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At least 1,279 records · Page 71

Innovations in Sensors and Controls for Building Energy Management: Research and Development Opportunities Report for Emerging Technologies

Sensors, actuators, and controllers, which collectively serve as the backbone of cyberphysical systems for building energy management, are one of the core technical areas of investment for achieving the U.S. Department of Energy (DOE) Building Technologies Office's (BTO's) goals for energy affordability in the national building stock - both commercial and residential. In fact, an aggregated annual energy savings of 29% is estimated in the commercial sector alone through the implementation of efficiency measures using current state-of-the-art sensors and controls to retune buildings by optimizing programmable settings based on occupant schedules and comfort requirements, as well as detecting and diagnosing equipment operation and installation problems (Fernandez et al. 2017). Monitoring and control of building conditions and operations has advanced significantly, from the invention of the modern thermostat just before the start of the 20th century to the midcentury incorporation of direct digital control into devices, the introduction of open protocols and network communications at the end of the century, and finally the invention of cloud-based computing and additional advancements that have enabled remote operation and a proliferation of connected and intelligent devices in building automation. Despite this potential, however, two main challenges hinder widespread adoption of sensors and controls in building operations that can ensure savings for high-efficiency components and equipment (e.g., heat pumps, windows, and lighting devices), as well as additional savings from more sophisticated control architectures and algorithms. energy savings of 29% is estimated in the commercial sector alone through the implementation of efficiency measures using current state-of-the-art sensors and controls to retune buildings by optimizing programmable settings based on occupant schedules and comfort requirements, as well as detecting and diagnosing equipment operation and installation problems (Fernandez et al. 2017). Monitoring and control of building conditions and operations has advanced significantly, from the invention of the modern thermostat just before the start of the 20th century to the midcentury incorporation of direct digital control into devices, the introduction of open protocols and network communications at the end of the century, and finally the invention of cloud-based computing and additional advancements that have enabled remote operation and a proliferation of connected and intelligent devices in building automation. Despite this potential, however, two main challenges hinder widespread adoption of sensors and controls in building operations that can ensure savings for high-efficiency components and equipment (e.g., heat pumps, windows, and lighting devices), as well as additional savings from more sophisticated control architectures and algorithms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Tandem particle-slurry batch reactors for solar water splitting (Final Scientific/Technical Report)

Economically, particle slurry reactors are projected to be one of the most promising technologies for solar photoelectrochemical hydrogen production, according to a 2009 techno-economic analysis commissioned by the US DOE and performed by Directed Technologies, Inc. The Fuel Cell Technologies Office’s Multi-Year Research, Development and Demonstration (MYRD&D) goals and targets are to reduce the cost of H 2 produced from renewable sources at the plant gate (i.e. not including delivery, dispensing, or storage) to < $2.00/gge, equivalent to ~$2.00/kg H 2 . Research results from our techno-economic modeling research suggest that this target could be met using particle slurry reactors assuming STH efficiencies in the range of 5 – 10%, materials lifetimes of < 1 year, and nanoparticles that cost up to 20 times more than projected costs of TiO 2 -coated Fe 2 O 3 nanoparticles. Although most large worldwide research efforts directed at solar photoelectrochemical hydrogen production focus on wafer-based designs, the projected lower cost for a particle slurry reactor at these disparate projected STH efficiencies clearly suggests that particle slurry reactors could be a scalable and deployable technology, assuming several challenges are overcome. These major technological challenges include the demonstration of a vertically-stacked-vessel architecture that is capable of operating sustainably while mostly relying on diffusion and natural convection to mix the redox shuttles between the vessels, and the demonstration that photocatalyst particles can operate at an overall 1% STH efficiency or larger when incorporated into this two-vessel design. Our research adds to the understanding of photocatalytic reactors for solar water splitting through numerical modeling results and experimental results. Numerical models were developed to simulate relevant device physics including particle and reactor dimensions which affect optical, transport, and rheological properties, electrocatalytic and photovoltaic properties of particles at various temperatures, and properties of redox shuttles and separators. Moreover, theoretical maximum solar-to-hydrogen efficiencies for ensembles of particles like in photocatalyst reactors were modeled and simulated and shown to equal or exceed those of photoelectrochemical designs under most scenarios. These results help determine constraints on the reactor that will enable more optimal designs for future prototypes. In parallel, experiments were performed to identify the most effective redox shuttles and to empirically validate the numerical models and simulations. Toward the latter, state-of-the-art light-absorbing particles and electrocatalysts were synthesized and characterized physically and photoelectrochemically for water electrolysis and redox chemistry with redox shuttles in the form factor of mesoporous electrodes and free-floating particles. The most promising materials candidates were used in a suspension reactor to evaluate performance toward photocatalytic H 2 production and results from the two measurements were compared. Predominantly, state-of-the-art cocatalyst-modified Rh-doped SrTiO 3 and BiVO 4 particles were further characterized to assess for their ability to perform visible-light-driven H 2 and O 2 evolution, respectively, and results were similar to those reported for the state-of-the-art in the peer-reviewed literature. Outcomes from this work inform the public of the effectiveness and promise of solar photocatalytic water splitting for clean and renewable hydrogen production. This work may also help increase research interest and funding for photocatalysis projects, which will accelerate development of a technology that will benefit the public by generating fuel while emitting few greenhouse gases and pollutants.

08 HYDROGEN↗

Dynamic optimization and economic evaluation of flexible heat integration in a hybrid concentrated solar power plant

Hybridization of concentrated solar power (CSP) plants provides flexibility in operation that can drastically improve the solar-to-electric (STE) efficiency and levelized cost of electricity (LCOE) relative to standalone CSP plants. Flexible heat integration (FHI) is a novel concept where the collection and integration of CSP within a power plant is modified relative to the amount of solar energy available. FHI improves the thermal efficiency of a hybrid solar tower steam Rankine cycle power plant but leads to increased pumping needs due to continuously elevated molten salt flow rates through the collection system, which can negatively impact STE efficiency. The present work is carried out to maximize the STE efficiency of a hybrid CSP plant utilizing FHI by employing a dynamic optimization framework where a genetic algorithm optimizes the operation of the plant over a given solar irradiance profile. The study concerns a plant hypothetically located in Salt Lake City, Utah. Here, the optimization results confirm the accuracy of a predictive heuristic where the preferred operation of the plant can be estimated relative to local peaks in the incident power generated by the heliostat collection field. The optimized FHI operation demonstrates a yearly STE efficiency of 13.8%, whereas the equivalent base-level hybrid and solar-only plants exhibit solar efficiencies of 13.4% and 11.2%, respectively. Economic analysis shows that FHI reduces yearly natural gas costs, leading to a $\$0.5$/MWh reduction in LCOE relative to the base-level hybrid configuration. Overall, the results show that hybrid FHI schemes exhibit economic benefits along with observed thermodynamic improvements.

14 SOLAR ENERGY↗

Digital pixel test structures implemented in a 65 nm CMOS process

The ALICE ITS3 (Inner Tracking System 3) upgrade project and the CERN EP R&D on monolithic pixel sensors are investigating the feasibility of the Tower Partners Semiconductor Co. 65 nm process for use in the next generation of vertex detectors. The ITS3 aims to employ wafer-scale Monolithic Active Pixel Sensors thinned down to 20–40 µm and bent to form truly cylindrical half barrels. Among the first critical steps towards the realisation of this detector is to validate the sensor technology through extensive characterisation both in the laboratory and with in-beam measurements. The Digital Pixel Test Structure (DPTS) is one of the prototypes produced in the first sensor submission in this technology and has undergone a systematic measurement campaign whose details are presented in this article. The results confirm the goals of detection efficiency and non-ionising and ionising radiation hardness up to the expected levels for ALICE ITS3 and also demonstrate operation at + 20 °C and a detection efficiency of 99% for a DPTS irradiated with a dose of 10 15 1 MeV n eq cm -2 . Furthermore, spatial, timing and energy resolutions were measured at various settings and irradiation levels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Efficient Computation of Doppler-Broadened Elastic Scattering Kernel Moments Using Ladder-Operator Formulation

Anefficient routine for computing Legendre moments of the Doppler-broadened elastic scattering kernel, including resonance scattering effects, has been implemented in the ISOXML module of Griffin. Isotropic scattering in the center-of-mass system and the ideal gas model for target motion are assumed. A ladder-operator formulation is introduced to compute all Legendre moments from order 0 to N simultaneously, enabling near-linear scaling of computational cost with respect to the maximum Legendre order. A physics-based strategy for constructing outgoing energy grids has also been developed, in which a tailored base grid is combined with adaptive refinement to maintain accuracy while limiting the number of outgoing energy points. For energies between resonances, a constant cross-section model is employed to further reduce computational cost. In addition, a quantitative criterion is derived to determine isotope-wise cut-off incident energies based on a prescribed up-scattering probability coverage. For 238U, up to incident energies of approximately 75, 230, and 661 eV at 294, 900, and 2500 K (corresponding to a 2% up-scattering probability threshold), computation of P0 kernels requires 1–8 s and computation of P0–P5 kernels requires 0.4–4 min using a single thread, while maintaining 1–3% relative error in up-scattering probability. These results demonstrate that the proposed formulation enables accurate and computationally practical Doppler-broadened kernel generation for online multigroup cross-section production in Griffin.

Doppler-broadening↗

Data-driven simultaneous process optimization and adsorbent selection for vacuum pressure swing adsorption

Technologies for post-combustion carbon capture are essential for the reduction of greenhouse gas emissions to the atmosphere. However, they are still associated with high costs and energy consumption. Intensified processes for carbon capture have the potential to overcome these challenges due to their higher efficiency, lower capital cost, and increased operational flexibility. Here, this work investigates simultaneous optimization of process conditions and adsorbent selection for a modular Vacuum Pressure-Swing Adsorption system designed for CO 2 capture. Both surrogate-based Nonlinear Programming and Mixed-Integer Nonlinear Programming approaches are applied and compared in terms of computational efficiency and solution accuracy. Moreover, process performance results are examined by applying several data analytics techniques to gain insights into the material-process correlations. Data-driven classifiers and neural networks can accurately predict whether a material is likely to satisfy purity, recovery, and energy constraints when operated at optimal process conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Online task-space motion control for positioner-coordinated multi-robot manufacturing systems

Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.

Arbogast, Alex [ORNL] (ORCID:0000000154740723)↗

Hybrid Electrochemical Hydrogen/Metal Hydride Compressor (Final Technical Report)

Various alternatives to traditional mechanical compressor systems have been considered, including MHC and EHC. Both MHCs and EHCs are solid-state systems that have no moving parts other than valves. Both are quiet and have low maintenance requirements. However, strength and material issues as well as water and heat management issues have challenged EHCs, especially, when operated at very high pressures. Similarly, low efficiency, especially, when staging is required to attain high, pressure ratios, has challenged MHCs and has made them too complex and expensive. Material degradation, due to hydrogen impurity effects, has also created issues for MHCs. One novel alternative evaluated here is to combine EHC and MHC technologies in a way to maximize their advantages and to minimize each of their challenges to improve the overall systems performance on a path to meet or exceed current DOE targets. A hybrid EH/MH compressor takes advantage of lower maintenance and operating costs as well as increased reliability associated with both the MHC and EHC technologies over traditional mechanical compressors. Neither the MHC nor the EHC have any moving parts other than valves. The hybrid system also takes advantage of the higher efficiency and lower cost of the EHC by operating at lower delivery pressures combined with the robust and simple operation of a single-stage, MH compressor at higher pressures. Both MHC and EHC technologies are scalable and can be used for a variety of hydrogen compression and delivery applications.

08 HYDROGEN↗

Grid-responsive hydrogen production: Capital utilization and current density vs. efficiency in variable electricity markets

To achieve low-cost hydrogen production from water electrolyzers, grid tied electrolysis may need to operate dynamically to minimize the cost of supplying energy to the electrolyzer stack and produce hydrogen during low-cost hours and turn off/down during high-cost hours. Operating systems in this way can decrease capital utilization (capacity factor) and electricity costs. This strategy would shift the dominant cost drivers away from electricity (and thus efficiency) to the capital costs of the system, due to the underutilized capital when operating at low-capacity factors. Increasing the operational current density of the system could, in effect, reduce the capital cost of the system while producing hydrogen at a lower efficiency on a per unit energy basis. In the variable electricity cost profiles analyzed in this paper, increasing the current density for liquid alkaline from 0.5 A/cm2 to 1.5 Ac/m2 and proton exchange membrane electrolyzers from 2 A/cm2 to 4 A/cm2 resulted in substantial reductions in the levelized cost of hydrogen. Additionally, as capacity factors and electricity costs decrease, the optimal operating current density of the electrolyzer systems analyzed increases. These findings suggest R&D efforts should focus on increasing the operational current densities, reducing the turn down ratios, and understanding the durability implications of those strategies on low-temperature liquid alkaline and proton exchange membrane electrolyzers.

08 HYDROGEN↗

Unconventional Applications of Superconducting Nanowire Single Photon Detectors

Superconducting nanowire single photon detectors are becoming a dominant technology in quantum optics and quantum communication, primarily because of their low timing jitter and capability to detect individual low-energy photons with high quantum efficiencies. However, other desirable characteristics, such as high detection rates, operation in cryogenic and high magnetic field environments, or high-efficiency detection of charged particles, are underrepresented in literature, potentially leading to a lack of interest in other fields that might benefit from this technology. We review the progress in use of superconducting nanowire technology in photon and particle detection outside of the usual areas of physics, with emphasis on the potential use in ongoing and future experiments in nuclear and high energy physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Robust Scheduling of Microgrids Considering Unintentional Islanding Conditions

This paper proposes a robust scheduling model for microgrids considering the stochastic unintentional islanding conditions. The proposed model minimizes the total operating cost of the microgrid by efficiently coordinating the supply of power from local distributed energy resources and the main grid. To capture the prevailing uncertainties in renewable generation and demand as well as unintentional islanding conditions, a two-stage adaptive robust optimization model is formulated to minimize the total operating cost under the worst realization of the modeled uncertainties. The column and constraint generation (C&CG) method is used to solve the problem in an iterative manner. The solution of the proposed scheduling model ensures robust microgrid operation in consideration of all possible realization of renewable generation, demand and unintentional islanding condition. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, two micro-turbines, a diesel generator and a battery demonstrate the effectiveness of the proposed approach.

Liu, Guodong↗

Numerical Investigation of Ammonia/n-Heptane Dual-Fuel Spray Flames Using Large Eddy Simulations

Diesel engines are extensively used in heavy-duty transportation, power generation, and marine vehicles due to their superior thermal efficiency and extended high-load operability compared to spark ignition (SI) engines. However, combustion in diesel engines is generally characterized by locally rich fuel–air mixtures and high combustion temperatures, causing significant amounts of soot and NO x emissions from these engines. Utilizing carbon-free alternative fuels and enhancing fuel efficiency represent promising strategies to mitigate greenhouse gas (GHG) and other emissions in the heavy-duty transportation sector. In this context, ammonia (NH 3 ), as a hydrogen carrier, has received significant attention as a viable substitute for hydrocarbon fuels due to its carbon-free composition, relatively high energy density, and well-established infrastructure. Many previous studies have considered combustion and emission characteristics of ammonia-hydrocarbon fuel blends in engines and simplified flames. But, detailed investigations on the effects of ammonia on the performance of hydrocarbon fuels under engine conditions are lacking. In the present study, we perform large eddy simulations (LES) of the ignition and flame processes in a constant-volume combustion reactor, where n-heptane is injected in an ammonia/air ambient mixture in a diesel-like environment. A detailed and validated reaction mechanism containing 302 species and 1981 reactions is employed. The Engine Combustion Network Spray H experimental data is used to validate the spray model under both non-reacting and reacting conditions. Dual-fuel combustion is simulated using the well-stirred reactor (WSR) approach. Results are presented for two spray cases: (1) single fuel (SF) with n-heptane injected into a mixture of air and combustion products and (2) dual-fuel (DF) with the injection of n-heptane in a mixture of air, ammonia, and combustion products. It is observed that the presence of ammonia has a significant effect on the ignition and flame development processes. With ammonia addition, both the first- and second-stage ignition delay times increase, but the effect of ammonia on the second-stage ignition is significantly more prominent. In addition, the ignition kernel size and growth rate decrease noticeably. For SF spray, the main ignition is characterized by multiple ignition kernels near the spray tip, whereas for DF spray, a single relatively small ignition kernel forms and grows slowly in the downstream direction. The flame development and the final quasi-steady flame structure are also modified due to ammonia. Here, the outcome of this research would enable a better understanding of ammonia–diesel dual-fuel spray flame behavior and guide the development of associated engine combustion strategies.

ammonia↗

Efficient Reformulation and Optimization for SC-ACOPF with Line Switching

This project aims to develop efficient and robust computational methods for solving the security-constrained alternating current optimal power flow problem (SC-ACOPF). The SC-ACOPF problem is a central problem in operating the electric power grids in the United States. It determines the most economically efficient way to operate the generation and transmission system to meet daily electricity demand. The solution found by solving an SC-ACOPF problem must satisfy the physics of the alternating current (AC) power flows, various generator and network operational constraints, and must maintain secure operation under various contingency scenarios, where a generator, a transmission branch, or a transformer may unexpectedly trip offline.

97 MATHEMATICS AND COMPUTING↗

Bipolar Membrane Electrodialyzers as Flexible Demand Response Resources: Co-Optimization of Cost Savings and Product Formation

Bipolar membrane electro dialyzers (BPMED) are widely used for chemical production and processing, including in the emerging ocean alkalinity enhancement (OAE) industry. In this paper, we explore the potential of BPMED devices as flexible electrochemical loads within power system operations. Using a multi-objective optimization framework, we evaluate BPMED operation across 24-hour and monthly horizons to examine how dispatch strategies respond to electricity price and grid conditions. Simulation results show that altering the relative weights of the choices in the objective function strongly shape the operating patterns, with cost-focused strategies that suppress the operation during peak prices. Furthermore, we propose alternative formulations that optimize operations to achieve both cost savings and alignment with periods of lower grid-side carbon intensity (CI), as low grid-side CI is key to maximize OAE efficiency. Additionally, a detailed sensitivity analysis highlights the importance of device properties, where low area-specific resistance (ASR) of membrane and high current efficiency (CE) are observed to jointly unlock cost-effective operation. However, even modest shunt efficiency losses are observed to erode performance and decrease system value. Importantly, the analysis demonstrates that BPMED can serve as a controllable and flexible demand response resource, shifting load to support multiple grid-side objectives, including (but not limited to) renewable integration, alleviate peak demand, and provide co-benefits for system reliability. These findings underscore BPMED’s dual role as a process technology and a grid-supporting asset, pointing to promising pathways for operational optimization of multiple objectives.

Bhattacharya, Saptarshi (ORCID:0000000308902060)↗

High-order matrix-free incompressible flow solvers with GPU acceleration and low-order refined preconditioners

In this work, we present a matrix-free flow solver for high-order finite element discretizations of the incompressible Navier-Stokes and Stokes equations with GPU acceleration. For high polynomial degrees, assembling the matrix for the linear systems resulting from the finite element discretization can be prohibitively expensive, both in terms of computational complexity and memory. For this reason, it is necessary to develop matrix-free operators and preconditioners, which can be used to efficiently solve these linear systems without access to the matrix entries themselves. The matrix-free operator evaluations utilize GPU-accelerated sum-factorization techniques to minimize memory movement and maximize throughput. The preconditioners developed in this work are based on a low-order refined methodology with parallel subspace corrections, as described for diffusion problems in [1]. The saddle-point Stokes system is solved using block-preconditioning techniques, which are robust in mesh size, polynomial degree, time step, and viscosity. For the incompressible Navier-Stokes equations, we make use of projection (fractional step) methods, which require Helmholtz and Poisson solves at each time step. The performance of our flow solvers is assessed on several benchmark problems in two and three spatial dimensions.

97 MATHEMATICS AND COMPUTING↗

An implicit-explicit time splitting strategy for the far SOL plasma fluid model with DG-FEM discretization

We consider a far scrape-off layer (SOL) plasma fluid model of ions that is governed by a Braginskiitype model: a one-dimensional, nonlinear system of advection-diffusion equations coupled with a diffusion equation for neutral particles. Our motivation for studying this system arises from the coupling between the edge plasma and radio-frequency (RF) heating, where solving a far SOL plasma fluid model provides critical insights into edge plasma dynamics. Numerical simulations of plasma fluid models require advanced computational techniques to achieve both efficiency and accuracy, especially when resolving the boundary layer in magnetically confined plasmas. In this work, we propose an implicit-explicit time operator splitting strategy that allows for an efficient solution algorithm, where the diffusive terms are treated semi-implicitly requiring only a linear solve, while the advection part is handled explicitly using a strong-stability-preserving Runge-Kutta (SSP-RK3) scheme. This leads to a fully decoupled system in which the diffusion and advection sub-problems can be solved separately, simplifying the overall solution procedure and allowing for efficient parallelization, which is particularly relevant for exploring the impact of RF heating on the SOL plasma. The main challenge of the discretization is due to the strong coupling between diffusion and advection, particularly through the boundary conditions. This makes implementation of such a scheme in an accurate and stable manner nontrivial. We discuss in detail how to split the equations and manage boundary conditions to maintain stability and well-posedness for each subsystem. We also describe a spatial discretization approach, based on the discontinuous Galerkin finite element method (DG-FEM) and present numerical results for a one-dimensional system.

Burkovska, Olena [ORNL] (ORCID:0000000163101130)↗

Materials and Fuels Complex Operations Management Improvement Strategy

The Materials and Fuels Complex (MFC) has experienced substantial growth in terms of staff, research, and production in recent years. MFC operational performance has effectively kept pace with this growth. However, to capture the continuous improvement actions needed to improve effectiveness and increase the efficiency of our management systems, a broad operations management strategy is necessary. The MFC Operations Management Improvement (OMI) Strategy is complementary to the MFC Five-Year Mission and Investment Strategies and the MFC Management Plan. The OMI strategy is structured to address the management systems outlined in the Nuclear Facility Management Standard Operations Model. Each management system is evaluated independently in a chapter that describes the prior 5 years of performance improvement, a description of improvement actions for the MFC staff that directly perform within or contribute to the management system, process improvements, and any needed equipment improvements. Additional chapters are added to address subject areas not formally described in the standard operations model. The OMI strategy actions are structured to have cross cutting impacts for improvements pertaining to the entire directorate or a single division. All division improvement agendas are aligned to the OMI strategy.

99 GENERAL AND MISCELLANEOUS↗

Materials and Fuels Complex Operations Management Improvement Strategy for FY2022

The Materials and Fuels Complex (MFC) has experienced substantial growth in terms of staff, research, and production in recent years. MFC operational performance has effectively kept pace with this growth. However, to capture the continuous improvement actions needed to improve effectiveness and increase the efficiency of our management systems, a broad operations management strategy is necessary. The MFC Operations Management Improvement (OMI) Strategy is complementary to the MFC Five-Year Mission and Investment Strategies and the MFC Management Plan. The OMI strategy is structured to address the management systems outlined in the Nuclear Facility Management Standard Operations Model. Selected management systems are evaluated independently in chapters that describe the prior 5 years of performance improvement, a description of improvement actions for the MFC staff that directly perform within or contribute to the management system, process improvements, and any needed equipment improvements. Chapter selection is based on a management system’s need for improvement. In some cases, management systems may be combined in a single chapter. Additional chapters are added to address subject areas not formally described in the standard operations model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗