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Short-term solar irradiance forecasting via satellite/model coupling

Here, the short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simply as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m 2 .

14 SOLAR ENERGY↗

Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems

An effort to design and build a modeling and simulation framework to assess the economic viability of Nuclear Hybrid Energy Systems (NHES) was undertaken in fiscal year 2015 (FY15). The purpose of this report is to document the various tasks associated with the development of such a framework and to provide a status on its progress. Several tasks have been accomplished. First, starting from a simulation strategy, a rigorous mathematical formulation has been achieved in which the economic optimization of a Nuclear Hybrid Energy System is presented as a constrained robust (under uncertainty) optimization problem. Some possible algorithms for the solution of the optimization problem are presented. A variation of the Simultaneous Perturbation Stochastic Approximation algorithm has been implemented in RAVEN and preliminary tests have been performed. The development of the software infrastructure to support the simulation of the whole NHES has also moved forward. The coupling between RAVEN and an implementation of the Modelica language (OpenModelica) has been implemented, migrated under several operating systems and tested using an adapted model of a desalination plant. In particular, this exercise was focused on testing the coupling of the different code systems; testing parallel, computationally expensive simulations on the INL cluster; and providing a proof of concept for the possibility of using surrogate models to represent the different NHES subsystems. Another important step was the porting of the RAVEN code under the Windows™ operating system. This accomplishment makes RAVEN compatible with the development environment that is being used for dynamic simulation of NHES components. A very simplified model of a NHES on the electric market has been built in RAVEN to confirm expectations on the analysis capability of RAVEN to provide insight into system economics and to test the capability of RAVEN to identify limit surfaces even for stochastic constraints. This capability will be needed in the future to enforce the stochastic constraints on the electric demand coverage from the NHES. The development team gained experience with many of the tools that are currently envisioned for use in the economic analysis of NHES and completed several important steps. Given the complexity of the project, preference has been given to a structural approach in which several independent efforts have been used to build the cornerstone of the simulation framework. While this is good approach in establishing such a complex framework, it may delay reaching more complete results on the performance of analyzed system configurations. The integration of the previously reported exergy analysis approach was initially proposed as part of this milestone. However, in reality, the exergy-based apportioning of cost will take place only in a second stage of the implementation since it will be used to properly allocate cost among the different NHES subsystems. Therefore, exergy does not appear at the level of the main drivers in the analysis framework; the latter development of the base framework is the focus of this report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Destructive Examination of Shipping Package 9975-02019

Destructive and non-destructive examinations have been performed on the components of shipping package 9975-02019 as part of a comprehensive SRS surveillance program for plutonium material stored in the K-Area Complex (KAC). During the field surveillance inspection of this package in KAC, two non-conforming conditions were noted: the axial gap of 1.577 inch exceeded the 1 inch maximum criterion, and two areas of dried glue residue were noted on the upper fiberboard subassembly. This package was subsequently transferred to SRNL for more detailed inspection and destructive examination. In addition to the conditions noted in KAC, the following conditions were noted: - Numerous small spots of corrosion were observed along the bottom edge of the drum. - In addition to the smeared glue residue on the upper fiberboard subassembly, there was also a small dark stain. - Mold was present on the side and bottom of the lower fiberboard subassembly. Dark stains from elevated moisture content were also present in these areas. - A dark spot with possible light corrosion was observed on the primary containment vessel flange, and corresponding rub marks were observed on the secondary containment vessel ID. - The fiberboard thermal conductivity in the radial orientation was above the specified range. When the test was repeated with slightly lower moisture content, the result was acceptable. The moisture content for both tests was within a range typical of other packages in storage. The observed conditions must be fully evaluated by KAC to ensure the safety function of the package is being maintained. Several factors can contribute to the concentration of moisture in the fiberboard, including higher than average initial moisture content, higher internal temperature (due to internal heat load and placement within the array of packages), and the creation of additional moisture as the fiberboard begins to degrade.

42 ENGINEERING↗

Design of Multi-Stage Solvent Extraction Process for Separation of Rare Earth Elements

Flowsheet design and stage determination for the separation of rare earth elements (REEs) using solvent extraction (SX) is a challenging task because of the chemical similarity of the REEs. Low separation factors between the elements and complex equilibrium chemistry provide unique challenges to designing an efficient flowsheet for the separation of elements. The multi-stage nature of the SX process adds further complexity, making the assessment of products for a proposed design and stage combination difficult. Therefore, to develop a SX flowsheet, it is essential to quantify the performance for various design and separation conditions. This paper attempts to address the challenge by utilizing an equilibrium and process modeling approach. Results from a bench-scale study performed on a 10 g/L rare earth salt mixture were used in studying the extraction/stripping behavior and developing equilibrium models. DEHPA with TBP as a phase modifier was used as an extractant, while hydrochloric acid was utilized as a stripping agent. The results obtained were used in developing extraction/stripping models, which were integrated into a process framework of a SX train in a Matlab/Simulink environment. The models were programmed as a function block routine and used for developing a flowsheet, which was simulated for differing separation and design conditions. To identify optimum stage combinations, a particle swarm optimization (PSO) routine was developed and implemented for each SX train. Recovery and purity of elements of interest were used as objective function criteria. The stage combination leading to the minimization of the objective function was used to identify the optimum stage combination for a series of SX trains to attempt a balance of purity and recovery. The models and optimization method were implemented to separate a feed mixture containing REEs, which indicated that 99.52 and 85.41 percent purity is achievable for Yttrium and Lanthanum separation using 8-12-3 and 10-3-5 stage combination for loading, scrubbing, and striping. The model also indicated difficult separability between neodymium, praseodymium, and cerium.

Srivastava, Vaibhav (ORCID:0000000212645987)↗

A Novel Equivalent Model of Active Distribution Networks Based on LSTM

Dynamic behaviors of distribution networks are of great importance for the power system analysis. Nowadays, due to the integration of the renewable energy generation, energy storage, plug-in electric vehicles, and distribution networks turn from passive systems to active ones. Hence, the dynamic behaviors of active distribution networks (ADNs) are much more complex than the traditional ones. The research interests how to establish an accurate model of ADNs in modern power systems are drawing a great deal of attention. In this paper, motivated by the similarities between power system differential algebraic equations and the forward calculation flows of recurrent neural networks (RNNs), a long short-term memory (LSTM) RNN-based equivalent model is proposed to accurately represent the ADNs. First, the adoption reasons of the proposed LSTM RNN-based equivalent model are explained, and its advantages are analyzed from the mathematical point of view. Then, the accuracy and generalization performance of the proposed model is evaluated using the IEEE 39-Bus New England system integrated with ADNs in the study cases. Here, it reveals that the proposed LSTM RNN-based equivalent model has a generalization capability to capture the dynamic behaviors of ADNs with high accuracy.

42 ENGINEERING↗

COVID-19 biomarkers based on respiratory microbiome content

COVID-19 patient care management would greatly benefit from new tools that enable accurate assessment of disease severity and stage, potentially enabling a personalized medicine approach. Detection of the SARS-CoV-2 virus itself, or even quantitation of viral loads, is not sufficient for accurate assessment of disease state beyond diagnosis of infection [eg, doi:10.1093/cid/ciaa344]. Levels of usual suspect protein biomarkers associated with host response to infection [eg, C-reactive protein (CRP); cytokines like IL-6, TNF-alpha, and IL-10; complement proteins like C3a and C5a], and of individual blood cell types (eg, leukocytes, lymphocytes, and subsets thereof), show limited correlation with disease severity and stage, with high patient-to-patient and study-to-study variability [eg, doi:10.1093/cid/ciaa248]. High-dimensional panels of biomarkers should have greater predictive power and resilience to unavoidable sources of variability; however, their assembly from proteins and cell types is extremely difficult, due to technical limitations in analyte measurement, especially with regard to starting material requirements and detection sensitivity. Host response profiling through Next Generation Sequencing (NGS) of gene expression patterns (ie, RNA-Seq) is a promising approach, but at the time of this project there were only two publicly available datasets of relevance [doi:10.1093/cid/ciaa203, doi:10.1080/22221751.2020.1747363], and close inspection of them revealed that each had at least one major flaw that severely undermined its value in supporting robust analysis of host response to SARS-CoV- 2 infection. However, the first of these studies [doi:10.1093/cid/ciaa203] fortuitously collected NGS data not only from host cells, but also from bacteria present in bronchoalveolar lavage fluid (BALF) recovered from COVID-19 patients; and because the respiratory microbiome (in terms of bacterial species content) is far less complex than the human transcriptome, the NGS data collected were sufficient to provide coverage depth supporting robust analysis. Surprisingly, the authors of the study did not carry out a detailed analysis of these data and their potential for revealing important new information about COVID-19. Therefore, we carried out a meta-analysis of the dataset as a first step in evaluating the potential for profiling of respiratory microbiome dynamics as a means of accurately assessing COVID-19 disease state.

59 BASIC BIOLOGICAL SCIENCES↗

Printable Fiber Reinforced Cement Composites – Feasibility Study

Additive manufacturing is enabling the manufacturability of structures with previously unattainable complexity or functionality, and there is growing interest in additive manufacturing of “printed” concrete structures. The focus of this Phase 1 Technical Collaboration (TC) project was to evaluate feasibility of printing hybrid cement composite structures reinforced with textile carbon fibers (tCF). This project leverages other (non-IACMI) projects on cement formulation and printing process development, as well as on the production process for tCF. This project’s primary focus was to explore cement composite mix design with textile carbon fibers to be manufactured by MonteFibre (TC partner) and evaluate suitable fiber-matrix interface or sizing for cement composites working with Michelman (TC Partner). This project supports IACMI’s goal of reducing the cost and embodied energy of carbon fiber composites. Cost is one of the fundamental challenges to carbon fiber reinforced cement composites. Cement is an extremely inexpensive material (approximately $\$$0.05/lb). Adding 1 wt% of conventional carbon fiber to cement quadruples its cost. Therefore, the need to use low-cost carbon fiber and ensure that the additional cost of the carbon fiber has a greater cost benefit to the final product. This was the first preliminary evaluation to integrate tCF reinforcement in cement composites, and such potential tCF utilization should significantly reduce materials cost. Cement composite production is energy and emissions intensive, thus by strengthening it less material will be required. Hence, the embodied energy and production time of the resulting structures will be reduced. Additionally, integrating these new materials into additive processes can enable selective use of the material in high load or stress areas. It is noteworthy that past work in this field of fiber reinforced cement composites did not consider the optimization of fiber-matrix interface using suitable sizing. Carbon fiber reinforcement offers potential added benefits of thermal conductivity (which affects cure rate) and flow behavior that could provide opportunities for site specific utilization of carbon fiber on hybrid cement structures (e.g. use the fiber reinforcement on outer surfaces to enhance strength and modulus and then infiltrating the internal structures with conventional concrete). MonteFibre was the industry lead and planned on supplying the tCF for this project. However, during the short Phase-1 duration of this project, MonteFibre was unable to produce tCF for this project due to manufacturing plant being off-line throughout the course of the project. The project team decided to pursue an alternate option which involved demonstrating printable concrete with steel fibers by the ORNL lead, Dr. Brian Post. The University of Tennessee collaboration team focused on evaluating the suitable chemical sizing for carbon fibers working with Michelman and also developed methods for material characterization of cement-based composites to evaluate the material response for compression, shear, flexure, and tension. The two milestones for University of Tennessee, Knoxville were realized related to identification of one sizing suitable for carbon fiber reinforced cement composite and developing data associated with mechanical behavior of unreinforced (neat) and carbon fiber reinforced cement composites. ORNL could not complete the task of carbon fiber reinforced printed cement composites due to the reasons mentioned earlier, but was able to replace tCF with steel fibers to demonstrate the feasibility of printing with fiber reinforced cement composites. The Project team reviewed possible sizing chemistry available in collaboration with Michelman for use on carbon fiber reinforcement in cement composites and concrete applications. Our initial goal was to identify a sizing most promising for formulation with textile carbon fibers (tCF) to deliver excellent mechanical properties in composite material state. Since tCF was not available for this project as originally envisioned, the team continued this task to identify a suitable sizing for carbon fiber applications by applying such sizing to lower cost carbon fibers currently available commercially from Zoltek called Panex fibers. At a future time this can be optimized for textile carbon fibers from Montefibre. The bulk of previous work on carbon fiber reinforced cement has neglected the importance of fiber-matrix adhesion on mechanical properties of the cement composite and identifying this missing link was an important accomplishment for future research. Tensile behavior of fiber reinforced concrete is important to evaluate in order to realize the dream of concrete products that do not need reinforcing steel. Important sample preparation and testing procedures were addressed in this study and it was concluded that substantial improvements in tensile behavior, without compromising compressive strength, and improved ductility can result from the use of carbon fiber reinforcement.

36 MATERIALS SCIENCE↗

Effect of proteoglycans at interfaces as related to location, architecture, and mechanical cues

Covalently bound functional GAGs orchestrate tissue mechanics through time-dependent characteristics. The role of specific glycosaminoglycans (GAGs) at the ligament-cementum and cementum-dentin interfaces within a human periodontal complex were examined. Matrix swelling and resistance to compression under health and modeled diseased states was investigated. The presence of keratin sulfate (KS) and chondroitin sulfate (CS) GAGs at the ligament-cementum and cementum-dentin interfaces in human molars (N = 5) was illustrated by using enzymes, atomic force microscopy (AFM), and AFM-based nanoindentation. Furthermore, the change in physical characteristics of modeled diseased states through sequential digestion of keratin sulfate (KS) and chondroitin sulfate (CS) GAGs was investigated. One-way ANOVA tests with P < 0.05 were performed to determine significant differences between groups. Additionally, the presence of mineral within the seemingly hygroscopic interfaces was investigated using transmission electron microscopy. Immunohistochemistry (N = 3) indicated presence of biglycan and fibromodulin small leucine rich proteoglycans at the interfaces. Digestion of matrices with enzymes confirmed the presence of KS and CS GAGs at the interfaces by illustrating a change in ti ssue architecture and mechanics. A significant increase in height (nm), decrease in elastic modulus (GPa), and tissue deformation rate (nm/s) of the PDL-C attachment site (215 ± 63-424 ± 94 nm; 1.5 ± 0.7-0.4 ± 0.2 GPa; 21 ± 7-48 ± 22 nm/s), and cementum-dentin interface (122 ± 69-360 ± 159 nm; 2.9 ± 1.3-0.7 ± 0.3 GPa; 18 ± 4-30 ± 6 nm/s) was observed. The sequential removal of GAGs indicated loss in intricate structural hierarchy of hygroscopic interfaces. From a mechanics perspective, GAGs provide tissue recovery/resilience. Our results provide insights into the role of GAGs toward conserved tooth movement in the socket in response to mechanical loads, and modulation of potentially deleterious strain at tissue interfaces.

59 BASIC BIOLOGICAL SCIENCES↗

Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles

Off-road vehicles, such as wheel loaders, excavators, and harvesters, are extensively utilized across a wide range of industries, including construction, agriculture, and mining. These machines have become indispensable in supporting the day-to-day operational needs of a nation, playing a critical role in various sectors' infrastructure and productivity. However, despite their utility, off-road vehicles are significant consumers of fossil fuels, resulting in substantial emissions that contribute to environmental degradation. This highlights the pressing need for research and technological advancements aimed at improving their energy efficiency and reducing their carbon footprint. There are, however, two primary challenges that must be addressed to achieve these goals. First, off-road vehicles typically perform both driving and working tasks simultaneously, which introduces a high level of complexity into their overall dynamic systems. Analysis the interactions between these functions is challenging. Second, research into off-road vehicles is inherently interdisciplinary, demanding expertise across several domains such as fluid power systems, vehicle dynamics, control theory, optimization techniques, and real-world implementation. Recognizing these challenges, we proposed the project titled "Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles" as a comprehensive solution to enhance fuel efficiency while simultaneously improving productivity. This project specifically focuses on autonomous off-road vehicles, with particular attention to wheel loaders, and seeks to develop novel methods to optimize energy consumption without sacrificing operational performance. The project integrates real-time control algorithms, vehicle dynamics modeling, and co-optimization of powertrain system and vehicle system to achieve these goals. Our optimization strategy dynamically co-optimizes critical parameters at both the powertrain and vehicle levels, including vehicle speed, working tool movements, powertrain dynamics, and engine operations in real-time. To streamline this optimization process, we developed a vehicle model that captures the key dynamics while significantly enhancing computational efficiency. This allows the system to intelligently minimize fuel consumption, all while maintaining or even improving productivity through real-time calculations during various off-road operations. To validate the effectiveness of this energy optimization method, we introduced a state-of-the-art Hardware-in-the-Loop (HIL) testbed. This reconfigurable testbed seamlessly integrates the actual engine with virtual models of the wheel loader's subsystems, allowing for accurate emulation of real-world operational loads and environments. By simulating these conditions, the HIL testbed enables us to evaluate the wheel loader’s performance under diverse working scenarios, ensuring the developed solution is applicable in real-world operations. This testbed proved to be instrumental in validating the optimization algorithms and demonstrating the system's practical effectiveness. During the evaluation and testing phase, we employed the HIL testbed to rigorously assess the energy savings and productivity improvements generated by the optimized system. The results were highly encouraging, revealing that the automated wheel loader achieved over 30% fuel savings compared to traditional, human-operated cycles, with comparable or even enhanced levels of productivity. The insights gained from this HIL-based testing provided critical validation of our approach and highlighted the potential for deploying these optimized autonomous technologies in real-world off-road vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

Center for Efficiency in Sustainable Energy Systems

The main goal of the Center for Efficiency in Sustainable Energy Systems is to produce a methodology that evaluates a variety of energy systems. Task I. Improved Energy Efficiency for Industrial Processes: This task, completed in partnership with area manufacturers, analyzes the operation of complex manufacturing facilities to provide flexibilities that allow them to improve active-mode power efficiency, lower standby-mode power consumption, and use low cost energy resources to control energy costs in meeting their economic incentives; (2) Identify devices for the efficient transformation of instantaneous or continuous power to different devices and sections of industrial plants; and (3) use these manufacturing sites to demonstrate and validate general principles of power management. Task II. Analysis of a solid oxide fuel cell operating on landfill gas: This task consists of: (1) analysis of a typical landfill gas; (2) establishment of a comprehensive design of the fuel cell system (including the SOFC stack and BOP), including durability analysis; (3) development of suitable reforming methods and catalysts that are tailored to the specific SOFC system concept; and (4) SOFC stack fabrication with testing to demonstrate the salient operational characteristics of the stack, including an analysis of the overall energy conversion efficiency of the system. Task III. Demonstration of an urban wind turbine system: This task consists of (1) design and construction of two side-by-side wind turbine systems on the YSU campus, integrated through power control systems with grid power; (2) preliminary testing of aerodynamic control effectors (provided by a small business partner) to demonstrate improved power control, and evaluation of the system performance, including economic estimates of viability in an urban environment; and (3) computational analysis of the wind turbine system as an enabling activity for development of smart rotor blades that contain integrated sensor/actuator/controller modules to enhance energy capture and reduce aerodynamic loading and noise by way of virtual aerodynamic shaping. Accomplishments: Task I. Improved Energy Efficiency for Industrial Processes: We organized an energy management training session held on February 22, 2011, which was advertised through a regional manufacturing association to provide wide-ranging notification. Over two dozen companies were represented a the seminar, ranging from heavy manufacturing businesses with $5,000,000 per year energy expenses, to small, light manufacturing facilities. Task 2. Landfill Fuel Cell Power Generation Solid Oxide Fuel Cells (SOFCs) were constructed and evaluated as a means of obtaining electrical energy from landfill gas. Analysis of landfill gas. Attempts at collecting gas samples at the landfill and evaluating them on campus were still unsuccessful. Even a Teflon® sample bag would lose its H2S content. Evaluation of Gas Clean-up We consider this a confirmation of the CO2 effect on the solubility of H2S in water making much less sulfide available for the photocatalyst. It also means that another method should be employed to clean up landfill gas. Nonetheless, composition of impurities in landfill gas was reduced sufficiently to allow successful operation of the test fuel cell. Comparison to a PEM fuel cell system. If a PEMFC were to be operated with landfill gas as the fuel, the gas would have to be treated for sulfur removal, and then processed in a reformer large enough to drive the equilibrium far toward the products, so that negligible CO would flow into the fuel cell. Analysis of a fuel cell running on landfill gas. Using a Gow-Mac gas chromatograph with a thermal conductivity detector, unambiguous determination of CO can be made, at least as a primary constituent Task 3: Task 3 Plasma Controlled Turbine Blades Wind Turbine Selection. After carefully reviewing the various model available in the market the team selected the ARE 110 (2.5kW). The ARE 110 provides a very long life with little maintenance due to their relatively low rotational speeds (low RPM). The turbines large swept area (10.2ms2/110sq.ft), high-efficiency blades, purpose built alternator, and optimized power electronics ensure maximum energy capture from a wide range of wind speeds. Two wind turbines were installed side-by-side at the Melnick Hall site to compare their performance. Evaluate and Optimize Aerodynamically Enhanced Turbine Blades Due to delays in the installation of the wind turbines, no actual data was obtained within the contract period. At this time, the turbines are installed and operational at YSU with standard blades. We are in contact with Orbital Research and in discussion as to how best the required data can be obtained.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Extended Sleeve Products Allow Control and Monitoring of Process Fluid Flows Inside Shielding, Behind Walls and Beneath Floors - 13041

Throughout power generation, delivery and waste remediation, the ability to control process streams in difficult or impossible locations becomes increasingly necessary as the complexity of processes increases. Example applications include radioactive environments, inside concrete installations, buried in dirt, or inside a shielded or insulated pipe. In these situations, it is necessary to implement innovative solutions to tackle such issues as valve maintenance, valve control from remote locations, equipment cleaning in hazardous environments, and flow stream analysis. The Extended Sleeve family of products provides a scalable solution to tackle some of the most challenging applications in hazardous environments which require flow stream control and monitoring. The Extended Sleeve family of products is defined in three groups: Extended Sleeve (ESV), Extended Bonnet (EBV) and Instrument Enclosure (IE). Each of the products provides a variation on the same requirements: to provide access to the internals of a valve, or to monitor the fluid passing through the pipeline through shielding around the process pipe. The shielding can be as simple as a grout filled pipe covering a process pipe or as complex as a concrete deck protecting a room in which the valves and pipes pass through at varying elevations. Extended Sleeves are available between roughly 30 inches and 18 feet of distance between the pipeline centerline and the top of the surface to which it mounts. The Extended Sleeve provides features such as ± 1.5 inches of adjustment between the pipeline and deck location, internal flush capabilities, automatic alignment of the internal components during assembly and integrated actuator mounting pads. The Extended Bonnet is a shorter fixed height version of the Extended Sleeve which has a removable deck flange to facilitate installation through walls, and is delivered fully assembled. The Instrument Enclosure utilizes many of the same components as an Extended Sleeve, yet allows the installation of process monitoring instruments, such as a turbidity meter to be placed in the flow stream. The basis of the design is a valve body, which, rather than having a directly mounted bonnet has lengths of concentric pipe added, which move the bonnet away from the valve body. The pipe is conceptually similar to an oil field well, with the various strings of casing, and tubing installed. Each concentric pipe provides a required function, such as the outermost pipes, the valve sleeve and penetration sleeve, which provide structural support to the deck flange. For plug valve based designs, the next inner pipe provides compression on the environmental seals at the top of the body to bonnet joint, followed by the innermost pipe which provides rotation of the plug, in the same manner as an extended stem. Ball valve ESVs have an additional pipe to provide compressive loading on the stem packing. Due to the availability of standard pipe grades and weights, the product can be configured to fit a wide array of valve sizes, and application lengths, with current designs as short as seven inches and as tall as 18 feet. Central to the design is the requirement for no special tools or downhole tools to remove parts or configure the product. Off the shelf wrenches, sockets or other hand tools are all that is required. Compared to other products historically available, this design offers a lightweight option, which, while not as rigidly stiff, can deflect compliantly under extreme seismic loading, rather than break. Application conditions vary widely, as the base product is 316 and 304 stainless steel, but utilizes 17-4PH, and other allows as needed based on the temperature range and mechanical requirements. Existing designs are installed in applications as hot as 1400 deg. F, at low pressure, and separately in highly radioactive environments. The selection of plug versus ball valve, metal versus soft seats, and the material of the seals and seats is all dependent on the application requirements. The design of the Extended Sleeve family of products provides a platform which solves a variety of accessibility problems associated with controlling process flow streams in remote, hard to reach locations in harsh environments. Installation of the equipment described has shown to allow access to flow streams that otherwise would require exceptional means to access and control. The Extended Sleeve family of products provides a scalable solution to both control and monitor process fluid flow through shielding, walls or floors when direct connection is advantageous. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Optimization of Advanced Steels for Cyclic Operation through an Integration of Material Testing, Modeling and Novel Component Test Validation

The efforts in this project were focused in three primary objectives, provided below: • To develop the needed microstructural processing and performance relationships and associated material models for specific constituents in fabricated weldments (such as the parent material, heat affected zone regions and weld metal), • Apply these metallurgical relationships through modeling of a welded pressure bearing power plant component subjected to cyclic operational conditions under both mechanical and thermal loading, and • Validate the model through novel structural feature and component tests. An attempt was made to optimize the heat treatment schedule to reduce or eliminate the presence of boron nitride (BN) in the matrix of the Grade 92 material. BN has been shown to be a primary nucleation source for creep damage. Proper evaluation of material behavior, and as assessed in this research, included the influence of geometric notches (such as those from poor fabrication or design) and metallurgical notches (such as weldments or poorly processed parent material). Better practice methodologies were implemented in the theoretical design of a high-temperature, critical component for cyclic operation. It was demonstrated that vessel testing can be reliably performed and provides a critical link between standard testing, structural assessment and validation. While the goal of an improved Grade 92 steel was not achieved in this project, there is considerable value in applying the documented testing and assessment methodologies to assess material and/or component behavior. This is especially true for materials and/or designs which are expected to be subjected to flexible operating modes. Design of a cycling state of the art thick wall steam header for long term operation with a state of the art ferritic steel was a task in this project. Implementation of that task showed how many factors including plant operating mode, creep strength, creep ductility, fatigue strength, and resistance to crack growth should be considered and evaluated to properly design high temperature components for long term service (200,000 operating hours or more) in a modern Fossil energy power plant. The current ASME non-nuclear boiler design code does not mandate this level of complex analysis nor does it provide all the metallurgical and mechanical properties data needed to perform this kind of design analysis.

20 FOSSIL-FUELED POWER PLANTS↗

Case Study: Nuclear-Renewable-Water Integration in Arizona

This document reports the application of the N-R HES software framework to a case study for Arizona Public Service (APS); the manager and part owner of the Palo Verde (PV) nuclear power plant. The case study is a work in progress of which this report presents a detailed description of the current model input data, assumptions and the corresponding results produced by the developed software framework. The goal of the report is, that with this information APS (together with INL) should be able to identify where more detailed data and more accurate model assumptions are necessary to reproduce all driving physical and economic phenomena in order to capture enough complexity of the reality to allow APS to use the results for their strategic decisions. The N-R HES software framework started being developed at INL two years ago [ref]. The framework has reached some level of maturity so that it can be applied to more than simple demonstration cases, e.g. real industry problems. Nevertheless, more capabilities are constantly added to accommodate the special needs of these challenging real life problems. The N-R HES framework is built on top of the RAVEN code [ref] and uses it as driver and workflow manager for all calculations. The framework has specifically been developed for the economic assessment of N-R HES systems. There are four main cornerstones of the N-R HES simulation framework: 1) generation of stochastic time series, 2) a probabilistic analysis and optimization set of algorithms available in RAVEN, 3) a set of models for representation of the physical behavior of N-R HES, and 4) a RAVEN plug-in that maps physical performance into economic performance called CashFlow. Within this framework, a broad spectrum of questions related to N-R HES can be addressed. One of the challenges currently of high interest is that the increasing penetration of variable renewables is altering the profile of the net demand (demand after removing all non curtailable renewable energy sources), with which the other generators on the grid have to cope. The N-R HES software framework is capable to analyze the potential feasibility of mitigating the resultant volatility in the net electricity demand. One possible solution to that problem currently intensively studied by the energy industry is adding stabilizing loads to the grid. These loads can be external industrial processes that are able to ramp production up and down quickly or adding variable internal loads that will lift the base load of the power plant. The latter is a possible solution currently studied by APS. APS if currently anticipating several challenges that will likely arise in the near future. One of them is, as mentioned, coping with the rapid growth of variable renewable energy (VRE) sources put on the grid. Although APS can sell its electricity for a fixed retail price to cover the local demand first, it also sells electricity in excess of the local demand at the Palo Verde energy hub. Due to the growing VRE penetration, the Palo Verde hub electricity spot price is negative more and more frequently. To mitigate this price volatility, APS is seeking to add more base load, so that the quantity of excess energy to be sold for prices potentially less than the internal retail price or even negative prices at the hub is reduced. A second challenge APS is facing is that their cooling water acquisition contract with the Sub Regional Operating Group (SROG) will expire soon and a renewal can only be done for a significantly higher price of the water. Therefore, APS is also seeking for alternative sources for their cooling water. An opportunity currently under investigation is to pump a limited quantity of brackish water from the regional ground water. Although much cheaper than the water from the new SROG contract, the salinity of the brackish water is so high that a blend of brackish and SROG water would need additional treatment to improve its quality for use in the cooling towers. An on-site reverse osmosis (RO) desalination plant is envisaged to reduce the salinity to an acceptable level. This report investigates the economic impact of such an RO plant. As one can see, the RO plant would help with both problems APS is facing: First, it would rise the APS base load helping to mitigate VRE induced hub price volatility. From this perspective, the RO plant can be seen as a stabilizing load on the grid as would be any other industrial process. Second, the RO’s goods, e.g. the clean water produced can be used by APS itself for a (hopefully) lower cost than 100% SROG water would be. The report will first describe the APS water procurement strategy in detail and lay out the possible alternative scenarios studied in this document. This is covered in Chapter 2. Next, in Chapter 3, the APS case model developed within the N-R HES software framework is described. This chapter includes also a description of the needed framework developments to accommodate the APS study.

97 MATHEMATICS AND COMPUTING↗

A finite element/level set model of polyurethane foam expansion and polymerization

Polyurethane foams are used widely for encapsulation and structural purposes because they are inexpensive, straightforward to process, amenable to a wide range of density variations (1 lb/ft3 - 50 lb/ft3), and able to fill complex molds quickly and effectively. Computational model of the filling and curing process are needed to reduce defects such as voids, out-of-specification density, density gradients, foam decomposition from high temperatures due to exotherms, and incomplete filling. This paper details the development of a computational fluid dynamics model of a moderate density PMDI structural foam, PMDI-10. PMDI is an isocyanate-based polyurethane foam, which is chemically blown with water. The polyol reacts with isocyanate to produces the polymer. PMDI- 10 is catalyzed giving it a short pot life: it foams and polymerizes to a solid within 5 minutes during normal processing. To achieve a higher density, the foam is over-packed to twice or more of its free rise density of 10 lb/ft3. The goal for modeling is to represent the expansion, filling of molds, and the polymerization of the foam. This will be used to reduce defects, optimize the mold design, troubleshoot the processed, and predict the final foam properties. A homogenized continuum model foaming and curing was developed based on reaction kinetics, documented in a recent paper; it uses a simplified mathematical formalism that decouples these two reactions. The chemo-rheology of PMDI is measured experimentally and fit to a generalized- Newtonian viscosity model that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. The equations are combined with a level set method to determine the location of the foam-gas interface as it evolves to fill the mold. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics, viscosity, and other material properties are all sensitive to temperature. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including two configurations of a mock structural part and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed for future work.

36 MATERIALS SCIENCE↗

Local Power Impact Experiment Design for a New Fuel Type for use in the Advanced Test Reactor

The Advanced Test Reactor (ATR), and complimentary zero-power ATR Critical (ATRC) reactor, located at Idaho National Labs (INL), are undergoing conversion from Highly Enriched Uranium (HEU) to Low Enriched Uranium (LEU). Both have a variety of testing locations that can receive large variations in flux due to its unique serpentine design, consisting of five lobes (see Figure 1). Initial criticality and power distribution throughout the core are controlled by core-external outer shim control cylinders (OSCCs). Distinct test loops allow for testing at specific temperatures, pressures, and irradiation conditions. The ATR is one of the key nuclear engineering research and testing facilities within the DOE National Laboratory Complex, and the ATRC supports its operation [1]. Currently, the Office of Material Management and Minimization (M3) within the National Nuclear Security Administration of the DOE is working to convert the remaining research reactors, including the ATR, from 93% HEU fuel to 19.75% LEU fuel (LEU) to support non-proliferation [2]. Extensive materials testing at INL and internationally has demonstrated that a high-density uranium molybdenum (U 10Mo) alloy can meet the performance requirements of the remaining high powered research reactors. However, there are many technical challenges to address before the conversion to LEU can be successful, including the accurate characterization of the reactor core physics with LEU fuel. Reactor physics safety evaluations currently use Monte Carlo for the 21st Century (MC21), a continuous-energy Monte Carlo radiation transport code [3]. Existing MC21 models of the ATR and ATRC cores have a validation basis for use in neutronics analyses with HEU fuel. The models are used to support safety analyses that include comparisons to the safety requirements for the reactors. However, the use of the LOWE element in the ATR and ATRC is not currently covered by the current model validation basis. To deploy the new fuel type, extensive computational reactor physics support is necessary to support the use of LOWE in the ATR and ATRC. Therefore, LOWE requires a rigorous validation basis, aligned with that of HEU fuel, that takes advantage of the existing software tools and processes currently used for the ATR and ATRC. The experiment to validate of the MC21 models for determining power, the Power Impact Validation Experiment, will consist of two flux runs in the ATRC, one with fully HEU loading and one with a single LOWE element. Both flux runs will be instrumented with 20 sets of azimuthal fission wires and 3 sets of axial fission wires, as shown in Figure 4. Standard flux run methodology will be used [4]. Power Impact Validation Experiment data will be compared against MC21 calculated data, both for absolute fission rate accuracy and to determine the relative change in fission rates between the two runs. The results of the Power Impact Validation Experiment and subsequent evaluations will provide the validation basis for MC21 for use with LOWE elements. Key features of the Power Impact Validation Experiment include: (1) Two flux runs to allow for LOWE perturbed measurements to be compared to already validated measurements taken from a full core of HEU fuel, (2) Optimization of instrumentation to balance analytical needs with practical considerations (e.g., limited time window to count beta particles from fission products), and (3) Standard ATRC core loading, including both driver positions and flux traps, to minimize cost while remaining representative of typical ATR core loading.

42 ENGINEERING↗

Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods

Advances in computation have brought about significant improvements in creating fast-running high-fidelity simulations of nuclear cores. The BEAVRS benchmark is a highly-detailed PWR specification with two cycles of measured operational data used to validate high-fidelity core analysis methods. This PWR depletion benchmark captures the fine details of the LWR fuel assemblies, burnable absorbers, in-core fission detectors, core loading and shuffling patterns. Specifically, 58 of the 193 assemblies contain in-core detectors with measurements taken over 61 axial positions every month. These detectors are U-235 fission chambers with slightly varying mass of U-235. The collected signals are normalized on a given assembly permitting full core comparisons. The fuel layout for cycle 1 and instrument tube locations for the reactor are given in figures 1 and 2 respectively. Through a series of data processing and comparisons, it was shown that axially integrated radial maps of reaction rates were in close agreement between provided detector data and calculated data. More recently, the focus of the BEAVRS project has been on quantifying uncertainty to further assess the validity of aforementioned results. A close investigation of sources of error shows that uncertainties from operational nuclear data arise primarily from data measurements and processing. While the errors in axial realignment and interpolation seem significant, these sources affect only a small subset of data points near grid spacers and do not persist throughout the entire core. Instead, measurement uncertainty from detector count rates and radial integration dominate the uncertainty in measured data are determined as the most significant sources of error. This uncertainty analysis treated each given burnup step as independent of comparable data at neighboring burnup steps. More recent work has been targeted at understanding how reaction rates vary over time, in order to determine whether calculated reaction rates follow any observable trends. This abstract hones in on transient uncertainty quantification, in order to compare observed data against models for transient behavior. The first section of the paper uses linear regression tools to fit operational data, while the latter portion of the paper explores more complex simulation tools to fit operational data. Ultimately, the BEAVRS benchmark aims to serve as a true non-proprietary international benchmark for the validation of high-fidelity tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of a Macro-Batch Qualification Strategy for the Hanford Tank Waste Treatment and Immobilization Plant

The Savannah River National Laboratory (SRNL) has evaluated the existing waste feed qualification strategy for the Hanford Tank Waste Treatment and Immobilization Plant (WTP) based on experience from the Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) waste qualification program. The current waste qualification programs for each of the sites are discussed in the report to provide a baseline for comparison. Recommendations on strategies are then provided that could be implemented at Hanford based on the successful Macrobatch qualification strategy utilized at SRS to reduce the risk of processing upsets or the production of a staged waste campaign that does not meet the processing requirements of the WTP. Considerations included the baseline WTP process, as well as options involving Direct High Level Waste (HLW) and Low Activity Waste (LAW) processing, and the potential use of a Tank Waste Characterization and Staging Facility (TWCSF). The main objectives of the Hanford waste feed qualification program are to demonstrate compliance with the Waste Acceptance Criteria (WAC), determine waste processability, and demonstrate unit operations at a laboratory scale. Risks to acceptability and successful implementation of this program, as compared to the DWPF Macro-Batch qualification strategy, include: Limitations of mixing/blending capability of the Hanford Tank Farm; The complexity of unit operations (i.e., multiple chemical and mechanical separations processes) involved in the WTP pretreatment qualification process; The need to account for effects of blending of LAW and HLW streams, as well as a recycle stream, within the PT unit operations; and The reliance on only a single set of unit operations demonstrations with the radioactive qualification sample. This later limitation is further complicated because of the 180-day completion requirement for all of the necessary waste feed qualification steps. The primary recommendations/changes include the following: Collection and characterization of samples for relevant process analytes from the tanks to be blended during the staging process; Initiation of qualification activities earlier in the staging process to optimize the campaign composition through evaluation from both a processing and glass composition perspective; Definition of the parameters that are important for processing in the WTP facilities (unit operations) across the anticipated range of wastes and as they relate to qualification-scale equipment; Performance of limited testing with simulants ahead of the waste feed qualification sample demonstration as needed to determine the available processing window for that campaign; and Demonstration of sufficient mixing in the staging tank to show that the waste qualification sample chemical and physical properties are representative of the transfers to be made to WTP. Potential flowcharts for derivatives of the Hanford waste feed qualification process are also provided in this report. While these recommendations are an extension of the existing WTP waste qualification program, they are more in line with the processes currently performed for SRS. The implementation of these processes at SRS has been shown to offer flexibility for processing, having identified potential processing issues ahead of the qualification or facility processing, and having provided opportunity to optimize waste loading and throughput in the DWPF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

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