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DOE OSTI2022

Workforce Development Bioenergy Experiential Learning Tool (Final Report)

The "Pathways to Bio-Power" program was designed as a workforce development initiative aimed at addressing the workforce gap in the bioenergy sector while promoting diversity and inclusion. The program incorporated advanced technologies, such as artificial intelligence (AI) and learning algorithms, to provide individualized training plans and pathways for Minority Business Enterprises (MBEs) and the current workforce to enter the bioenergy industry. However, after careful consideration, it was determined that proceeding to Phase II was not feasible due to several reasons related to resource allocation, market demand, and technical challenges.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Demo 5: RapidClave Technology Demonstrations – Round II (Task 2)

The purpose of this project task was to make automotive composite part manufacturing more cost competitive for low volume production and thereby drive composite application innovation. The strategy was to incorporate low-cost preforming, snap cure resins, and RapidClave® processing to create an alternative to conventional automotive composite manufacturing based on SMC. The program used RapidClave® technology from Globe Machine Manufacturing, fast-curing (“snap cure”) epoxy resins from Hexion, and conformable/stretchable glass fiber reinforcement mats produced by Owens Corning for rapid preforming. O’Gara Armoring retrofits vehicles to meet special security needs, such as larger doors to facilitate easier entry into the vehicle. O’Gara has a variety of custom vehicles in need of custom doors that require affordable tooling to produce approximately 100 ship sets/year. The project focused on a composite door panel application provided by O’Gara that is currently made by manual chopped fiber spray-up processing. UDRI reverse-engineered the current composite door panel and created tooling for use in the RapidClave®. UDRI designed an improved composite door using MultiMat fiberglass reinforcement from Owens Corning. UDRI made snap cure resin films from Hexion resin. Finally, UDRI conducted molding trials to compare autoclave processing with RapidClave® processing. The technical goals of the project were to reduce tooling cost by 50% as compared to SMC compression molding and to reduce cycle time by 50% compared to current manual spray-up process. The approach to reduce tool costs is based on use of single sided tooling for use at 100 psi, as compared to matched metal SMC tooling. An added benefit realized from the program is that the Owens Corning mat provided more uniform thickness and improved performance. Tensile and flexural strengths and moduli were increased by at least 50%. This task also demonstrated a 75% decrease in cycle time. O’Gara is evaluating the technology demonstrated in this project for some of their current production. Additionally, there are new products O’Gara is pursuing which require higher production rates than their current products. O’Gara has identified these new products as good candidates for the RapidClave® technology. The cost advantages demonstrated by this project would then lead to significant economic development. In conclusion, this task successfully combined the RapidClave® technology from Globe with a snap cure epoxy resin film system from Hexion and preform material from Owens Corning. Further research is needed to better map the technical limits such as cycle time of these technologies. Additionally, the technology should be extended in terms of size and shape to include large parts outside of automotive applications, such as a small aircraft fuselage.

36 MATERIALS SCIENCE↗

DOE OSTI2024

E-PVT: enhanced position-velocity-time scheduler for computer-controlled optical finishing with comprehensive considerations of dynamics constraints, continuity and efficiency

Deterministic computer-controlled optical finishing is an essential approach for achieving high-quality optical surfaces. Its determinism and convergence rely heavily on precise and smooth motion control to guide the machine tool over an optical surface to correct residual errors. One widely supported and smooth motion control model is position-velocity-time (PVT), which employs piecewise cubic polynomials to describe positions. Our prior research introduced a PVT-based velocity scheduling method, demonstrating sub-nanometer level convergence in ion beam figuring (IBF) processes. However, three challenges remained. Firstly, this method relies on quadratic programming, resulting in computational intensiveness for dense tool paths. Secondly, the dynamics constraints and velocity and acceleration continuities are not comprehensively considered, limiting the full potential of PVT-based control. Thirdly, no compensation mechanism existed when dynamics constraints are exceeded. In this study, in response to these challenges, we proposed the Enhanced PVT (E-PVT) method, reducing the time complexity from O ( n 3 ) to O ( n ) while fully addressing dynamics constraints and continuities. A novel compensation method utilizing particle swarm optimization was proposed to address situations where dynamics constraints might be exceeded while maintaining the overall processing efficiency. Validation through simulation and experimentation confirmed the improved performance of E-PVT.

36 MATERIALS SCIENCE↗

DOE OSTI2013

Cementitious Barriers Partnership FY2013 End-Year Report

In FY2013, the Cementitious Barriers Partnership (CBP) demonstrated continued tangible progress toward fulfilling the objective of developing a set of software tools to improve understanding and prediction of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. In November 2012, the CBP released “Version 1.0” of the CBP Software Toolbox, a suite of software for simulating reactive transport in cementitious materials and important degradation phenomena. In addition, the CBP completed development of new software for the “Version 2.0” Toolbox to be released in early FY2014 and demonstrated use of the Version 1.0 Toolbox on DOE applications. The current primary software components in both Versions 1.0 and 2.0 are LeachXS/ORCHESTRA, STADIUM, and a GoldSim interface for probabilistic analysis of selected degradation scenarios. The CBP Software Toolbox Version 1.0 supports analysis of external sulfate attack (including damage mechanics), carbonation, and primary constituent leaching. Version 2.0 includes the additional analysis of chloride attack and dual regime flow and contaminant migration in fractured and non-fractured cementitious material. The LeachXS component embodies an extensive material property measurements database along with chemical speciation and reactive mass transport simulation cases with emphasis on leaching of major, trace and radionuclide constituents from cementitious materials used in DOE facilities, such as Saltstone (Savannah River) and Cast Stone (Hanford), tank closure grouts, and barrier concretes. STADIUM focuses on the physical and structural service life of materials and components based on chemical speciation and reactive mass transport of major cement constituents and aggressive species (e.g., chloride, sulfate, etc.). THAMES is a planned future CBP Toolbox component focused on simulation of the microstructure of cementitious materials and calculation of resultant hydraulic and constituent mass transfer parameters needed in modeling. Two CBP software demonstrations were conducted in FY2013, one to support the Saltstone Disposal Facility (SDF) at SRS and the other on a representative Hanford high-level waste tank. The CBP Toolbox demonstration on the SDF provided analysis on the most probable degradation mechanisms to the cementitious vault enclosure caused by sulfate and carbonation ingress. This analysis was documented and resulted in the issuance of a SDF Performance Assessment Special Analysis by Liquid Waste Operations this fiscal year. The two new software tools supporting chloride attack and dual-regime flow will provide additional degradation tools to better evaluate performance of DOE and commercial cementitious barriers. The CBP SRNL experimental program produced two patent applications and field data that will be used in the development and calibration of CBP software tools being developed in FY2014. The CBP software and simulation tools varies from other efforts in that all the tools are based upon specific and relevant experimental research of cementitious materials utilized in DOE applications. The CBP FY2013 program involved continuing research to improve and enhance the simulation tools as well as developing new tools that model other key degradation phenomena not addressed in Version 1.0. Also efforts to continue to verify the various simulation tools through laboratory experiments and analysis of field specimens are ongoing and will continue into FY2014 to quantify and reduce the uncertainty associated with performance assessments. This end-year report summarizes FY2013 software development efforts and the various experimental programs that are providing data for calibration and validation of the CBP developed software.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2013

Development of Models to Simulate Tracer Tests for Characterization of Enhanced Geothermal Systems

A recent report found that power and heat produced from enhanced (or engineered) geothermal systems (EGSs) could have a major impact on the U.S energy production capability while having a minimal impact on the environment. EGS resources differ from high-grade hydrothermal resources in that they lack sufficient temperature distribution, permeability/porosity, fluid saturation, or recharge of reservoir fluids. Therefore, quantitative characterization of temperature distributions and the surface area available for heat transfer in EGS is necessary for the design and commercial development of the geothermal energy of a potential EGS site. The goal of this project is to provide integrated tracer and tracer interpretation tools to facilitate this characterization. This project was initially focused on tracer development with the application of perfluorinated tracer (PFT) compounds, non-reactive tracers used in numerous applications from atmospheric transport to underground leak detection, to geothermal systems, and evaluation of encapsulated PFTs that would release tracers at targeted reservoir temperatures. After the 2011 midyear review and subsequent discussions with the U.S. Department of Energy Geothermal Technology Program (GTP), emphasis was shifted to interpretive tool development, testing, and validation. Subsurface modeling capabilities are an important component of this project for both the design of suitable tracers and the interpretation of data from in situ tracer tests, be they single- or multi-well tests. The purpose of this report is to describe the results of the tracer and model development for simulating and conducting tracer tests for characterizing EGS parameters.

EGS↗

DOE OSTI2024

Evaluating the Impact of Off-Design CHP Performance on the Optimal Sizing and Dispatch on Hybrid Renewable-CHP Distributed Energy Resources

The maturation of distributed energy resources (DER) has prompted the exploration of their deployment in commercial building applications due to their potential to supply energy at lower costs and emissions rates compared to centralized generation. While several software tools exist for evaluating the techno-economic potential of integrated renewable energy and combined heat and power (CHP) systems for distributed generation applications, many suffer from poor accuracy in capturing off-design (part load and changes in ambient air temperature and pressure) performance characteristics of microturbines, combustion turbines, or internal combustion engines. Thus, this paper presents a methodology for integrating these off-design characteristics in the mixed-integer linear program within REopt, a hybrid DER screening tool. The economic impact of the CHP off-design performance is observed through several application studies of various hybrid system configurations in different climates. Each study indicates how CHP off-design performance influences optimal sizing and dispatch decisions and therefore overall system economic value. We observe through case studies that modeling without the off-design effects, depending on the CHP prime mover and site, can result in Net Present Value predictions of hybrid systems that can be overoptimistic in frequently hot climates (up to 52%), too conservative in frequently cold climates (up to 11%), or unaffected (+/-1%) in temperate climates. Cases also highlight several advantages of hybrid systems relative to non-hybrid systems such as total economic value and the systems' ability to mitigate potentially negative consequences attributed to off-design performance.

ambient de-rate↗

DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

DOE OSTI2015

High-Power Microwave Transmission and Mode Conversion Program

This is a final technical report for a long term project to develop improved designs and design tools for the microwave hardware and components associated with the DOE Plasma Fusion Program. We have developed basic theory, software, fabrication techniques, and low-power measurement techniques for the design of microwave hardware associated gyrotrons, microwave mode converters and high-power microwave transmission lines. Specifically, in this report we discuss our work on designing quasi-optical mode converters for single and multiple frequencies, a new method for the analysis of perturbed-wall waveguide mode converters, perturbed-wall launcher design for TE0n mode gyrotrons, quasi-optical traveling-wave resonator design for high-power testing of microwave components, and possible improvements to the HSX microwave transmission line.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Developing the Proof of Concept for the SERI QC Flag Translation

SERI QC is a robust solar data quality assessment software tool that has been in continuous use for more than three decades. This report, the second of six in the Data Quality and Uncertainty Integration project, develops the proof of concept, including programming in C and a collection of spreadsheet tools, for estimating the operational uncertainty from three-component solar irradiance measurements using information available from SERI QC. The report establishes a field reference for determining the operational uncertainty for each irradiance component based on the SERI QC coupling. Results demonstrate that the operational uncertainty estimates based on global irradiance best represent the collective results for all sky conditions.

14 SOLAR ENERGY↗

DOE OSTI2025

Compressed Air Scoping Tool Teaches Energy Efficiency Best Practices

Standards and practices around compressed air systems are evolving as previous golden rules become outdated and unhelpful. One of the most referenced guidelines gives us the perfect example: The previous rule of thumb for compressed air storage – 1-3 gal/cfm1,2 – is now accepted to be 3-5 gal/cfm. This change in recommended storage is only one of many in the industry, resulting in industrial users lost in a sea of contradictory best practices. To help combat confusion and poor information sharing, a collaborative effort between Oak Ridge National Laboratory (ORNL) and the Department of Energy’s (DOE’s) Better Plants program created the Compressed Air (CA) Scoping Tool with the most up-to-date best practices in the industry (as of 2023). It can be used as a nonbiased, one-stop shop for best practice recommendations. The Excelbased tool is designed to be an initial step in understanding the operation of a compressed air system, a baselining tool enabling users to comprehend various aspects of a facility’s system from the production of compressed air to its application by end users.

42 ENGINEERING↗

DOE OSTI2017

Application of automated measurement and verification to utility energy efficiency program data

Trustworthy savings calculations are critical to convincing regulators of both the cost-effectiveness of energy efficiency program investments and their ability to defer supply-side capital investments. Today’s methods for measurement and verification (M&V) of energy savings constitute a significant portion of the total costs of energy efficiency programs. They also require time-consuming data acquisition. A spectrum of savings calculation approaches is used, with some relying more heavily on measured data and others relying more heavily on estimated, modeled, or stipulated data. The increasing availability of “smart” meters and devices that report near-real time data, combined with new analytical approaches to quantify savings, offers the potential to conduct M&V more quickly and at lower cost, with comparable or improved accuracy. Commercial energy management and information systems (EMIS) technologies are beginning to offer these ‘M&V 2.0’ capabilities, and program administrators want to understand how they might assist programs in quickly and accurately measuring energy savings. This paper presents the results of recent testing of the ability to use automation to streamline the M&V process. In this paper, we apply an automated whole-building M&V tool to historic data sets from energy efficiency programs to begin to explore the accuracy, cost, and time trade-offs between more traditional M&V, and these emerging streamlined methods that use high-resolution energy data and automated computational intelligence. For the data sets studied we evaluate the fraction of buildings that are well suited to automated baseline characterization, the uncertainty in gross savings that is due to M&V 2.0 tools’ model error, and indications of labor time savings, and how the automated savings results compare to prior, traditionally determined savings results. The results show that 70% of the buildings were well suited to the automated approach. In a majority of the cases (80%) savings and uncertainties for each individual building were quantified to levels above the criteria in ASHRAE Guideline 14. In addition the findings suggest that M&V 2.0 methods may also offer time-savings relative to traditional approaches. Lastly, we discuss the implications of these findings relative to the potential evolution of M&V, and pilots currently being launched to test how M&V automation can be integrated into ratepayer-funded programs and professional implementation and evaluation practice.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

The ADAQ framework: An integrated toolkit for data acquisition and analysis with real and simulated radiation detectors

Here, the ADAQ framework is a collection of software tools that is designed to streamline the acquisition and analysis of radiation detector data produced in modern digital data acquisition (DAQ) systems and in Monte Carlo detector simulations. The purpose of the framework is to maximize user scientific pro-ductivity by minimizing the effort and expertise required to fully utilize radiation detectors in a variety of scientific and engineering disciplines. By using a single set of tools to span the real and simulation domains, the framework eliminates redundancy and provides an integrated workflow for high-fidelity comparison between experimental and simulated detector performance. Built on the ROOT data analysis framework, the core of the ADAQ framework is a set of Cþþ and Python libraries that enable high-level control of digital DAQ systems and detector simulations with data stored into standardized binary ROOT files for further analysis. Two graphical user interface programs utilize the libraries to create powerful tools: ADAQAcquisition handles control and readout of real-world DAQ systems and ADAQAnalysis provides data analysis and visualization methods for experimental and simulated data. At present, the ADAQ framework supports digital DAQ hardware from CAEN S.p.A. and detector simulations performed in Geant4; however, the modular design will facilitate future extension to other manufacturers and simulation platforms.

detector simulation↗

DOE OSTI2017

Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Applications of the Dulmage–Mendelsohn decomposition for debugging nonlinear optimization problems

Nonlinear modeling and optimization is a valuable tool for aiding decisions by engineering practitioners, but programming an optimization problem based on a complex electrical, mechanical, or chemical process is a time-consuming and error-prone activity. Therefore, there is a need for model analysis and debugging tools that can detect and diagnose modeling errors. One such tool is the Dulmage–Mendelsohn decomposition, which identifies structurally under- and over-determined subsets in systems of equations and variables by partitioning the bipartite graph of the system. This work provides the necessary background to understand the Dulmage–Mendelsohn decomposition and its application to the analysis of nonlinear optimization problems, demonstrates its use in diagnosing a variety of modeling errors, and introduces software implementations for analyzing nonlinear optimization problems in the Pyomo and JuMP algebraic modeling languages.

42 ENGINEERING↗

DOE OSTI2024

Assessing Inverter-Based Resources Modeling Gaps in Commonly Used Short-Circuit Programs

Future bulk power systems are expected to operate with a high penetration of inverter-based resources (IBR). This is anticipated to fundamentally change the system’s short-circuit behaviors and demand a change in existing transmission line protection settings or schemes. Phasor-domain short circuit programs (e.g., ASPEN, CAPE, and CYME) remain the mainstream tools for developing protection settings. However, the system protection community has shared concerns about the accuracy of IBR models in short-circuit programs. This report compares the performance of existing generic IBR models in short-circuit programs with detailed electro-magnetic transient (EMT) models provided by several different IBR manufacturers in PSCAD, to quantify the short-circuit program’s IBR model accuracy, assess their ability to replicate individual IBR controls such as negative sequence current injections, and identify specific gaps in the existing generic phasor-domain IBR models that are currently available.

42 ENGINEERING↗

DOE OSTI2015

Designs for Risk Evaluation and Management

The Designs for Risk Evaluation and Management (DREAM) tool was developed as part of the effort to quantify the risk of geologic storage of carbon dioxide (CO 2 ) under the U.S. Department of Energy's National Risk Assessment Partnership (NRAP). DREAM is an optimization tool created to identify optimal monitoring schemes that minimize the time to first detection of CO 2 leakage from a subsurface storage formation. DREAM acts as a post-processer on user-provided output from subsurface leakage simulations. While DREAM was developed for CO 2 leakage scenarios, it is applicable to any subsurface leakage simulation of the same output format. The DREAM tool is comprised of three main components: (1) a Java wizard used to configure and execute the simulations, (2) a visualization tool to view the domain space and optimization results, and (3) a plotting tool used to analyze the results. A secondary Java application is provided to aid users in converting common American Standard Code for Information Interchange (ASCII) output data to the standard DREAM hierarchical data format (HDF5). DREAM employs a simulated annealing approach that searches the solution space by iteratively mutating potential monitoring schemes built of various configurations of monitoring locations and leak detection parameters. This approach has proven to be orders of magnitude faster than an exhaustive search of the entire solution space. The user's manual illustrates the program graphical user interface (GUI), describes the tool inputs, and includes an example application.

(Ruprecht) Yonkofski, Catherine↗

DOE OSTI2020

National Grid: Using the LEAD Tool Data to Target Energy Affordability Services to Eligible Customers in New York

In the following use case, investor-owned utility company, National Grid, used the Low-Income Energy Affordability Data (LEAD) Tool to support the implementation of its Home Energy Affordability Team (HEAT), a weatherization program for income-eligible residential natural gas customers in its service territory in Long Island, New York. Using LEAD Tool data, National Grid was able to determine how many households may be eligible for the program to inform additional marketing efforts. This use case is an example of how utilities of all sizes and types in the United States can use the LEAD Tool in similar ways to gain insights and better address customer energy affordability needs.

Low-Income Energy Affordability Data Tool, LEAD To↗

DOE OSTI2014

MO-E-9A-01: Risk Based Quality Management: TG100 In Action

One of the goals of quality management in radiation therapy is to gain high confidence that patients will receive the prescribed treatment correctly. To accomplish these goals professional societies such as the American Association of Physicists in Medicine (AAPM) has published many quality assurance (QA), quality control (QC), and quality management (QM) guidance documents. In general, the recommendations provided in these documents have emphasized on performing device-specific QA at the expense of process flow and protection of the patient against catastrophic errors. Analyses of radiation therapy incidents find that they are most often caused by flaws in the overall therapy process, from initial consult through final treatment, than by isolated hardware or computer failures detectable by traditional physics QA. This challenge is shared by many intrinsically hazardous industries. Risk assessment tools and analysis techniques have been developed to define, identify, and eliminate known and/or potential failures, problems, or errors, from a system, process and/or service before they reach the customer. These include, but are not limited to, process mapping, failure modes and effects analysis (FMEA), fault tree analysis (FTA), and establishment of a quality management program that best avoids the faults and risks that have been identified in the overall process. These tools can be easily adapted to radiation therapy practices because of their simplicity and effectiveness to provide efficient ways to enhance the safety and quality of treatment processes. Task group 100 (TG100) of AAPM has developed a risk-based quality management program that uses these tools. This session will be devoted to a discussion of these tools and how these tools can be used in a given radiotherapy clinic to develop a risk based QM program. Learning Objectives: Learn how to design a process map for a radiotherapy process. Learn how to perform a FMEA analysis for a given process. Learn what Fault tree analysis is all about. Learn how to design a quality management program based upon the information obtained from process mapping, FMEA and FTA.

60 APPLIED LIFE SCIENCES↗