is pleased to have led a partnership to advance the state-of-the-science of solar power forecasting by designing, developing, building, deploying, testing, and assessing the SunCast™ Solar Power Forecasting System. The project has included cutting edge research, testing in several geographically- and climatologically-diverse high penetration solar utilities and Independent System Operators (ISOs), and wide dissemination of the research results to raise the bar on solar power forecasting technology. The partners include three other national laboratories, six universities, and industry partners. This public-private-academic team has worked in concert to perform use-inspired research to advance solar power forecasting through cutting-edge research to advance both the necessary forecasting technologies and the metrics for evaluating them. The project has culminated in a year-long, full-scale demonstration of provide irradiance and power forecasts to utilities and ISOs to use in their operations. The project focused on providing elements of a value chain, beginning with the weather that causes a deviation from clear sky irradiance and progresses through monitoring and observations, modeling, forecasting, dissemination and communication of the forecasts, interpretation of the forecast, and through decision-making, which produces outcomes that have an economic value. The system has been evaluated using metrics developed specifically for this project, which has provided rich information on model and system performance. Research was accomplished on the very short range (0-6 hours) Nowcasting system as well as on the longer term (6-72 hour) forecasting system. The shortest range forecasts are based on observations in the field. The shortest range system, built by Brookhaven National Laboratory (BNL) and based on Total Sky Imagers (TSIs) is TSICast, which operates on the shortest time scale with a latency of only a few minutes and forecasts that currently go out to about 15 min. This project has facilitated research in improving the hardware and software so that the new high definition cameras deployed at multiple nearby locations allow discernment of the clouds at varying levels and advection according to the winds observed at those levels. Improvements over “smart persistence” are about 29% for even these very short forecasts. StatCast is based on pyranometer data measured at the site as well as concurrent meteorological observations and forecasts. StatCast is based on regime-dependent artificial intelligence forecasting techniques and has been shown to improve on “smart persistence” forecasts by 15-50%. A second category of short-range forecasting systems employ satellite imagery and use that information to discern clouds and their motion, allowing them to project the clouds, and the resulting blockage of irradiance, in time. CIRACast (the system produced by the Cooperative Institute for Atmospheric Research [CIRA] at Colorado State University) was already one of the more advanced cloud motion systems, which is the reason that team was brought to this project. During the project timeframe, the CIRA team was able to advance cloud shadowing, parallax removal, and implementation of better advecting winds at different altitudes. CIRACast shows generally a 25-40% improvement over Smart Persistence between sunrise and approximately 1600 UTC (Coordinated Universal Time) . A second satellite-based system, MADCast (Multi-sensor Advective Diffusive foreCast system), assimilates data from multiple satellite imagers and profilers to assimilate a fully three-dimensional picture of the cloud into the dynamic core of WRF. During 2015, MADCast (provided at least 70% improvement over Smart Persistence, with most of that skill being derived during partly cloudy conditions. That allows advection of the clouds via the Weather Research and Forecasting (WRF) model dynamics directly. After WRF-Solar™ showed initial success, it was also deployed in nowcasting mode with coarser runs out to 6 hours made hourly. It provided improvements on the order of 50-60% over Smart Persistence for forecasts up to 1600 UTC. The advantages of WRF-Solar-Nowcasting and MADCast were then blended to develop the new MAD-WRF model that incorporates the most important features of each of those models, both assimilating satellite cloud fields and using WRF-So far physics to develop and dissipate clouds. MAE improvements for MAD-WRF for forecasts from 3-6 hours are improved over WRF-Solar-Now by 20%. While all the Nowcasting system components by themselves provide improvement over Smart Persistence, the largest benefit is derived when they are smartly blended together by the Nowcasting Integrator to produce an integrated forecast. The development of WRF-Solar™ under this project has provided the first numerical weather prediction (NWP) model specifically designed to meet the needs of irradiance forecasting. The first augmentation improved the solar tracking algorithm to account for deviations associated with the eccentricity of the Earth’s orbit and the obliquity of the Earth. Second, WRF-Solar™ added the direct normal irradiance (DNI) and diffuse (DIF) components from the radiation parameterization to the model output. Third, efficient parameterizations were implemented to either interpolate the irradiance in between calls to the expensive radiative transfer parameterization, or to use a fast radiative transfer code that avoids computing three-dimensional heating rates but provides the surface irradiance. Fourth, a new parameterization was developed to improve the representation of absorption and scattering of radiation by aerosols (aerosol direct effect). A fifth advance is that the aerosols now interact with the cloud microphysics, altering the cloud evolution and radiative properties, an effect that has been traditionally only implemented in atmospheric computationally costly chemistry models. A sixth development accounts for the feedbacks that sub-grid scale clouds produce in shortwave irradiance as implemented in a shallow cumulus parameterization Finally, WRF-Solar™ also allows assimilation of infrared irradiances from satellites to determine the three dimensional cloud field, allowing for an improved initialization of the cloud field that increases the performance of short-range forecasts. We find that WRF-Solar™ can improve clear sky irradiance prediction by 15-80% over a standard version of WRF, depending on location and cloud conditions. In a formal comparison to the NAM baseline, WRF-Solar™ showed improvements in the Day-Ahead forecast of 22-42%. The SunCast™ system requires substantial software engineering to blend all of the new model components as well as existing publically available NWP model runs. To do this we use an expert system for the Nowcasting blender and the Dynamic Integrated foreCast (DICast®) system for the NWP models. These two systems are then blended, we use an empirical power conversion method to convert the irradiance predictions to power, then apply an analog ensemble (AnEn) approach to further tune the forecast as well as to estimate its uncertainty. The AnEn module decreased RMSE (root mean squared error) by 17% over the blended SunCast™ power forecasts and provided skill in the probabilistic forecast with a Brier Skill Score of 0.55. In addition, we have also developed a Gridded Atmospheric Forecast System (GRAFS) in parallel, leveraging cost share funds. An economic evaluation based on Production Cost Modeling in the Public Service Company of Colorado showed that the observed 50% improvement in forecast accuracy will save their customers $819,200 with the projected MW deployment for 2024. Using econometrics, NCAR has scaled this savings to a national level and shown that an annual expected savings for this 50% forecast error reduction ranges from $11M in 2015 to $43M expected in 2040 with increased solar deployment. This amounts to a $455M discounted savings over the 26 year period of analysis.

14 SOLAR ENERGY↗
DOE OSTI2021

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.

adjoint optimization↗
DOE OSTI2016

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models feature diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Virtual Microscope Views of the Apollo 11 and 12 Lunar Samples

The Apollo virtual microscope is a means of viewing, over the Internet, polished thin sections of every rock in the Apollo lunar sample collections via software, duplicating many of the functions of a petrological microscope, is described. Images from the Apollo 11 and 12 missions may be viewed at: www.virtualmicroscope.org/content/apollo. Introduction: During the six NASA missions to the Moon from 1969-72 a total of 382 kilograms of rocks and soils, often referred to as "the legacy of Apollo", were collected and returned to Earth. A unique collection of polished thin sections (PTSs) was made from over 400 rocks by the Lunar Sample Curatorial Facility at the Johnson Spacecraft Center (JSC), Houston. These materials have been available for loan to approved PIs but of course they can't be simultaneously investigated by several researchers unless they are co-located or the sample is passed back and forward between them by mail/hand carrying which is inefficient and very risky for irreplaceable material. When The Open University (OU), the world's largest Distance Learning Higher Education Establishment found itself facing a comparable problem (how to supply thousands of undergraduate students with an interactive petrological microscope and a personal set of thin sections), it decided to develop a software tool called the Virtual Microscope (VM). As a result it is now able to make the unique and precious collection of Apollo specimens universally available as a resource for concurrent study by anybody in the world's Earth and Planetary Sciences community. Herein, we describe the first steps of a collaborative project between OU and the Johnson Space Center (JSC) Curatorial Facility to record a PTS for every lunar rock, beginning with those collected by the Apollo 11 and 12 missions. Method: Production of a virtual microscope dedicated to a particular theme divides into four main parts - photography, image processing, building and assembly of virtual microscope components, and publication on a website. Two large research quality microscopes are used to collect all the images required for a virtual microscope. The first is part of an integrated package that utilizes Leica PowerMosaic software and a motorised XYZ stage to generate large area mosaics. It includes a fast acquisition camera and depending on the PTS size normally is used to produce seamless mosaic images consisting of 100-500 individual photographs. If the sample is suitable, three mosaics of each sample are recorded - plane polarised light, between crossed polars and reflected light. In order for the VM to be a true petrological microscope it is necessary to recreate the features of a rotating stage and perform observations using filters to produce polarised light. Thus the petrological VM includes the capability of seeing changes in optical properties (pleochroism and birefringence) during rotation allowing mineral identification. The second microscope in the system provides the functions of the rotating stage. To this microscope we have added a robotically controlled motor to acquire seventy-two images (5 degree intervals) in plane polarised light and between crossed polars. To process the images acquired from the two microscopes involves a combination of proprietary software (Photoshop) and our own in-house code. The final stage involves assembling all the components in an HTML5 environment. Pathfinder investigations: We have undertaken a number of pilot studies to demonstrate the efficacy of the petrological microscope with lunar samples. The first was to make available on-line images collected from the Educational Package of Apollo samples provided by NASA to the UK STFC (Science and Technical Facilities Council) for loan as educational material e.g. for schools. The real PTSs of the samples are now no longer sent out to schools removing the risks associated with transport, accidental breakage and eliminating the possibility of loss. The availability of lunar sample VM-related material was further extended to include twenty-eight specimens from all of the Apollo missions. Some of these samples were made more generally available through an ibook entitled "Moon Rocks: an introduction to the Geology of the Moon," free from the Apple Bookstore. Research possibilities: Although the Virtual Microscope was originally conceived as a teaching aid and was later recognised as a means of public outreach and engagement, we now realize that it also has enormous potential as a high level research tool. Following discussions with the JSC Curators we have received Curation and Analysis Planning Team for Extraterrestrial Materials (CAPTEM) permission to embark on a programme of digitizing the entire lunar sample PTS collection for all three of the above purposes. By the time of the 47th Lunar and Planetary Science Conference (LPSC) we will have completed 81 rocks collected during the Apollo 11 and 12 missions and the data, with cross-links to the Lunar Sample Compendium will go live on the Web at the 47th LPSC. The VM images of the Apollo 11 (41 VM images) and 12 (40 VM images) missions can be viewed at: http:/www.virtualmicroscope.org/content/apollo. The lunar sample VM will enable large numbers of skilled/unskilled microscopists (professional and amateur researchers, educators and students, enthusiasts and the simply curious non-scientists) to share the information from a single sample. It will mean that all the PTSs already cut, even historical ones, could be available for new joint investigations or private study. The scientific return from the collection will increase exponentially as a result of further debate and discussion. Simultaneously the VM will remove the need for making unnecessary multiple samplings, avoid consignment of delicate/breakable specimens (all of which are priceless) to insecure mail/courier services and reduce direct labour and indirect costs, travel budgets and unproductive travelling time necessary for co-location of collaborating researchers. For the future we have already recognized further potential for virtual technology. There is nothing that a petrologist likes more than to see the original rock as a hand specimen. It is entirely possible to recreate virtual hand specimens with 3-D hard and software, already developed for viewing fossils, located within the Curatorial Facility, http://curator.jsc.nasa.gov/lunar/lsc/index.cfm.

Gibson, E. K.↗
DOE OSTI2021

High-dimensional Data-driven Energy optimization for Multi-Modal Transit Agencies (HD-EMMA) (Final Technical Report)

Public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. Electric vehicles (EVs) can have a much lower environmental impact than comparable internal combustion engine vehicles (ICEVs), especially in urban areas. Unfortunately, EVs are also much more expensive than ICEVs. As a result, many public transit agencies can afford only mixed fleets of transit vehicles, consisting of EVs, hybrids (HEVs), and ICEVs. Transit agencies that operate such mixed fleets of vehicles face a challenging optimization problem: these agencies need to decide which vehicles are assigned to serving which transit trips. Since the advantage of EVs over ICEVs varies depending on the route and time of day (e.g., the benefit of EVs is higher in slower traffic with frequent stops and lower on highways), the assignment can have a significant effect on energy use and, hence, environmental impact. Through this project, we have developed reference data about energy collections and constructed a set of machine learning models that can accurately predict the energy consumption for the whole fleet at the level of each trip. We have used these models to develop a scheduling and assignment strategy that can rotate the different vehicle types across the transit agencies’ routes. The optimization algorithm ensures that the vehicles are matched to trips considering weather patterns, expected congestion, and road gradients to minimize the overall energy usage. We list the key observations from our project for other practitioners below. Details are available in the report, and the list of source code and our publications are included in the appendix. 1. We have demonstrated the feasibility of collecting, merging and analyzing large volumes of high-resolution real-world telemetry data from a mixed vehicle fleet. To mitigate the inherent noise of the recorded GPS points, the team developed an algorithm that filters data and maps the points onto a street. The algorithm considers previous and subsequent location measurements and different characteristics of nearby streets to determine how likely the vehicle travels on them. Then, the team segmented the time series into disjoint contiguous samples based on adjacent road segments and repeated the outlier detection and removal. For each data point, the team added features corresponding to elevation changes within the samples, weather features, such as temperature, and traffic data, such as speed ratio between actual speed and free-flow speed. 2. We have developed two forms of machine learning models that be used to understand and analyze the energy operations of a mixed vehicle transit fleet. The micro prediction model provides estimates of instantaneous energy prediction for all types of buses (diesel, hybrid, and electric). Such a model is important in evaluating the energy impacts of real-time bus operation strategies, but it is challenging due to diversified driving cycles of transit buses. The model can help the drivers understand the impact of their driving behaviors and short-term congestions. The macro prediction models estimate average energy consumption across the whole trip considering the features: distance traveled, various road-type features, elevation change, day of the week, time of day, various weather features (temperature, humidity, etc.), and traffic features (speed ratio and jam factor). 3. We have demonstrated that it is possible to transfer the machine learning models we have developed in this project to other teams and cities by using inductive transfer learning. We also showed that the performance of the macro energy prediction models can be improved using a multi-task learning approach where the learning parameters are shared between the models being developed for different vehicle types. The advantage of this approach is improved learning performance as the models can exploit common spatio-temporal and environmental characteristics. 4. Finally, we have developed trip and vehicle assignment and scheduling algorithms that use the energy prediction models and develop a trip to vehicle type (diesel, electric, hybrid) assignment for the whole operation to reduce overall emissions and cost. We have shown through simulations that the proposed algorithms can save $\$$ 48,910 in energy costs and 175 metric tons of CO 2 emission annually for CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

MO-FG-213-04: Managing the Relationship

Academic-industrial collaborations are playing an increasingly prominent role in medical physics research. Successful partnerships have enabled truly translational, benchtop-to-bedside research that has significantly and positively impacted our field. Given the current flat or depleting trends in federal funding, and the increasing emphasis in the medical physics community on demonstrating translatability, efficacy, and safety prior to widespread clinical use, it is anticipated that such partnerships will become ever more important in advancing our field. In the future, it is likely that neither academia alone, nor industry alone, will be able to bring significant innovation to successfully impact patient care in radiotherapy. Such innovation will require partnership and symbiosis through the lifetime of the project. This symposium is aimed at professionals from academia and the industry who are interested in either initiating new collaborations or maintaining and improving existing partnerships. We will hear from four thought leaders from industry and academia on critical aspects of building and maintaining successful academic-industrial research partnerships. The following topics will be addressed: 1. Motivations: The industry perspective [Kevin Brown, Elekta] What goes into the development of a company’s R&D roadmap What are the motivations and expectations of the industry from academic partners How can academics make a successful pitch by identifying projects aligned with a company’s roadmap Why are some relationships successful and some not Milestones and progress reports - Why do we need them 2. Motivations: The academic perspective [T. Rock Mackie, Univ. of Madison, WI; Tomotherapy] What are the motivations and expectations of academic partners from the industry What are the cultural differences in academia vs industry on sharing information, exchanging ideas Partnership or entrepreneurship? When does each option make sense 3. Industrial Grants and Research Contracts – a Primer [Norbert Pelc; Stanford University] What topics are suited to industrial grants vs. academic grants How do resources (personnel effort, tuition) get allocated and charged in academia What are reasonable resource and timeline requests for small and big projects; from small and big companies “Fair market value” considerations Sections of a research agreement (IP including software confidential information, publications, data, exclusivity, support) 4. Managing the relationship [John Wong, Johns Hopkins University] How to effectively collaborate with each other How to adapt to changes in the relationship How to renew funding with the industry Moderated Panel Discussion [All speakers + moderators] Learning Objectives: 1. Understand the motivations of each partner 2. Elements that contribute to a successful partnership 3. Avoiding pitfalls - Challenges on either side that may derail a project 4. How to frame a research grant and agreement 5. How to sustain the collaborative relationship Amit Sawant: Funding from: NIH. Varian, Elekta and VisionRT; Michelle Svatos: Employee and shareholder: Varian, Board Member, TopasMC; Kevin Brown: Employee, Elekta; T. Rock Mackie: Consultant, Accuray; Norbert Pelc: Research support: Philips Healthcare, GE Healthcare; John Wong: Funding from NIH, Xstrahl and Elekta. Co-founder and advisor for JPLC Associates, LLC.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2013

An Offload NIC for NASA, NLR, and Grid Computing

This work addresses distributed data management and access dynamically configurable high-speed access to data distributed and shared over wide-area high-speed network environments. An offload engine NIC (network interface card) is proposed that scales at nX10-Gbps increments through 100-Gbps full duplex. The Globus de facto standard was used in projects requiring secure, robust, high-speed bulk data transport. Novel extension mechanisms were derived that will combine these technologies for use by GridFTP, bandwidth management resources, and host CPU (central processing unit) acceleration. The result will be wire-rate encrypted Globus grid data transactions through offload for splintering, encryption, and compression. As the need for greater network bandwidth increases, there is an inherent need for faster CPUs. The best way to accelerate CPUs is through a network acceleration engine. Grid computing data transfers for the Globus tool set did not have wire-rate encryption or compression. Existing technology cannot keep pace with the greater bandwidths of backplane and network connections. Present offload engines with ports to Ethernet are 32 to 40 Gbps f-d at best. The best of ultra-high-speed offload engines use expensive ASICs (application specific integrated circuits) or NPUs (network processing units). The present state of the art also includes bonding and the use of multiple NICs that are also in the planning stages for future portability to ASICs and software to accommodate data rates at 100 Gbps. The remaining industry solutions are for carrier-grade equipment manufacturers, with costly line cards having multiples of 10-Gbps ports, or 100-Gbps ports such as CFP modules that interface to costly ASICs and related circuitry. All of the existing solutions vary in configuration based on requirements of the host, motherboard, or carriergrade equipment. The purpose of the innovation is to eliminate data bottlenecks within cluster, grid, and cloud computing systems, and to add several more capabilities while reducing space consumption and cost. Provisions were designed for interoperability with systems used in the NASA HEC (High-End Computing) program. The new acceleration engine consists of state-ofthe- art FPGA (field-programmable gate array) core IP, C, and Verilog code; novel communication protocol; and extensions to the Globus structure. The engine provides the functions of network acceleration, encryption, compression, packet-ordering, and security added to Globus grid or for cloud data transfer. This system is scalable in nX10-Gbps increments through 100-Gbps f-d. It can be interfaced to industry-standard system-side or network-side devices or core IP in increments of 10 GigE, scaling to provide IEEE 40/100 GigE compliance.

Awrach, James↗
DOE OSTI2016

Are Lock-Free Concurrent Algorithms Practically Wait-Free?

Lock-free concurrent algorithms guarantee that some concurrent operation will always make progress in a finite number of steps. Yet programmers prefer to treat concurrent code as if it were wait-free, guaranteeing that all operations always make progress. Unfortunately, designing wait-free algorithms is generally a very complex task, and the resulting algorithms are not always efficient. Although obtaining efficient wait-free algorithms has been a long-time goal for the theory community, most nonblocking commercial code is only lock-free. This article suggests a simple solution to this problem. We show that for a large class of lock-free algorithms, under scheduling conditions that approximate those found in commercial hardware architectures, lock-free algorithms behave as if they are wait-free. In other words, programmers can continue to design simple lock-free algorithms instead of complex wait-free ones, and in practice, they will get wait-free progress. Our main contribution is a new way of analyzing a general class of lock-free algorithms under a stochastic scheduler. Our analysis relates the individual performance of processes to the global performance of the system using Markov chain lifting between a complex per-process chain and a simpler system progress chain. We show that lock-free algorithms are not only wait-free with probability 1 but that in fact a general subset of lock-free algorithms can be closely bounded in terms of the average number of steps required until an operation completes. Here, to the best of our knowledge, this is the first attempt to analyze progress conditions, typically stated in relation to a worst-case adversary, in a stochastic model capturing their expected asymptotic behavior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Proposed guidance for preparing and reviewing a molten salt non-power production or utilization facility application

Development of non-power molten salt reactors (MSRs) are under consideration to further establish an MSR experience base, support the requirements of Title 10 of the Code of Federal Regulations (10 CFR) Section 50.43(e), and provide any additional analyses needed for development of a full-scale MSR. Guidance provided in this report is based on MSRs operating with liquid fuel (i.e., fuel dissolved within a molten salt). These reactors, unless owned by the DOE or DOD, will require licensing by the US Nuclear Regulatory Commission (NRC) staff. Standard review plan (SRP) guidance for large light water reactors (LWRs) is available in NUREG-0800, Standard Review Plan for the Review of Safety Analysis Reports for Nuclear Power Plants; Light Water Reactor (LWR) Edition. However, NRC staff observed that NUREG-0800 is very cumbersome to apply to non-power reactors “because of the great differences in complexity and hazards between non-power reactors and nuclear power plants.” Therefore, a program to develop performance-based guidance applicable to non-power reactors was initiated. In 1996, NUREG-1537, Parts 1 and 2, Guidelines for Preparing and Reviewing Applications for the Licensing of Non-Power Reactors, was published. Part 1, the format and content guide, suggests a uniform format for presenting information in non-power reactor applications that is acceptable to the NRC staff, but conformance with the format and content is not required. Part 2, the SRP, ensures the quality and uniformity of the staff review of an application. Unfortunately, the application guidelines and SRP do not provide adequate guidance for all advanced non-LWR technologies and applications. This discrepancy eventually led to the 2012 development of interim staff guidance (ISG) for NUREG-1537, which includes criteria for describing and reviewing aqueous homogeneous reactors (AHRs). Specifically, NUREG-1537 ISG, 2012 expanded the original document to address three areas: 1. updated criteria for heterogeneous non-power reactors, 2. criteria for licensing AHRs, and 3. criteria for licensing a Part 50-licensed isotope production facility. In 2015, the US Department of Energy (DOE) opted to build on the AHR NUREG-1537 ISG experience by performing a gap analysis of the guidance that would be used to license a non-power MSR. MSRs represent one of the advanced non-LWR technologies selected by DOE for development through a multiyear cost share award with Southern Company Services. Under this Advanced Reactor Concepts 2015 (DOE Advanced Reactor Concepts [ARC] 15) award program, the DOE tasked Oak Ridge National Laboratory (ORNL) to evaluate the guidance changes that the NRC may need to consider when licensing an MSR non-power reactor. ORNL staff, with support from Boston Government Services, LLC, focused on five system-related chapters in NUREG-1537 that were considered most relevant to inform the effort that would be required for a non-power MSR applicant. ORNL documented this review in a technical report, ORNL/TM-2018/834, Proposed Guidance for Preparing and Reviewing Molten Salt Non-Power Reactor License Applications (NUREG-1537). The report was subsequently shared with industry and the NRC. The 2018 review was limited in scope, focusing on key system chapters based on the expected significance of each chapter relative to expected differences in addressing advanced non-LWR technologies, specifically non-power MSRs, compared with heterogeneously fueled non-power reactors. In the ORNL report, proposed generic adaptations were suggested for the following NUREG-1537 chapters: Chapter 4, “Reactor Description”; Chapter 5, “Reactor Coolant Systems”; Chapter 6, “Engineered Safety Features”; Chapter 9, “Auxiliary Systems”; Chapter 11, “Radiation Protection Program and Waste Management” The inclusion of Chapter 11 in the previous review effort was intended to provide guidance for categorizing the waste-handling process for an MSR operating with homogenous fuel. The introductions from Parts 1 and 2 of the 2012 NUREG-1537 ISG provide guidance for the application and review of production facilities. After a period of operation, non-power MSRs with homogenous fuel will include gaseous and soluble fission products. The gaseous fission products will be collected and held for decay in an off-gas system. There might also be an initiative to polish or filter the soluble fission products in the fuel salt by some mechanical or chemical means. The treatment and handling of fission products in the non-power MSR fuel salt and the description of this process in the safety analysis report (SAR) must be very precise to avoid the waste treatment facility being construed as a co-located special nuclear material (SNM) fuel cycle facility (see Section 2.3 of this report). Subsequent to the release of ORNL/TM-2018/834, NRC staff expressed a desire to continue the regulatory gap analysis that was begun in that report. This would provide additional clarity and information addressed in certain sections of the original report, while also providing new guidance on certain topics not addressed in the original report. This revision would benefit the NRC staff reviewing applications involving non-power MSR designs and would help developers understand how the NRC staff might approach the review of such applications. The focus of this report is to provide infrastructure support to the NRC staff for the regulatory review of non-power MSRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Anticipating Change - A Means to Save Time and Rethink the Implementation of the 10 Code of Federal Regulations 770 Real Property Transfer Process - 15662

The Department of Energy (DOE) issued 10 Code of Federal Regulations (CFR) 770 in 2000 for the 'Transfer of Real Property at Defense Nuclear Facilities for Economic Development'. The rule was issued in order to 'offset negative impacts on communities caused by unemployment from related DOE down-sizing, facility close-outs and workforce restructuring'. There is a sense of urgency implied in efforts designed to address economic conditions, especially in communities that have hosted DOE facilities and are experiencing negative impacts of mission changes. Despite the urgency, the transfer of real property from DOE or any federal agency is a lengthy, complex, iterative, but necessarily diligent effort. After all, the aim of the process is to be able to demonstrate that the property proposed for transfer is protective of human health and the environment for the intended use. Notwithstanding the efforts of the economic development organization to market, recruit, and prepare a robust proposal to request property, and the efforts of DOE to perform the many due diligence activities in response to that request, the actual results of the evaluations are an unknown until a major portion of the process is completed. Will the property be determined to be suitable for transfer? Will there be deed restrictions? Is indemnification available? Has a mission need for the property arisen while working through the reviews? There are many points along the way that can sidetrack or delay progress and, in the interim, the economic viability of the proposal can collapse. Even without the unforeseen events, the process in and of itself is lengthy. It is often heard (loudly) that it takes far too long to obtain a piece of property once a request is made; that observation/criticism is worthy of serious attention. Rather than revisit old debates, why not learn from them? Why not look at the transfer process from a different point of view and ameliorate it so it can be more responsive to community needs? Why not anticipate change, anticipate requests, and make property available before a request as well as responding to requests to make property available? There are several ways to rethink and modify the way the transfer process is implemented to reduce the time following a request. The modifications would arise from both internal information sharing, integrated and timely up-front planning and, in particular, by varying how and when certain elements of the process to enable transfer are performed. This paper will address: 1. How a unified overall vision can be created from the cleanup input of Site-Specific Advisory Boards with the Community Reuse Organizations' planning for economic development and can help inform site cleanup to end state to future use; 2. Why DOE is in the best position to know its site conditions and could determine ahead of a transfer request what property is indeed available and notify of that determination; 3. How a range of disposition paths for real property are available to DOE; and 4. Why broadening the understanding of 'best interest of the government' to one that is clearly able to recognize non-monetary benefits is in the best interest of the government. Anticipating change helps prepare DOE and their host communities for the future. It creates opportunities for flexibility and time savings. The sooner DOE's unneeded and under-utilized real property can be made available to the communities that need it most, the sooner those communities can work to moderate the adverse effects of DOE mission changes. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Licensing Modernization Project for Advanced Reactor Technologies: FY 2018 Project Status Report

The promise of new nuclear technology and the future of commercial power in the United States (U.S.) are linked to the existence of an efficient and safety-focused regulatory review and licensing process. With an appropriate regulatory framework, reactor suppliers and regulators can design, license, build, and export advanced reactor units more effectively and efficiently and thereby help meet the growing need for clean and reliable energy. To help address the challenge of maintaining compatibility between the regulatory environment and new commercial nuclear plant designs, the U.S. Department of Energy (DOE) is supporting an industry-led effort called the Licensing Modernization Project (LMP). This cost-shared initiative, started in 2016 and scheduled to continue through mid-2019, targets amendment to key elements of the U.S. nuclear power reactor regulatory framework to specifically address licensing barriers in advanced-reactor concepts. The project is focused on updating guidance for certain technical licensing requirements that are largely incompatible with non-light-water reactors (non-LWR) and establish a new pathway for design-safety evaluations and license-application development. Upon completion, the project will have created a new pathway, founded on modern probabilistic assessment techniques, that offers developers, suppliers, regulators, and owner/operatorowner-operators greater clarity and assurance in design and licensing decisions. The LMP employs a team of advanced reactor technology and licensing subject matter experts working closely with U.S. regulators, affected industries, and interested members of the public. The project is managed by Southern Company and supported through a cost share arrangement with DOE. Technical contributions are also provided to the project from the Idaho National Laboratory (INL) Regulatory Development area, the Nuclear Energy Institute (NEI), and the U.S. Nuclear Regulatory Commission (NRC). The LMP identified a suite of high priority issues that provided significant uncertainty within the regulated non-LWR community. It was determined that much of this uncertainty could be retired by issuing updated licensing guidance founded on safety performance demonstrations and modern probabilistic methodologies. The success criteria for the project were established as: • Generate sets of technology inclusive (TI), risk-informed, and performance-based (TI-RIPB) technical requirements, recommendations, and proposals that could be reviewed, amended, and adopted for use by both NRC staff and industry. The proposals would create an optional-use regulatory framework without imposing additional (i.e., mandatory) requirements. • Support LMP the recommended updates of LMP such that they can be finalized, endorsed by NRC, and used by applicants within 5 years. This also supports the DOE advanced- reactor development and deployment goal of completing licensing reviews for technically mature non-LWR concepts sufficient to allow construction to proceed by the early 2030’s. • Further overall programmatic objectives established by DOE’s Gateway for Accelerated Innovation in Nuclear (GAIN) initiative by resolving technology-inclusive policy issues that adversely impact regulatory reviews, siting, permitting, and/or licensing of non-LWRs. This would provide significantly more regulatory certainty for advanced reactor developers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

A New Appraisal- Lessons from the History of Efforts to Value Green and High-Performance Home Attributes in the United States

Rigorous consideration of green and high-performance (“green/HP”) features is rarely included in the property valuation process._ To help illuminate why this is the case, this report takes stock of the history of efforts to improve practices, and identifies barriers that have emerged and opportunities for overcoming them. Particular emphasis is placed on what energy and environmental policymakers and other stakeholders outside the appraisal community can contribute to the broader effort to advance professional practices. The history has unfolded in parallel with turbulent periods in the housing market for which appraisers and their customers are deemed to share responsibility, followed by cycles of regulations, siloing of appraisers in the name of professional integrity, and commoditization of the valuation process itself. This pattern has important ramifications for aspirations that appraisers engage more fully in identifying and valuing the green/HP characteristics of homes. On the one hand, it is legally and ethically incumbent on appraisers to do so, yet on the other hand it is perceived as a risky avenue to follow. Risks arise where findings can be challenged as either over- or under-stating value, together with a market environment in which the complexity of their assignments increases despite downward pressure on appraiser fees. While efforts to address green/HP considerations date back to the early 1980s, the vast majority of activity has taken place within the past five years. Many players have engaged in the efforts to promote improved valuation practices. These include the Appraisal Foundation, The Appraisal Institute, Colorado Energy Office, Earth Advantage, EcoBroker, Elevate Energy, Fannie Mae, Federal Housing Administration, Home Innovation Research Labs, The Institute for Market Transformation, Northwest Energy Efficiency Alliance, National Association of Homebuilders, National Association of State Energy Officials, National Association of Appraisers, RESNET, USEPA, USDOE and its National Laboratories, the U.S. Green Buildings Council, and the Vermont Green Homes Alliance. Many activities have resulted, ranging from trainings, to data-gathering instruments, and the emergence of a literature attempting to statistically isolate the effects of green/HP characteristics on home values. In some cases, the results of studies have been overgeneralized and oversold, and embodied flawed methods. Although the green/HP community has encouraged appraisers to focus on exemplary buildings (e.g., LEED or ENERGY STAR Certified), any level of green or energy performance can in fact influence value, including below-average performance (a.k.a. “brown discount”), irrespective of whether or not the building has been formally rated. This overly narrow focus represents a significant missed opportunity. Other surmountable challenges include limitations to non-appraisers’ understanding of the appraisal process (and practical constraints therein). A byproduct of this can be unrealistic expectations of what appraisers can and will do in the marketplace. These challenges notwithstanding, the environment for moving forward has improved. There is better data today (a critical need); expanded efforts to disclose energy use information (characteristics, consumption, bills); improved and more pervasive building energy codes, building rating and labeling initiatives; and a host of federal, state, and local policies that have collectively brought green/HP practices much more into the mainstream. Meanwhile, a renewed focus on professional standards of care and competency for assessing green/HP homes make it increasingly important for appraisers to consider these factors in their assignments. Despite the past four decades of studies, there is little if any discernible uptake of these practices by the appraisal practice at large. It would behoove interested parties to step back and consider what new strategies might be productive. A key element of any new plan should be to reset the nature of interactions with the industry, with the goal a more collaborative, two-way discussion to help improve outsiders’ understanding of the valuation process. It is not only the appraiser that needs to be engaged and could benefit from awareness raising. Homeowners, builders, lenders, utilities, insurance companies should also provide input on how green/HP factors impact property valuations and ways to accurately reflect these considerations in appraisals and real estate transactions more broadly. Given extensive inertia within the appraisal industry and a mixed history of interactions with the non-appraisal stakeholders, it is unlikely that the status quo will achieve much unless followed with more coordinated and persistent efforts. Workshops, studies, and memoranda of understanding will not on their own have much impact, and do not address deeper structural issues. Expectations are often unrealistic and not attentive to real-world constraints faced by appraisers. The report identifies key barriers impeding more thorough consideration of green/HP factors in residential real estate appraisals, and solutions for mitigating them. Barriers • Although industry standards of practice caution against bias of any sort, a skeptical predisposition towards “green” is reinforced by information deficiencies. • Information deficiencies result from the lack or difficulty of obtaining usable data on green/HP features in subject properties as well as valid sales comparisons or cashflow analyses. • Competency deficiencies, such as lack of conversancy in relevant technical topics, leads to oversights, and disjointed treatment of relevant information. • Time/cost pressure and process commoditization (e.g., template-based approaches) result from highly constrained budgets, quick turn-around times expected of appraisers, and standardized practices that were not developed with green/HP considerations in mind. • Professional differences between appraisers and sustainability professionals include divergent objectives, the former being market observers and the latter market influencers. • Risk aversion arises from multiple concerns including veracity, accuracy, and persistence of energy data, impacts of operational choices, new sources of appraiser liability associated with green/HP assessments, industry pressures not to over-value buildings or suggestion of bias, and concern about spending non-billable time on complex assignments. • A public policy vacuum has been created by disjointed and uncoordinated efforts from public-sector stakeholders, insufficient efforts to discuss and understand the appraisal industry and process, and a perception by some valuation professionals that green/HP is oversold. Opportunities • Elevating the competency of appraisers can be achieved through a combination of improved industry standards of care and equal-access training and professional development offerings. • Development of better information resources must focus on building-level information that provides robust documentation as well as aggregate sales-comparison data and other contextual information such as local codes, typical upgrade costs, energy prices, etc. • Improved energy benchmarking and rating tools could provide appraisers with information more well-adapted to their particular needs, which differ from those of typical audiences such as energy managers. • Better characterizing and managing risk will enable appraisers to cope with uncertainties in performance information, and help identify where risks may be introduced or mitigated by green/HP features, including higher costs or obsolescence of poorly-performing buildings. • Integrating disaster resilience and sustainability in appraisals would recognize important synergisms among these features, including durability and ability of green/HP buildings to better withstand external hazards. • Mitigating the problem of additional time/cost for performing assignments is an essential need that can be addressed by providing easier access to information and analytic procedures, perhaps coupled with new resources to defray the associated costs. • Enhancing demand for improved appraisals is a fundamental need, and depends on owners, developers, lenders, and others soliciting competent appraisers to perform scopes that expressly call out green/HP considerations, and to critically review the work product for compliance before acceptance. • Engaging new market participants, such as energy utilities and insurance companies can ensure fuller representation and participation of market stakeholders already engaged in green/HP activities and capable of furnishing valuable data and managing associated risks. Cutting across these individual activities, there is a need for outside stakeholders to formulate and follow a roadmap instead of piecemeal initiatives, bridging the professional/cultural divide between appraisers and green/HP communities, and tracking progress in order to know what is working. A more coherent communication and training strategy is needed, as the appraisal industry is highly fragmented, with two-thirds of appraisers opting out of membership in trade associations. In sum, while there is no silver bullet for advancing the practice of valuing green/HP features, there are concrete opportunities. Parties seeking solutions must identify barriers they wish to address and select from among potential initiatives that map to those barriers. Close collaboration with the appraisal community is critical, as non-appraisers have historically obtained limited traction with this industry due to lack of understanding of the nuances involved in the valuation profession. Large organizations and agencies should have a united approach; the perception or reality of a fragmented and uncoordinated strategy is unsettling for prospective partners in the appraisal industry. This requires improved communication and education within and among these communities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗
DOE OSTI2015

Criticality safety analysis of spent fuel storage or handling disposals using burnup credit - loading curve calculation - 14445

MILLENNIUM and REEL SAS Companies have shared their own experience to develop a neutron and criticality calculations chain in order to perform isotopic composition predictions of spent fuel after irradiation in a reactor and criticality analysis of fuel storages taking into account burnup credit. The whole calculation sequence is divided into three steps, all calling SCALE 6.1.2 modules. The first two steps are dedicated to the evaluation of isotopic compositions of burnt fuel. As transport and depletion calculations in three dimensions appears to be way too long for the whole core (about several months), dealing with each fuel assembly one by one is the alternative solution MILLENNIUM and REEL SAS commonly chose to study. Therefore, the first step aims at determining the axial burnup profile of a given fuel assembly using a 3-D model with infinite reflections on lateral axes. The T6-depl sequence of TRITON module coupling KENO-VI and ORIGEN-S was used in this step. Sensitivity studies confirmed that addition of the 8 closest neighbors of the studied fuel assembly in the model has an insignificant impact on the axial burnup profile. However, fuel assemblies in the peripheral zone of the core must be treated separately with a model including the nearest fuel assemblies and the effect of peripheral water. Then, the second phase evaluates the isotopic compositions of each fuel assemblies at the center of the active height with a 2-D model under conservative core conditions. The T-depl sequence of the TRITON module coupling NEWT to ORIGEN-S is called in this step. Each fuel assembly must be studied separately to consider loading pattern changes occurring at each cycle. An infinite model with reflections on lateral axes is used and the closest neighbors of the fuel assembly are limited to 2 pins - which is around the size of the neutrons mean free path in the core. This is an innovative physical trick aiming at compensating for a limited computing power. Finally, isotopic compositions calculated are combined with the axial burnup profile of the first step to extrapolate the concentrations along the whole active length. Data can then be added in any criticality model, such as a spent fuel pit or any disposal handling fuel assemblies. Criticality analyses of burnt fissile material using burnup credit can be managed within a reasonable amount of time, on condition that sufficient proofs of code qualification for the studied range of parameters are provided, especially on fission products isotopic compositions calculation. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗
NASA NTRS1996

Geodata Modeling and Query in Geographic Information Systems

Geographic information systems (GIS) deal with collecting, modeling, man- aging, analyzing, and integrating spatial (locational) and non-spatial (attribute) data required for geographic applications. Examples of spatial data are digital maps, administrative boundaries, road networks, and those of non-spatial data are census counts, land elevations and soil characteristics. GIS shares common areas with a number of other disciplines such as computer- aided design, computer cartography, database management, and remote sensing. None of these disciplines however, can by themselves fully meet the requirements of a GIS application. Examples of such requirements include: the ability to use locational data to produce high quality plots, perform complex operations such as network analysis, enable spatial searching and overlay operations, support spatial analysis and modeling, and provide data management functions such as efficient storage, retrieval, and modification of large datasets; independence, integrity, and security of data; and concurrent access to multiple users. It is on the data management issues that we devote our discussions in this monograph. Traditionally, database management technology have been developed for business applications. Such applications require, among other things, capturing the data requirements of high-level business functions and developing machine- level implementations; supporting multiple views of data and yet providing integration that would minimize redundancy and maintain data integrity and security; providing a high-level language for data definition and manipulation; allowing concurrent access to multiple users; and processing user transactions in an efficient manner. The demands on database management systems have been for speed, reliability, efficiency, cost effectiveness, and user-friendliness. Significant progress have been made in all of these areas over the last two decades to the point that many generalized database platforms are now available for developing data intensive applications that run in real-time. While continuous improvement is still being made at a very fast-paced and competitive rate, new application areas such as computer aided design, image processing, VLSI design, and GIS have been identified by many as the next generation of database applications. These new application areas pose serious challenges to the currently available database technology. At the core of these challenges is the nature of data that is manipulated. In traditional database applications, the database objects do not have any spatial dimension, and as such, can be thought of as point data in a multi-dimensional space. For example, each instance of an entity EMPLOYEE will have a unique value corresponding to every attribute such as employee id, employee name, employee address and so on. Thus, every Employee instance can be thought of as a point in a multi-dimensional space where each dimension is represented by an attribute. Furthermore, all operations on such data are one-dimensional. Thus, users may retrieve all entities satisfying one or more constraints. Examples of such constraints include employees with addresses in a certain area code, or salaries within a certain range. Even though constraints can be specified on multiple attributes (dimensions), the search for such data is essentially orthogonal across these dimensions.

Adam, Nabil↗
DOE OSTI2015

Scalability under a Power Bound using the GREMLINs Framework

With the move towards exascale, system and software developers will have to deal with issues of extreme parallelism. The system properties affected most by the increase in node and core count are the shared resources on node and across the system. The increase in parallelism leads to reduced memory and bandwidth when regarding individual cores. Since power is a limiting factor for supercomputers, and power is not fully utilized in current systems, overprovisioning compute resources is a viable approach to maximized power utilization. To maximize system performance in regard to these changing conditions, it is necessary to understand how resource restrictions impact performance and system behavior. For the purpose of understanding anticipated system properties the GREMLINs Framework was developed. The framework gives the opportunity to add power restrictions, hinder memory properties and introduce faults to study resilience, among others. These features give the opportunity to use current petascale technology to study problems system designers and software developers will have to face when moving towards exascale and beyond. This work describes the initial release of the GREMLINs Framework, developed for this work, and shows how it can be used to study the scaling behavior of proxy applications. These proxy applications represent a selection of HPC workloads important to the scientific community. The proxy applications studied are AMG2013, an algebraic multi-grid linear system solver, CoMD, a classical molecular dynamics proxy application and NEKBONE, an application that uses a high order spectral element method to solve the Navier-Stokes equations. The main interest of these studies lies in analysis regarding their power behavior at scale under a power bound. These findings show how the GREMLINs Framework can help systems and software designers to attain better application performance and can also be used as basis for CPU power balancing tools to use power more efficiently.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Added Value for Integrated Marine Energy Data Systems (February 2021)

Launched in 2019, the Portal and Repository for Information on Marine Renewable Energy (PRIMRE) provides centralized access, standardization, community building, and integration of United States (U.S.) databases, tools and codes, and other resources that cover a range of marine energy information. The PRIMRE universe contains a series of Knowledge Hubs that represent data and information on testing of marine energy devices (MHKDR); environmental effects (Tethys); engineering and technical papers (Tethys Engineering); descriptions of marine energy companies and technologies (Marine Energy Projects Database); codes and models (Marine Energy Software); and guidance on testing and measurements (Telesto). Content is added to PRIMRE by applying a set of Guidelines and Best Practices (PRIMRE Guidelines). An aggregate search across the PRIMRE site enables users to find data and information from all the PRIMRE Knowledge Hubs simultaneously, using a single entry-point (PRIMRE Search). In addition to providing access to a range of data and information on marine energy development, testing, and effects, PRIMRE allows for the development of valueadded products and processes that will help move the marine energy industry forward. The PRIMRE team has recently launched two key initiatives in the U.S.-Signature Projects and Lessons Learned. Outputs and outcomes from these two initiatives will be highlighted in this paper. The Signature Projects initiative is intended to bring focus to a selection of ongoing and completed marine energy projects funded by the U.S. Department of Energy's Water Power Technologies Office (WPTO), and to inform the marine energy community of what investigations have been undertaken, what tools are available, and where gaps in information persist. Each Signature Project tags papers, reports, and data from large marine energy research projects, providing easy access and attention to all the output and associated products from each project. The Lessons Learned initiative is intended to ensure that hard-won achievements are recognized and available for those who come later, that missteps and unfortunate outcomes can be prevented in future, and that efficiencies and effective shortcuts can be publicized and used as the marine energy industry moves forward. This initiative builds off the Knowledge Hubs and reaches out to members of the marine energy community, particularly technology developers and researchers, to integrate experience in the development, deployment, assessment, success, challenges while creating this new industry and field of study.

data sharing↗