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DOE OSTI2013

Imaging-based optical caliper for objects in hot manufacturing processes

OG Technologies, Inc. (OGT), in conjunction with its industrial and academic partners, proposes to develop an Imaging-Based Optical Caliper (hereafter referred to as OC) for Objects in Hot Manufacturing Processes. The goal is to develop and demonstrate the OC with the synergy of OGT's current technological pool and other innovations to provide a light weight, robust, safe and accurate portable dimensional measurement device for hot objects with integrated wireless communication capacity to enable real time process control. The technical areas of interest in this project are the combination of advanced imaging, Sensor Fusion, and process control. OGT believes that the synergistic interactions between its current set of technologies and other innovations could deliver products that are viable and have high impact in the hot manufacture processes, such as steel making, steel rolling, open die forging, and glass industries, resulting in a new energy efficient control paradigm in the operations through improved yield, prolonged tool life and improved quality. In-line dimension measurement and control is of interest to the steel makers, yet current industry focus is on the final product dimension only instead of whole process due to the limit of man power, system cost and operator safety concerns. As sensor technologies advances, the industry started to see the need to enforce better dimensional control throughout the process, but lack the proper tools to do so. OGT along with its industrial partners represent the indigenous effort of technological development to serve the US steel industry. The immediate market that can use and get benefited from the proposed OC is the Steel Industry. The deployment of the OC has the potential to provide benefits in reduction of energy waste, CO2 emission, waste water amount, toxic waste, and so forth. The potential market after further expended function includes Hot Forging and Freight Industries. The OC prototypes were fabricated, and were progressively tested on-site in several steel mill and hot forging facilities for evaluation. Software refinements and new calibration procedures were also carried out to overcome the discovered glitches. Progress was presented to the hot manufacture facilities worldwide. Evidence showed a great interest and practical need for this product. OGT is in the pilot commercialization mode for this new development. The R&D team also successfully developed a 3D measurement function with no additional investment of hardware or equipment to measure low or room temperature object dimensions. Several tests were conducted in the reality environment to evaluate the measurement results. This new application will require additional development in product design.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Considerations for AMI-Based Operations for Distribution Feeders

More than $5 billion in investments in advanced metering infrastructure (AMI) technologies, AMI deployments, as pervasive secondary network voltage monitoring systems, provide opportunities for utility operations and controls. This paper focuses on the considerations for AMI-based tools and techniques as the industry moves toward operationalizing such large data sets. Phase identification is a first such tool. Numerous distribution network analysis, monitoring, and control applications - including volt/volt-ampere reactive control, state estimation, and distribution automation - require accurate phase connectivity information in the system models. The phase connectivity database maintained by utilities is inaccurate because of a significant amount of missing data, restoration activities, and network reconfiguration. Existing phase identification techniques that estimate phase connectivity work well in distribution feeders that have low or no photovoltaic (PV) generation; however, they fail to identify the phases accurately when considerable PV generation is present. This work addresses the phase identification problem in the presence of high PV generation using statistical analysis methods. Further, insights into the AMI data requirements for this application in terms of data window length and resolution are provided using sensitivity analysis performed on an actual distribution feeder model of San Diego Gas & Electric Company. The results of this study show that the phase connectivity, even in the presence of high PV generation, can be accurately identified using statistical analysis of AMI data of 1 day.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Considerations for AMI-Based Operations for Distribution Feeders: Preprint

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Perspectives on Next Steps in Arms Control and Non-Proliferation

Much has happened in arms control over the last year as this chapter has been in development. The prospects for arms control as a viable national security tool have, if anything, grown darker. Russia has falsely equated tearing down the remaining arms control edifice with creating potential leverage vis-à-vis its actions in Ukraine. China has failed to update its talking points on being a responsible arms control actor with its massive nuclear force expansion. The United States has stated clearly that it is open for business on arms control and risk reduction, but it unfortunately has no customers in Russia and China. It remains unclear what specifically the United States is selling in terms of what it wants in a potential agreement. Competitive dynamics and an atmosphere of great power competition are driving all parties further away from the table.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2015

Metrology for Fuel Cell Manufacturing

The project was divided into three subprojects. The first subproject is Fuel Cell Manufacturing Variability and Its Impact on Performance. The objective was to determine if flow field channel dimensional variability has an impact on fuel cell performance. The second subproject is Non-contact Sensor Evaluation for Bipolar Plate Manufacturing Process Control and Smart Assembly of Fuel Cell Stacks. The objective was to enable cost reduction in the manufacture of fuel cell plates by providing a rapid non-contact measurement system for in-line process control. The third subproject is Optical Scatterfield Metrology for Online Catalyst Coating Inspection of PEM Soft Goods. The objective was to evaluate the suitability of Optical Scatterfield Microscopy as a viable measurement tool for in situ process control of catalyst coatings.

08 HYDROGEN↗

DOE OSTI2013

SOWFA + Super Controller User's Manual

SOWFA + Super Controller is a modification of the NREL's SOWFA tool which allows for a user to apply multiturbine or centralized wind plant control algorithms within the high-fidelity SOWFA simulation environment. The tool is currently a branch of the main SOWFA program, but will one day will be merged into a single version. This manual introduces the tool and provides examples such that a user can implement their own super controller and set up and run simulations. The manual only discusses enough about SOWFA itself to allow for the customization of controllers and running of simulations, and details of SOWFA itself are reported elsewhere Churchfield and Lee (2013); Churchfield et al. (2012). SOWFA + Super Controller, and this manual, are in alpha mode.

17 WIND ENERGY↗

DOE OSTI2021

Report for Task 15: Developed Tool Verification/Validation Report (Deliverable D11): AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency

This report summarizes the verification report for the developed modules. The team conducted verification in two phases. In phase 1, the modules were validated using offline validation methods and in phase 2 the modules were subjected to real-time validation. This report outlines the approach and the results for the modules under offline and real-time settings. The rest of the report details the functional workflow of AGGREGATE modules, we then transition to offline validation followed by real-time validation of modules. We conclude the report by discussing some of the key points of this report.

14 SOLAR ENERGY↗

DOE OSTI2018

Surface Preparation and Treatment for Large-Scale 3D-Printed Composite Tooling Coating Adhesion

Recent advances in large-scale thermoplastic additive manufacturing (AM), using fused deposition modelling (FDM), have shown that the technology can effectively produce large aerospace tools with common feed stocks, costing 2.3 $/kg, such as a 20% carbon-filled acrylonitrile butadiene styrene (ABS). Large-scale additive manufacturing machines have build-volumes in the range of cubic meters and use commercially available pellet feedstock thermoplastics, which are significantly cheaper (5–10 $/kg) than the filament feedstocks for desktop 3D printers (20–50 $/kg). Additionally, large-scale AM machines have a higher material throughput on the order of 50 kg/h. This enables the cost-efficient tool production for several industries. Large-scale 3D-printed tooling will be computerized numerical control (CNC)-machined and -coated, to provide a surface suitable for demolding the composite parts. This paper outlines research undertaken to review and improve the adhesion of the coating systems to large, low-cost AM composite tooling, for marine or infrastructure composite applications. Lower cost tooling systems typically have a lower dimensional accuracy and thermal operating requirements than might be required for aerospace tooling. As such, they can use lower cost commodity grade thermoplastics. The polymer systems explored in the study included polypropylene (PP), styrene-maleic anhydride (SMA), and polylactic acid (PLA). Bio-based filler materials were used to reduce cost and increase the strength and stiffness of the material. Fillers used in the study included wood flour, at 30% by weight and spray-dried cellulose nano-fibrils, at 20% by weight. Applicable adhesion of the coating was achieved with PP, after surface treatment, and untreated SMA and PLA showed desirable coating adhesion results. PLA wood-filled composites offered the best properties for the desired application and, furthermore, they have environment-friendly advantages.

Sauerbier, Philipp (ORCID:0000000150238568)↗

DOE OSTI2013

DAKOTA reliability methods applied to RAVEN/RELAP-7.

This report summarizes the result of a NEAMS project focused on the use of reliability methods within the RAVEN and RELAP-7 software framework for assessing failure probabilities as part of probabilistic risk assessment for nuclear power plants. RAVEN is a software tool under development at the Idaho National Laboratory that acts as the control logic driver and post-processing tool for the newly developed Thermal-Hydraulic code RELAP-7. Dakota is a software tool developed at Sandia National Laboratories containing optimization, sensitivity analysis, and uncertainty quantification algorithms. Reliability methods are algorithms which transform the uncertainty problem to an optimization problem to solve for the failure probability, given uncertainty on problem inputs and a failure threshold on an output response. The goal of this work is to demonstrate the use of reliability methods in Dakota with RAVEN/RELAP-7. These capabilities are demonstrated on a demonstration of a Station Blackout analysis of a simplified Pressurized Water Reactor (PWR).

Swiler, Laura Painton↗

DOE OSTI2014

Validation of Multiple Tools for Flat Plate Photovoltaic Modeling Against Measured Data

This report expands upon a previous work by the same authors, published in the 40th IEEE Photovoltaic Specialists conference. In this validation study, comprehensive analysis is performed on nine photovoltaic systems for which NREL could obtain detailed performance data and specifications, including three utility-scale systems and six commercial scale systems. Multiple photovoltaic performance modeling tools were used to model these nine systems, and the error of each tool was analyzed compared to quality-controlled measured performance data. This study shows that, excluding identified outliers, all tools achieve annual errors within +/-8% and hourly root mean squared errors less than 7% for all systems. It is further shown using SAM that module model and irradiance input choices can change the annual error with respect to measured data by as much as 6.6% for these nine systems, although all combinations examined still fall within an annual error range of +/-8.5%. Additionally, a seasonal variation in monthly error is shown for all tools. Finally, the effects of irradiance data uncertainty and the use of default loss assumptions on annual error are explored, and two approaches to reduce the error inherent in photovoltaic modeling are proposed.

14 SOLAR ENERGY↗

DOE OSTI2014

Developing a System for Testing Computational Social Models using Amazon Mechanical Turk

The US faces persistent, distributed threats from malevolent individuals, groups and organizations around the world. Computational Social Models (CSMs) help anticipate the dynamics and behaviors of these actors by modeling the behavior and interactions of individuals, groups and organizations. For strategic planners to trust the results of CSMs, they must have confidence in the validity of the models. Establishing validity before model use will enhance confidence and reduce the risk of error. One problem with validation is designing an appropriate controlled test of the model, similar to the testing of physical models. Lab experiments can do this, but are often limited to small numbers of subjects, with low subject diversity and are often in a contrived environment. Natural studies attempt to test models by gathering large-scale observational data (e.g., social media) however this loses the controlled aspect. We propose a new approach to run large-scale, controlled online experiments on diverse populations. Using Amazon Mechanical Turk, a crowdsourcing tool, we will draw large populations into controlled experiments in a manner that was not possible just a few years ago.

42 ENGINEERING↗

DOE OSTI2020

Sliding Mode Network Perimeter Control

Urban traffic congestion is a chronic problem faced by many cities in the US and worldwide. It results in inefficient infrastructure use as well as increased vehicle fuel consumption and emission levels. Congestion is intertwined with delay, as road users waste precious hours on the road, which in turn reduces productivity. Researchers have developed, and continue to design, tools and systems to alleviate this problem. Network perimeter control is one such tool that has been studied extensively. It attempts to control the flow of vehicles entering a protected area to ensure that the congested regime predetermined by the Network Fundamental Diagram (NFD) is not reached. In this paper, a method derived from sliding mode control theory is presented. Its main advantages over proportional-integral controllers include (1) minimal tuning, (2) no linearization of the governing equations, (3) no assumptions with regard to the shape of the NFD, and (4) ability to handle various demand profiles without the need to retune the controller. A sliding mode controller was implemented and tested on a congested grid network. The results show that the proposed controller produces network-wide delay savings and disperses congestion effectively.

42 ENGINEERING↗

DOE OSTI2021

Genotype-dependent contribution of CBF transcription factors to long-term acclimation to high light and cool temperature

When grown under cool temperature, winter annuals upregulate photosynthetic capacity as well as freezing tolerance. Here, the role of three cold-induced C-repeat-binding factor (CBF1–3) transcription factors in photosynthetic upregulation and freezing tolerance was examined in two Arabidopsis thaliana ecotypes originating from Italy (IT) or Sweden (SW), and their corresponding CBF1–3-deficient mutant lines it: cbf123 and sw: cbf123 . Photosynthetic, morphological and freezing-tolerance phenotypes, as well as gene expression profiles, were characterized in plants grown from the seedling stage under different combinations of light level and temperature. Under high light and cool (HLC) growth temperature, a greater role of CBF1–3 in IT versus SW was evident from both phenotypic and transcriptomic data, especially with respect to photosynthetic upregulation and freezing tolerance of whole plants. Overall, features of SW were consistent with a different approach to HLC acclimation than seen in IT, and an ability of SW to reach the new homeostasis through the involvement of transcriptional controls other than CBF1–3. These results provide tools and direction for further mechanistic analysis of the transcriptional control of approaches to cold acclimation suitable for either persistence through brief cold spells or for maximisation of productivity in environments with continuous low temperatures.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Towards a Semantically-Enabled Control Strategy for Building Simulations: Integration of Semantic Technologies and Model Predictive Control

State-of-the-art building simulation control methods incorporate physical constraints into their mathematical models, but omit implicit constraints associated with policies of operation and dependency relationships among rules representing those constraints. To overcome these shortcomings, there is a recent trend in enabling the control strategies with inference-based rule checking capabilities. One solution is to exploit semantic web technologies in building simulation control. Such approaches provide the tools for semantic modeling of domains, and the ability to deduce new information based on the models through use of Description Logic (DL). In a step toward enabling this capability, this paper presents a cross-disciplinary data-driven control strategy for building energy management simulation that integrates semantic modeling and formal rule checking mechanisms into a Model Predictive Control (MPC) formulation. The results show that MPC provides superior levels of performance when initial conditions and inputs are derived from inference-based rules.

Delgoshaei, Parastoo↗

DOE OSTI2013

RAVEN as a tool for dynamic probabilistic risk assessment: Software overview

RAVEN is a software tool under development at the Idaho National Laboratory (INL) that acts as the control logic driver and post-processing tool for the newly developed Thermal-Hydraulic code RELAP-7. The scope of this paper is to show the software structure of RAVEN and its utilization in connection with RELAP-7. A short overview of the mathematical framework behind the code is presented along with its main capabilities such as on-line controlling/ monitoring and Monte-Carlo sampling. A demo of a Station Black Out PRA analysis of a simplified Pressurized Water Reactor (PWR) model is shown in order to demonstrate the Monte-Carlo and clustering capabilities. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Smart Ventilation Controls for Occupancy and Auxiliary Fan Use Across U.S. Climates

Smart Ventilation has been developed as a way to reduce the energy associated with ventilation by changing when ventilation happens and how much ventilation occurs at any given time. In high performance buildings with low envelope and appliance related loads, ventilation is becoming a bigger part of the total building energy use and needs to be addressed if performance targets are to be met. This work explores the development and performance of smart ventilation controls based on occupancy and auxiliary fan operation that provide annual dwelling unit ventilation equivalence to ASHRAE Standard 62.2-2016. A prototype high performance home compliant with U.S. DOE Building America Zero Energy Ready program requirements was simulated using the REGCAP tool with and without smart controls across 15 U.S. DOE climate zones. Balanced and unbalanced IAQ fans were independently simulated, and all smart controlled fans had airflows double the reference 62.2-2016 airflow. Three idealized occupancy patterns were examined: 1st shift (a typical daily work/school absence), an extended 1st shift with more time spent out of the home evenings and weekends and 3rd shift (night work). The Occupancy controller turns the IAQ fan off during unoccupied periods, and it resumes ventilation upon their return. While unoccupied, contaminants are allowed to accumulate in the space, because occupants are not exposed to these contaminants. When occupants return home, they are exposed to these higher contaminant concentrations, and the controller increases the ventilation rate sufficiently to ensure equivalence with a continuous IAQ fan. Accounting for pollutant emissions that occur during unoccupied periods (as required by ASHRAE 62.2-2016), sharply distinguishes our occupancy controls from past Demand Controlled Ventilation systems. This new accounting method results in equivalent contaminant exposure, as well as lower reductions in average ventilation rates and lower energy savings. Smart controls were demonstrated that saved HVAC energy (i.e., avoided heating/cooling load, as well as fan energy)—averaging between 6 and 46% of ventilation-related energy use depending on the control strategy and occupancy pattern assumptions. The greatest savings were in the combined Auxiliary Fan + Occupancy control. Energy savings increased with climate heating demand and longer unoccupied time periods. The 3rd shift occupancy pattern had better performance, due to the thermal benefit of reducing the ventilation rate during the cold nighttime hours. This same effect provided a cooling energy benefit in hotter locations for the 1st shift. Overall, savings from occupancy-based smart controls were low, because of the recovery period required after occupants return home, during which the airflow is double the 62.2 reference. This recovery is required to maintain equivalence with the ASHRAE standard. Occupancy-based control performance was improved when combined with sensing auxiliary fans and when providing a pre-occupancy flush out of one- or two-hours. Performance was similarly improved if the ASHRAE Standard were to recognize that pollutant emissions are lower during unoccupied periods, iii allowing a lower target ventilation rate during unoccupied periods (not currently in the standard) (see Full vs. Half AEQ in this report). Finally, over-sized unbalanced fans that are cycled on-and-off by a smart controller (or timer) were found to substantially increase annual average air exchange and energy use relative to a continuous unbalanced fan due to the effects of superposition with natural infiltration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Automated Controller Hardware-In-The-Loop Testbed for EV Charger Resilience Analysis

This paper focuses on the development of a tool that includes an automated testbed with controls, protection, and communications integrated into a real-time system to provide a platform to generate data sets for failure modes and effects analysis. This tool establishes a value for automation of data generation for different scenarios and addresses the gap of nonexistent field data for different applications and use cases. The features of this tool can further be expanded to include multiple power electronics models, communication protocols, and scaled system architectures. This general framework was evaluated for a DC fast charger system use case to provide quantitative solution for resiliency.

Starke, Michael↗

DOE OSTI2023

A new coupling of a GPU-resident large-eddy simulation code with a multiphysics wind turbine simulation tool

The development of new wind farm control strategies can benefit from combined analysis of flow dynamics in the farm and the behavior of individual turbines within one simulation environment. In this work, we present such an environment by developing a new coupling between the large-eddy simulation (LES) code GRASP and the multiphysics wind turbine simulation tool OpenFAST via an actuator line model (ALM). In addition, the implementation of the recently proposed filtered actuator line model (FALM) within the coupling is described. The new ALM implementation is cross-verified with results from four other commonly used research LES codes. The results for the blade loads and the near wake obtained with the new coupling are consistent with the other codes. Deviations are observed in the far wake. The results further indicate that the FALM is able to reduce the lift and power overprediction from which the traditional ALM suffers on coarse LES grids. This new simulation environment paves the way for future wind farm simulations under realistic weather conditions by leveraging GRASP's ability to impose data from large-scale meteorological models as boundary conditions.

17 WIND ENERGY↗