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At least 73 records · Page 4

Transaction-Based Building Controls Framework, Volume 1: Reference Guide

This document proposes a framework concept to achieve the objectives of raising buildings’ efficiency and energy savings potential benefitting building owners and operators. We call it a transaction-based framework, wherein mutually-beneficial and cost-effective market-based transactions can be enabled between multiple players across different domains. Transaction-based building controls are one part of the transactional energy framework. While these controls realize benefits by enabling automatic, market-based intra-building efficiency optimizations, the transactional energy framework provides similar benefits using the same market -based structure, yet on a larger scale and beyond just buildings, to the society at large.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

AGR-5/6/7 Experiment Monitoring and Simulation Progress

Advanced Gas Reactor (AGR)--5/6/7 is the last of a series of AGR experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The test train contains five separate capsules that are independently controlled and monitored. Each capsule contains multiple 12.51 mm long compacts filled with low-enriched uranium carbide/oxide (UCO) TRISO fuel particles. The objectives of the AGR-5/6/7 experiment are to: 1. Irradiate reference-design fuel particles to support fuel qualification. 2. Establish operating margins for the fuel beyond normal operating conditions. 3. Provide irradiated fuel performance data and irradiated fuel samples for post-irradiation examination (PIE) and safety testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Performance of Ferrite Vector Modulators in the LLRF System of the Fermilab HINS 6-Cavity Test

The High Intensity Neutrino Source (HINS) 6-cavity test is a part of the Fermilab HINS Linac R&D program for a low energy, high intensity proton Hsup>- linear accelerator. One of the objectives of the 6-cavity test is to demonstrate the use of high power RF Ferrite Vector Modulators(FVM) for independent control of multiple cavities driven by a single klystron. The beamline includes an RFQ and six cavities. The LLRF system provides a primary feedback loop around the RFQ and the distribution of the regulated klystron output is controlled by secondary learning feed-forward loops on the FVMs for each of the six cavities. The feed-forward loops provide pulse to pulse correction to the current waveform profiles of the FVM power supplies to compensate for beam-loading and other disturbances. The learning feed-forward loops are shown to successfully control the amplitude and phase settings for the cavities well within the 1 % and 1 degree requirements specified for the system.

79 ASTRONOMY AND ASTROPHYSICS↗

AGR-5/6/7 Experiment Monitoring and Simulation Progress

Advanced Gas Reactor (AGR)--5/6/7 is the last of a series of AGR experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The test train contains five separate capsules that are independently controlled and monitored. Each capsule contains multiple 12.51 mm long compacts filled with low-enriched uranium carbide/oxide (UCO) TRISO fuel particles. The objectives of the AGR-5/6/7 experiment are to: 1. Irradiate reference-design fuel particles to support fuel qualification. 2. Establish operating margins for the fuel beyond normal operating conditions. 3. Provide irradiated fuel performance data and irradiated fuel samples for post-irradiation examination (PIE) and safety testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

AGR-5/6/7 Experiment Monitoring and Simulation Progress

Advanced Gas Reactor (AGR)--5/6/7 is the last of a series of AGR experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The test train contains five separate capsules that are independently controlled and monitored. Each capsule contains multiple 12.51 mm long compacts filled with low-enriched uranium carbide/oxide (UCO) TRISO fuel particles. The objectives of the AGR-5/6/7 experiment are to: 1. Irradiate reference-design fuel particles to support fuel qualification. 2. Establish operating margins for the fuel beyond normal operating conditions. 3. Provide irradiated fuel performance data and irradiated fuel samples for post-irradiation examination (PIE) and safety testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Optimal Power Hardware-in-the-Loop Interfacing: Applying Modern Control For Design and Verification of High-Accuracy Interfaces

Here, we develop a novel approach to designing power hardware-in-the-loop (PHIL) simulation interfaces that maximizes simulation bandwidth and accuracy by leveraging a modern control framework that explicitly considers objectives on accuracy and can automatically synthesize an optimal controller that meets these objectives while stabilizing the closed-loop system. The method developed improves upon common approaches to PHIL interface design that typically involve multiple design steps for manual compensation and stabilization design that can result in interfaces that are stable but have suboptimal bandwidth and accuracy. The approach developed is general and can be applied to most PHIL system configurations. The modeling framework allows for the inclusion of scaling factors and hardware-under-test current injection models that are common to practical PHIL simulations and have significant impacts on stability. We also present practical methods and metrics for verifying the absolute accuracy of PHIL simulation results without relying on relative comparisons to potentially inaccurate models or previous simulation results. We demonstrate the accuracy evaluation method and show the improved performance achievable when using the optimal PHIL interface design approach in an experimental case study involving a 100-kVA battery inverter.

42 ENGINEERING↗

Controller Hardware-in-the-Loop Evaluation of a Microgrid Controller for a Microgrid System with Multiple Grid-Forming Inverters

This paper presents the laboratory evaluation of a commercial Microgrid Management System (MGMS) implemented in the real-world Bronzeville Microgrid which features a futuristic scenario with high renewable energy integration and the use of multiple Grid-Forming (GFM) inverters. The primary objective of the performance evaluation for the MGMS is to assess the MGMS's capability to dispatch GFM units, including a GFM PV unit and two GFM battery units, to maintain the system stability and ensure economic operation, thus guaranteeing the microgrid's resilience during prolonged outages and dynamic events. The laboratory controller hardware-in-the-loop provides realistic testing environment through detailed electromagnetic transient modeling of the microgrid system, hardware MGMS, and standard communication protocols (DNP3). The CHIL evaluation shows how the MGMS effectively manages the GFM inverters, highlighting its performance in maintaining stability, reliability, and survivability in a microgrid environment with a high penetration of renewable energy sources.

controller hardware-in-the-loop↗

Controller-Hardware-in-the-Loop Evaluation of a Microgrid Controller for a Microgrid System With Multiple Grid-Forming Inverters

This paper presents the laboratory evaluation of a commercial Microgrid Management System (MGMS) implemented in the real-world Bronzeville Microgrid which features a futuristic scenario with high renewable energy integration and the use of multiple Grid-Forming (GFM) inverters. The primary objective of the performance evaluation for the MGMS is to assess the MGMS's capability to dispatch GFM units, including a GFM PV unit and two GFM battery units, to maintain the system stability and ensure economic operation, thus guaranteeing the microgrid's resilience during prolonged outages and dynamic events. The laboratory controller hardware-in-the-loop provides realistic testing environment through detailed electromagnetic transient modeling of the microgrid system, hardware MGMS, and standard communication protocols (DNP3). This CHIL evaluation shows how the MGMS effectively manages the GFM inverters, highlighting its performance in maintaining stability, reliability, and survivability in a microgrid environment with a high penetration of renewable energy sources.

controller hardware-in-the-loop↗

Optimal CO 2 storage management considering safety constraints in multi-stakeholder multi-site GCS projects: A Markov game perspective

Geological carbon storage (GCS) projects could involve a diverse array of stakeholders or players from public, private, and regulatory sectors, each with different objectives and responsibilities. Given the complexity, scale, and long-term nature of GCS operations, determining whether individual stakeholders can independently optimize their interests — or whether collaborative coalition agreements are needed — remains a central question for effective GCS project planning and management. To access large, high-quality storage resources, future GCS deployment may increasingly occur in geologically connected sites, where shared geological features such as pressure space and reservoir pore capacity can lead to competitive behavior among stakeholders. In this work, we propose a paradigm based on Markov games to quantitatively investigate how different coalition structures affect the goals of stakeholders. We frame this multi-stakeholder multi-site problem as a multi-agent reinforcement learning problem with safety constraints. Our approach enables agents to learn optimal strategies while complying with safety regulations. We present an example where multiple operators are injecting CO 2 into their respective project areas in a geologically connected basin. To address the high computational cost of repeated simulations of high fidelity models, a previously developed surrogate model based on the Embed-to-Control (E2C) framework is employed. Our results demonstrate the effectiveness of the proposed framework in addressing optimal management of CO 2 storage when multiple stakeholders with different objectives and goals are involved.

58 GEOSCIENCES↗

Controller Hardware-in-the-Loop Evaluation of a Microgrid Controller for a Microgrid System with Multiple Grid-Forming Inverters: Preprint

This paper presents the laboratory evaluation of a commercial Microgrid Management System (MGMS) implemented in the real-world Bronzeville Microgrid which features a futuristic scenario with high renewable energy integration and the use of multiple Grid-Forming (GFM) inverters. The primary objective of the performance evaluation for the MGMS is to assess the MGMS's capability to dispatch GFM units, including a GFM PV unit and two GFM battery units, to maintain the system stability and ensure economic operation, thus guaranteeing the microgrid's resilience during prolonged outages and dynamic events. The laboratory controller hardware-in-the-loop provides realistic testing environment through detailed electromagnetic transient modeling of the microgrid system, hardware MGMS, and standard communication protocols (DNP3). The CHIL evaluation shows how the MGMS effectively manages the GFM inverters, highlighting its performance in maintaining stability, reliability, and survivability in a microgrid environment with a high penetration of renewable energy sources.

controller hardware-in-the-loop↗

Leveraging Computational Storage Devices in Campaign Storage [Slides]

Computational storage provides new ways of accelerating data-intensive applications. In-drive data management schemes matter (O_DIRECT, clustered index). Layer violation: “cheating” one filesystem may be possible; cheating multiple layers of filesystems is hard (FS internal load balancing, fail over, compression, concurrency control). The future directions include block-based acceleration to object-based acceleration.

97 MATHEMATICS AND COMPUTING↗

Optimization-based control using input convex neural networks

Input convex neural networks (ICNNs) are a family of deep learning models where the outputs are constructed to be convex functions of the inputs. By parameterizing system models using ICNNs, optimization-based control problems can be solved as convex optimization problems, leading to improved performance and robustness. This work proposes a novel framework where the control objective function and constraints are modelled using ICNNs. A case study of optimization-based control with output constraints is conducted on a process with input multiplicity and nonminimum phase behavior. The simulation results demonstrate improved economic yield compared with normal neural networks. Additionally, the input convexity formulation is compared with simple regularization techniques, and unique benefits such as improved data efficiency and robustness of the proposed formulation are shown. Finally, by explicitly incorporating prior knowledge about convexity, this framework provides a good balance between the universal approximation power of deep learning and computational feasibility required by control.

42 ENGINEERING↗

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

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

adjoint optimization↗

An Adaptive Memory Interface Controller for Improving Bandwidth Utilization of Hybrid and Reconfigurable Systems

Emerging applications such as data mining, bioinformatics, knowledge discovery, social network analysis are irregular. They use data structures based on pointers or linked lists, such as graphs, unbalanced trees or unstructures grids, which generates unpredictable memory accesses. These data structures usually are large, but difficult to partition. These applications mostly are memory bandwidth bounded and have high synchronization intensity. However, they also have large amounts of inherent dynamic parallelism, because they potentially perform a task for each one of the element they are exploring. Several efforts are looking at accelerating these applications on hybrid architectures, which integrate general purpose processors with reconfigurable devices. Some solutions, which demonstrated significant speedups, include custom-hand tuned accelerators or even full processor architectures on the reconfigurable logic. In this paper we present an approach for the automatic synthesis of accelerators from C, targeted at irregular applications. In contrast to typical High Level Synthesis paradigms, which construct a centralized Finite State Machine, our approach generates dynamically scheduled hardware components. While parallelism exploitation in typical HLS-generated accelerators is usually bound within a single execution flow, our solution allows concurrently running multiple execution flow, thus also exploiting the coarser grain task parallelism of irregular applications. Our approach supports multiple, multi-ported and distributed memories, and atomic memory operations. Its main objective is parallelizing as many memory operations as possible, independently from their execution time, to maximize the memory bandwidth utilization. This significantly differs from current HLS flows, which usually consider a single memory port and require precise scheduling of memory operations. A key innovation of our approach is the generation of a memory interface controller, which dynamically maps concurrent memory accesses to multiple ports. We present a case study on a typical irregular kernel, Graph Breadth First search (BFS), exploring different tradeoffs in terms of parallelism and number of memories.

BFS↗

Post-Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada for Calendar Year 2016 (January 2016–December 2016), Revision 1

Corrective Action Unit (CAU) 98: Frenchman Flat on the Nevada National Security Site was the location of 10 underground nuclear tests. CAU 98 underwent a series of investigations and actions in accordance with the Federal Facility Agreement and Consent Order to assess contamination of groundwater by radionuclides from the tests. A Closure Report completed that process in 2016 and called for long-term monitoring, use restrictions (URs), and institutional controls to protect the public and environment from potential exposure to contaminated groundwater. Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the UR boundaries remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2016. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. The tritium concentration in both wells is slowly decreasing. The water-level monitoring network includes 16 wells. Depth to water measured in 2016 in all wells is consistent with recent measurements. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Assessing the Feasibility of Controlling Aedes aegypti with Transgenic Methods: A Model-Based Evaluation

Suppression of dengue and malaria through releases of genetically engineered mosquitoes might soon become feasible. Aedes aegypti mosquitoes carrying a conditionally lethal transgene have recently been used to suppress local vector populations in small-scale field releases. Prior to releases of transgenic insects on a wider scale, however, most regulatory authorities will require additional evidence that suppression will be effective in natural heterogeneous habitats. We use a spatially explicit stochastic model of an Ae. aegypti population in Iquitos, Peru, along with an uncertainty analysis of its predictions, to quantitatively assess the outcome of varied operational approaches for releases of transgenic strains with conditional death of females. We show that population elimination might be an unrealistic objective in heterogeneous populations. We demonstrate that substantial suppression can nonetheless be achieved if releases are deployed in a uniform spatial pattern using strains combining multiple lethal elements, illustrating the importance of detailed spatial models for guiding genetic mosquito control strategies.

59 BASIC BIOLOGICAL SCIENCES↗

FY12 Annual Report: PHEV Engine Control and Energy Management Strategy

The objectives are: (1) Investigate novel engine control strategies targeted at rapid engine/catalyst warming for the purpose of mitigating tailpipe emissions from plug-in hybrid electric vehicles (PHEV) exposed to multiple engine cold start events; (2) Optimize integration of engine control strategies with hybrid supervisory control strategies in order to reduce cold start emissions and fuel consumption of PHEVs; and (3) Ensure that development of new vehicle technologies complies with existing emission standards.

33 ADVANCED PROPULSION SYSTEMS↗

PHEV Engine Control and Energy Management Strategy (FY12 Annual Report)

Our objective was to investigate novel engine control strategies targeted at rapid engine/catalyst warming for the purpose of mitigating tailpipe emissions from plug-in hybrid electric vehicles (PHEV) exposed to multiple engine cold start events, and to validate and optimize hybrid supervisory control techniques developed during previous and on-going research projects by integrating them into the vehicle level control system and complementing them with the modified engine control strategies in order to further reduce emissions during both cold start and engine re-starts.

Chambon, Paul H.↗