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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Pressurized-Water Reactor Core Design using Multi-Objective Plant Fuel Reload Optimization Platform

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program Risk-Informed Systems Analysis (RISA) Pathway Plant Reload Optimization Project aims to develop an integrated, comprehensive framework offering an all-in-one solution for reload evaluations with a special focus on optimization of core design. The optimization of the fuel loading pattern is one of the most important considerations in reducing the amount of new fuel used in the core. Due to thousands of possible options of core configuration, finding optimal solutions is an unachievable task for a human. The Plant ReLoad Optimization (PRLO) platform which supports artificial-intelligence-based reactor core designing is now fully capable of handling realistic problems. The PRLO Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. The NSGA-II (Non-dominated Sorting Genetic Algorithm-II) optimizer was developed and tested within RAVEN (Risk Analysis and Virtual Environment) to handle many constraints by using an augmented objectives methodology. The demonstration was performed with constrained multi-objective optimization of a 17 × 17 pressurized-water reactor core loading patterns to minimize fuel cost and maximize fuel cycle length.

42 ENGINEERING↗
DOE OSTI2018

Tomographic Event Reconstruction with MicroBooNE Data

Event reconstruction is one of the most challenging tasks in analyzing the data from current and future massive single-phase liquid argon time projection chambers (LArTPCs). The performance of event reconstruction is critical to the potency of the eventual physics result. In this note, we describe a novel event reconstruction method, known as Wire-Cell tomographic imaging, applied to MicroBooNE data. MicroBooNE is an 85 metric ton single-phase LArTPC and the first of a trio of LArTPCs in the Short Baseline Neutrino (SBN) program. MicroBooNE’s principal aims are to understand the MiniBooNE low energy excess, measure neutrino-argon interaction cross sections, and improve the understanding and capability of single-phase LArTPCs through detector R&D.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computationally intensive tasks to specialized hardware. However, as the landscape of compute accelerators quickly evolves, it becomes increasingly difficult to manually adapt the code to the latest hardware or software environments. A solution which is portable to multiple hardware architectures without substantially compromising performance would thus be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we present our experience porting the LArTPC simulation code in the Wire-Cell Toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs are presented, followed by a discussion of the factors affiecting the performance and plans for future improvements.

Yu, Haiwang↗
DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS): Task 4.0 Deliverable – Geologic Analysis Report

Project OASIS (Optimizing Alabama’s CO 2 Storage in Shelby County) is a geologic and reservoir characterization study designed to evaluate deep saline formations for potential long-term carbon dioxide (CO 2 ) storage in central Alabama near the National Carbon Capture Center (NCCC) and Alabama Power’s Plant Gaston. The project centers on the Cambro-Ordovician Knox Group and underlying strata such as the Conasauga and Rome Formations, which were investigated through the drilling of two stratigraphic test wells to obtain electronic well logs, core, and sidewall core plugs. These data provide direct measurements of porosity, permeability, and lithologic variability critical for reservoir characterization. Complementing the well program, a limited 2D seismic survey was acquired to help select the site for Westover #2, and a more regional Seismic Exchange (SEI) seismic survey was licensed and interpreted to define structural and stratigraphic frameworks in a new Static Earth Model (SEM), map reservoir continuity, and identify potential sealing intervals. Integrated with geologic and reservoir modeling, these datasets form the basis for evaluating storage capacity, injectivity, and containment.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Reconfigurable perovskite nickelate electronics for artificial intelligence

Reconfigurable devices offer the ability to program electronic circuits on demand. Here, in this work, we demonstrated on-demand creation of artificial neurons, synapses, and memory capacitors in post-fabricated perovskite NdNiO 3 devices that can be simply reconfigured for a specific purpose by single-shot electric pulses. The sensitivity of electronic properties of perovskite nickelates to the local distribution of hydrogen ions enabled these results. With experimental data from our memory capacitors, simulation results of a reservoir computing framework showed excellent performance for tasks such as digit recognition and classification of electrocardiogram heartbeat activity. Using our reconfigurable artificial neurons and synapses, simulated dynamic networks outperformed static networks for incremental learning scenarios. The ability to fashion the building blocks of brain-inspired computers on demand opens up new directions in adaptive networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Development Plan for the MOX Fuel Fabrication Process

The Advanced Fuel Campaign (AFC) in Fuel Cycle Research and Development (FCRD) has tasks of near term Accident Tolerant Fuel (ATF) for light water reactor (LWR) and long term advanced reactor fuel research and development. Mixed Oxide (MOX) is one of the options for the advanced reactor fuel and development plan for the fabrication and characterization of MOX is described. The efforts will include the confirmation of the MOX fabrication capability and development of processing parameters for the stable fabrication of MOX fuel to support future MOX work if the need arises from the program. Establishing a robust fabrication process of desired stoichiometry utilizing the fabrication equipment recently added to Fuel Manufacturing Facility (FMF) glove box sintering furnace would be the main goal of the development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Multi-Mechanism Flood Hazard Assessment: Critical Review of Current Practice and Approaches

This report documents the initial findings from the Nuclear Regulatory commission (NRC)-sponsored research project Methods for Estimating Joint Probabilities of Coincident and Correlated Flooding Mechanisms for Nuclear Power Plant Flood Hazard Assessments.1 This research project is a part of NRC’s Probabilistic Flood Hazard Assessment (PFHA) Research Program and will aid the development of guidance on the use of PFHA methods to evaluate infrastructure safety for existing and proposed US nuclear power plants (NPPs). More specifically, this project intends to provide technical background for the development of flood hazard curves for multi-mechanism floods (MMFs). MMFs are flood events caused by more than one flooding mechanism (e.g., flood events due to the simultaneous occurrence of precipitation-induced river flooding and storm surge). Project activities include three main tasks: Task 1—Survey of current concepts and methods in assessing MMF hazards; Task 2—Critical assessment of selected methods and approaches for quantifying probabilistic MMF hazard risk; Task 3—Development of example case studies to illustrate best practices for quantifying probabilistic MMF hazard risk The initial findings from Tasks 1 and 2 are documented in this report. Task 1 comprised a survey of approaches and methods that have been applied to understand and assess flood hazards due to MMFs. Task 2 involved a critical review of the selected approaches and methods. To that end, the scope of this report includes documentation of (1) a reconnaissance-level survey of the current state of concepts and practice for MMF hazard assessment; (2) a generalized MMF assessment framework to address the distinctions among various types of flood-forcing phenomena, flood mechanisms (grouped into three mechanism types), and flood severity metrics; (3) a wide-ranging survey of approaches and methods that have been applied to various flooding phenomena and settings; and (4) a critical assessment of MMF hazard assessment methods. Studies were identified involving MMFs related to coastal flooding mechanisms, fluvial (rivers/streams) flooding mechanisms, and associated combinations of coastal and fluvial flooding mechanisms. Studies were also identified that address MMFs involving coastal and fluvial flooding mechanisms as well as coastal flooding mechanisms along with extreme precipitation (without specific attribution to fluvial or pluvial mechanisms). The studies identified for review in this report included assessments at varying spatial scales (from local to global) with differing geographic regions of focus using both observed and synthetic data. The majority of studies identified and reviewed were site-specific assessments focusing on relatively short return periods. Studies considered a range of flood severity metrics, made differing assumptions regarding the occurrence of extrema, and used multiple statistical techniques; the use of copulas for the development of joint distributions was a particularly popular analysis technique. The literature review highlighted the differences among existing studies relative to terminology used, means of presenting results, framework and techniques employed, and level of sophistication regarding the number and types of variables considered. Despite the significant diversity in existing studies, the review identified several promising techniques that will be considered in future work under this project, including the development of joint distributions for MMFs using copula and Bayesian-motivated approaches.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

Beyond Relaxation and Newton–Raphson: Solving AC OPF for Multi-Phase Systems With Renewables

This paper focuses on the AC Optimal Power Flow (OPF) problem for multi-phase systems. Particular emphasis is given to systems with high integration of renewables, where adjustments of the real and reactive output powers from renewable sources of energy are necessary in order to enforce voltage regulation. The AC OPF problem is known to be nonconvex (and, in fact, NP-hard). Convex relaxation techniques have been recently explored to solve the OPF task with reduced computational burden; however, sufficient conditions for tightness of these relaxations are only available for restricted classes of system topologies and problem setups. Identifying feasible power-flow solutions remains hard in more general problem formulations, especially in unbalanced multi-phase systems with renewables. To identify feasible and optimal AC OPF solutions in challenging scenarios where existing methods may fail, this paper leverages the Feasible Point Pursuit - Successive Convex Approximation algorithm - a powerful approach for general nonconvex quadratically constrained quadratic programs. The merits of the approach are illustrated using single- and multiphase distribution networks with renewables, as well as several transmission systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Evaluation of Roadmap to Achieve Energy Delivery Systems Cybersecurity

The Department of Energy/Office of Electricity Delivery and Energy Reliability (DOE/OE) Cybersecurity for Energy Delivery Systems (CEDS) program is currently evaluating the Roadmap to Achieve Energy Delivery Systems Cybersecurity document that sets a vision and outlines a set of milestones. The milestones are divided into five strategic focus areas that include: 1. Build a Culture of Security; 2. Assess and Monitor Risk; 3. Develop and Implement New Protective Measures to Reduce Risk; 4. Manage Incidents; and 5. Sustain Security Improvements. The most current version of the roadmap was last updated in September of 2016. Sandia National Laboratories (SNL) has been tasked with revisiting the roadmap to update the current state of energy delivery systems cybersecurity protections. SNL is currently working with previous and current partners to provide feedback on which of the roadmap milestones have been met and to identify any preexisting or new gaps that are not addressed by the roadmap. The specific focus areas SNL was asked to evaluate are: 1. Develop and Implement New Protective Measures to Reduce Risk and 2. Sustain Security Improvements. SNL has formed an Industry Advisory Board (IAB) to assist in answering these questions. The IAB consists of previous partners on past CEDS funded efforts as well as new collaborators that have unique insights into the current state of cybersecurity within energy delivery systems. The IAB includes asset owners, utilities and vendors of control systems. SNL will continue to maintain regular communications with the IAB to provide various perspectives on potential future updates to further improve the breadth of cybersecurity coverage of the roadmap.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

ARM Aerosol Measurement Science Group Strategic Planning Workshop 2017

The Aerosol Measurement Science Group (AMSG) was tasked with evaluating the status of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s existing aerosol instrumentation, measurement strategies, and data products in the context of ARM and Atmospheric System Research (ASR) science directions and the current and future needs of ARM data users. A workshop comprising the AMSG members and external experts in aerosol measurements was convened in February 2017 to delineate specific measurements and efforts in data product development that would align the ARM aerosol program investments well with the needs of the scientific community. Topics of discussion in the workshop included priority measurements and instrumentation to be deployed at the range of ARM sites, physical system configurations that impact the character of observables and quality of observations, calibration strategies, overarching deployment strategies for aerosol observing systems (AOS), and communication about and accessibility of data. This report provides an account of workshop discussions and prioritized recommendations for ARM supported activities that will bring measurements to quality and science-ready data products relevant to the ASR and larger science community.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Final Report: Scale-up of Algal Biofuel Production Using Waste Nutrients

Renewable fuels can be more environmentally friendly than conventional fuels and can be produced locally, supporting energy independence. Liquid renewable fuels are of special interest due to their high energy density. Algae are a promising prospective feedstock for low carbon intensity liquid biofuels, due to their high productivity and potential for high lipid or carbohydrate content. Their ability to grow on wastewater and waste nutrients and on non-arable land are cost and sustainability advantages. The organic matter content of wastewater promotes mixotrophic and/or heterotrophic growth of both algae and bacteria, boosting biomass productivity further. However, economic and technologic challenges persist that prevent the scale-up of algal biofuels to commercial relevance. These challenges include algal harvesting, drying, dewatering, and the conversion of algal biomass to usable fuels (Hannon et al 2010, Dunlap and Shaw 2009, Pienkos et al. 2009). The US Department of Energy (DOE) Bioenergy Technologies Office (BETO) supports research to overcome these challenges and outlines the research and development goals for algal biofuels in their Multi-Year Program Plan (MYPP). The long-term goals of the MYPP for algal biofuels research are briefly as follows: develop the domestic ability to produce algal biofuels at a scale of 5 billion gallons per year (BGY) by 2030 and demonstrate technologies that produce biofuel intermediates from algae at a cost of $3/gallon of gasoline equivalent (GGE) by 2022 (BETO MYPP 2016). This research reported herein was funded to investigate methods of meeting an intermediate milestone of 2,500 gallons of biofuel intermediate per acre per year for a non-integrated process by improving algal productivity, harvesting efficiency, and conversion to biofuel intermediates. Use of wastewater and wastewater nutrients was a key distinguishing characteristic of this project. In pursuit of 2,500 gallons of biofuel intermediate (BFI) per acre per year, California Polytechnic State University, San Luis Obispo (Cal Poly) sought to develop the capability to produce biofuel intermediates from microalgae grown on municipal wastewater at a 20-acre algae-based wastewater treatment facility in Delhi, California (37.43° N), which includes 7 acres of raceway ponds. Coupling algal biofuel production with wastewater treatment capitalizes on the abundant waste nutrients and carbon present in wastewater and reduces use of clean water in algal biorefinery systems. In this research, the performance of the full-scale wastewater treatment plant was characterized by measuring productivity, wastewater treatment performance, hydraulic characteristics, and energy consumption. Nine 1,000-L pilot raceways with CO2 addition were used in experiments to maximize productivity. Low-cost, energy-efficient algae bioflocculation and settling were monitored. Population genetics were monitored in an attempt to correlate taxa with superior productivity and/or settling. Algae-bacterial biomass was converted to biofuel intermediates via bench-scale hydrothermal liquefaction (HTL), and the resulting fuel quality was characterized. To develop rapid strain screening capabilities, a climate simulating photobioreactor (“LEAPS”) was developed and validated against outdoor raceways. A techno-economic analysis (TEA) and a lifecycle assessment (LCA) were performed to model process economics and sustainability. The major outcomes of this research included demonstration of 33 g/m2-day annual average algal-bacterial productivity in pilot raceways, and a biofuel intermediate yield of 0.35 g intermediate/g algae biomass via HTL, for a yield of 4,100 gallons BFI per acre per year, assuming a 90% harvest efficiency and ignoring other minor losses. This exceeded the project goal of 2,500 gallons of BFI per acre per year and nearly met the 2030 program goal, highlighting the promise of integrating wastewater treatment and biofuels production. The biocrude BFI produced by the process is refined to diesel and naphtha fuels. These fuels are normalized to the energy content of gasoline (gallons gasoline equivalent, GGE, for comparison to other fuels). Results from the TEA of the this complete “well-to-wheel” process demonstrated that, at a 400-ha scale, a minimum fuel selling price (MFSP) of $12.55/GGE, which could be decreased 57% to $7.14/GGE when including revenue from coupling the biofuel production with the co-products of wastewater treatment services and low carbon fuel credits from California and Federal programs. Due mainly to the high capital costs of thickener centrifuges and hydrothermal processing equipment, the fuel cost is sensitive to scale, with significantly lower costs expected for larger farms. In this research project, significant advances were made in improving raceway algal productivity and fuel production from algae biomass, while also improving process economics. These outcomes brought the algal biofuel technology closer to being a sustainable and marketable process. The remainder of this executive summary is organized into the following six primary project tasks: (1) to optimize biomass productivity for a selected strain at Delhi, (2) to maximize algal productivity and harvesting efficiency in Delhi pilot ponds, (3) a full-scale raceway hydraulic characterization, (4) biomass processing to biofuel intermediates, and (5) scale-up engineering analysis, modeling, and planning.

09 BIOMASS FUELS↗
DOE OSTI2018

Innovation in Contracting Strategy for a Master Services Agreement for Remediation of Low Level Radioactive Waste - 18381

The Port Hope Area Initiative (PHAI) is a federal environmental clean-up program. Its mandate is the remediation and local, long-term, safe management of approximately 1.7 million cubic metres of historic low-level radioactive waste in the adjacent communities of Port Hope and Port Granby in Southern Ontario, Canada. The PHAI is being undertaken by Canadian Nuclear Laboratories (CNL), on behalf of Atomic Energy of Canada Limited, a federal Crown corporation. It is currently one of the largest environmental remediation projects in Canada. The safety of workers, the public and the environment while delivering the PHAI on time and within budget is CNL's number one priority. The PHAI is being carried out as two projects - the Port Hope Project and the Port Granby Project. The Port Hope Project is the larger of the two and includes the cleanup of approximately 1.2 million cubic metres of historic waste from several locations, including the Port Hope Harbour, a closed municipal landfill and approximately 800 residential properties. This complex project requires contracting the services of qualified, skilled and experienced environmental remediation contractors to meet the diverse needs of the myriad tasks that comprise the remediation and restoration of all properties. This paper will highlight how the CNL contracting services team developed an innovative approach to a contracting strategy designed to deliver the safe execution of work and keep the project on time and within budget. The approach addresses the complexities of a scope of work that consists of multiple work packages to be executed both concurrently and in tandem, and that require highly specialized trades/skills, as well as high-level project management expertise to ensure seamless coordination among the various contractors. The author will discuss CNL's strategy to engage the market with a Request for Expression of Interest to identify potential qualified suppliers and gauge their level of interest, issue a Request for Prequalification (RFPQ) to determine eligible contractors and, ultimately, issue a Request for Proposal for a Master Services Agreement (MSA) that would competitively evaluate each contractor's direct experience, technical expertise, quality management programs, safety systems compliance and track record. Using CNL's experience as a case study, the paper will highlight how an innovative approach can positively affect project timelines by describing how CNL addressed the challenge associated with the limited time available to implement procurement processes and deliver a series of executed agreements while ensuring that work would begin on time and key project milestones would be met. The author will summarize how CNL's strategy put the project back on schedule, without compromising the process guideline/requirements, and ensured that a qualified and experienced set of contractors, committed to a strong safety culture, will be available to perform the work required when the cleanup in the Port Hope community begins in 2018. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

XPRESS: eXascale PRogramming Environment and System Software

The XPRESS Project is one of four major projects of the DOE Office of Science Advanced Scientific Computing Research X-stack Program initiated in September, 2012. The purpose of XPRESS is to devise an innovative system software stack to enable practical and useful exascale computing around the end of the decade with near-term contributions to efficient and scalable operation of trans-Petaflops performance systems in the next two to three years; both for DOE mission-critical applications. To this end, XPRESS directly addresses critical challenges in computing of efficiency, scalability, and programmability through introspective methods of dynamic adaptive resource management and task scheduling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Designing and prototyping extensions to the Message Passing Interface in MPICH

As HPC system architectures and the applications running on them continue to evolve, the MPI standard itself must evolve. The trend in current and future HPC systems toward powerful nodes with multiple CPU cores and multiple GPU accelerators makes efficient support for hybrid programming critical for applications to achieve high performance. However, the support for hybrid programming in the MPI standard has not kept up with recent trends. The MPICH implementation of MPI provides a platform for implementing and experimenting with new proposals and extensions to fill this gap and to gain valuable experience and feedback before the MPI Forum can consider them for standardization. Here, in this work, we detail six extensions implemented in MPICH to increase MPI interoperability with other runtimes, with a specific focus on heterogeneous architectures. First, the extension to MPI generalized requests lets applications integrate asynchronous tasks into MPI’s progress engine. Second, the iovec extension to datatypes lets applications use MPI datatypes as a general-purpose data layout API beyond just MPI communications. Third, a new MPI object, MPIX_Stream, can be used by applications to identify execution contexts beyond MPI processes, including threads and GPU streams. MPIX stream communicators can be created to make existing MPI functions thread-aware and GPU-aware, thus providing applications with explicit ways to achieve higher performance. Fourth, MPIX Streams are extended to support the enqueue semantics for offloading MPI communications onto a GPU stream context. Fifth, thread communicators allow MPI communicators to be constructed with individual threads, thus providing a new level of interoperability between MPI and on-node runtimes such as OpenMP. Lastly, we present an extension to invoke MPI progress, which lets users spawn progress threads with fine-grained control to adapt the communication performance to their application designs. We describe the design and implementation of these extensions, provide usage examples, and highlight their expected benefits with performance results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Novel Serpentine Robot Combinations for Inspection in Hard-to-Reach Areas of Damaged or Decommissioned Structures - 17335

U.S. government agencies, particularly the Dept. of Energy, need robotic tools to handle and inspect high-consequence materials - materials for which mishandling would result in great risk to both application operators and the general public. The remediation and documentation of nuclear waste has become a problem of national significance and it cannot be addressed without robotic tools. The use of robots bypasses the danger and decreases the preparation time to handle harmful materials. In the 1980's and 90's, the US Dept. of Energy (DOE) invested heavily in robotic technologies as part of a comprehensive program of research and development aimed at enabling safer and more efficient cleanup of nuclear waste sites. For the next generation of harder, more complex clean-up problems, there is a clear need for more R and D. There is a clear need for flexible, quickly deployable robotic technologies that can be configured to respond to unforeseen situations -- or can be purpose-built for planned activities -- while keeping human workers safe, yet effective. Modularity and inter-operability are core capabilities for inspection tasks in contaminated facilities with a large variety of inspection problems. With any tool, familiarity breeds ingenuity, and ingenuity leads to new innovations in efficiency, effectiveness, safety, and performance. For example, the simple screwdriver can be held fourteen different ways by an experienced machinist who knows exactly what he or she wants to accomplish at any given moment. As a tool, robots are no different. To maximize the efficiency, effectiveness, safety and performance, redeployment and reuse of familiar tools is essential. Modularity can assist with re-deployment and modularity manifests itself in both hardware and software. In some applications of inspection of high-consequence materials, a common concern has been the simplicity of the tool -- often correlated with cost (which is not always accurate) -- in case it becomes unrecoverable. In the case of robots, which have complex user interfaces and complex dynamics of interaction, the lack of familiarity can lead to clumsy operations and reduced accumulation of knowledge. As a result, while incremental successes may be achieved with sequential uses of different robots, there often is little knowledge gain that is generalizable across multiple uses. Total cost often goes down when a more sophisticated, but more familiar tool, can be used more frequently.An example is the inspection of the H-Canyon Exhaust Air Tunnel at the Savannah River Site nuclear waste facility in the United States [1]. This is a particularly nasty environment, due to the acidic gases, large amounts of erosion and debris, and wet, mucky puddles. Over the past twelve years, six inspections have been attempted with five different robotic vehicles. In fact, these inspections have been successful with their limited, but progressively increasing objectives, although most robots have been abandoned in the tunnel. While each vehicle has cost less than $75,000 (the sacrificial part), the total costs of development have been much higher. The robots used to investigate changed much from iteration to iteration and it is not clear a strong body of generalizable expertise was built up across trials. The authors of this study demonstrated the combination of two types of modular, serpentine, re-configurable robots for locomotion over complex terrains and the inspection of hard-to-reach areas. The MOTHERSHIP is a tread/limb/serpentine hybrid robot design for locomotion over complex terrains, while the CMU snake robot provides highly articulated inspection of highly confined spaces. The demonstration at the Portsmouth Gaseous Diffusion Plant involves a combination of the two whereby gross locomotion is achieved with the MOTHERSHIP and the CMU Snake deploys a sensor package to gather data from behind and under obstacles. Although statically configured in its present state, the combined robot is built of individual modules for which reconfiguration has been demonstrated in both labs at Purdue and CMU. In future work, much higher degrees of reconfiguration and re-purposing of both software and hardware are easily achievable with these unique platforms. (authors)

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