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At least 1,603 records · Page 89

National Renewable Energy Laboratory/Habitat for Humanity Zero Energy Home: A Cold Climate Case Study for Affordable Zero Energy Homes

The design of this 1,280-square-foot, three-bedroom Habitat for Humanity of Metro Denver zero energy home carefully combines envelope efficiency, efficient equipment, appliances and lighting, and passive and active solar features to reach the zero energy goal. The home was designed with an early version (July 22, 2004) of the BEOpt building optimization software; DOE2 and TRNSYS were used to perform additional analysis. This engineering approach was tempered by regular discussions with Habitat construction staff and volunteers. These discussions weighed the applicability of the optimized solutions to the special needs and economics of a Habitat house, moving the design toward simple, easily maintained mechanical systems and volunteer-friendly construction techniques. A data acquisition system was installed in the completed home to monitor its performance. The home's energy performance was monitored for 10 years. A comprehensive report on the home was done after the first 2 years of monitoring and a follow-up ACEEE paper on the project including 10 years of performance data was presented in 2016.

Affordable Housing↗

ADAM: A web platform for graph-based modeling and optimization of supply chains

Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. Here, in this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

97 MATHEMATICS AND COMPUTING↗

Processable High Electron Mobility {pi}-Copolymers via Mesoscale Backbone Conformational Ordering

The synthesis and experimental/theoretical characterization of a new series of electron-transporting copolymers based on the naphthalene bis(4,8-diamino-1,5-dicarboxyl)amide (NBA) building block are reported. Comonomers are designed to test the emergent effects of manipulating backbone torsional characteristics, and density functional theory (DFT) analysis reveals the key role of backbone conformation in optimizing electronic delocalization and transport. The NBA copolymer conformational and electronic properties are characterized using a broad array of molecular/macromolecular, thermal, optical, electrochemical, and charge transport techniques. All NBA copolymers exhibit strongly aggregated morphologies with significant nanoscale order. Copolymer charge transport properties are investigated in thin-film transistors and exhibit excellent electron mobilities ranging from 0.4 to 4.5 cm(2) V-1 s(-1). Importantly, the electron transport efficiency correlates with the film mesoscale order, which emerges from comonomer-dependent backbone planarity and extension. These results illuminate the key NBA building block structure-morphology-bulk property design relationships essential for processable, electronics-applicable high-performance polymeric semiconductors.

n‐↗

Critical Analysis of Replacements for R-410A in Heat Pump Applications

Using low-GWP refrigerants can reduce the Green House Gas (GHG) emission of HVAC systems. Research has shown that using heat exchangers with small diameter tubes is a promising solution to meet the performance goals of heat pump using low-GWP refrigerants due to reduced refrigerant charge, reduced flammable impact and environmental impact. However, application of small diameter tube requires in-depth component design optimization to make the new system adapt to low-GWP refrigerants.In this paper, multi-objective optimizations using Particle Swarm Optimization (PSO) algorithm on a R-410A residential 5-ton air source heat pump is performed for improved system performance and reduced material cost. Five R-410A alternatives, i.e., R-32, R-454A, R-454B, R-454C and R-455A are investigated. R-455A and R-454C have GWP lower than 150. As a result of optimization, 12.4%-19.1% Energy Efficiency Ratio (EER) improvement and up to 71% HXs material cost saving is achieved. Life Cycle Climate Performance (LCCP) analysis shows that optimized systems reduce total CO2 emission by 13%-33% depending on the choice of refrigerant and climate zone.The optimal heat exchangers resulting from this research can fit into the original R-410A fan-coil units. The proposed heat pump design method establishes a production and installation path to produce cost-effective low-GWP heat pumps easily accepted by end users.

Li, Zhenning↗

Improved Nondestructive Isotopic Analysis with Practical Microcalorimeter Gamma Spectrometers

Advances in both instrumentation and data analysis software are now enabling the first ultra-high-resolution microcalorimeter gamma spectrometers designed for implementation in nuclear facilities and analytical laboratories. With approximately ten times better energy resolution than high-purity germanium detectors, these instruments can overcome important uncertainty limits. Microcalorimeter gamma spectroscopy is intended to provide nondestructive isotopic analysis capabilities with sufficient precision and accuracy to reduce the need for sampling, chemical separations, and mass spectrometry to meet safeguards and security goals. Key milestones were the development of the SOFIA instrument (Spectrometer Optimized for Facility Integrated Applications) and the SAPPY software (Spectral Analysis Program in PYthon). SOFIA is a compact instrument that combines advances in large multiplexed transition-edge sensor arrays with optimized cryogenic performance to overcome many practical limitations of previous systems. With a 256-pixel multiplexed detector array capable of 5,000 counts per second, measurement time can be comparable to high-purity germanium detectors. SAPPY was developed to determine isotopic ratios in data from SOFIA and other microcalorimeter instruments with an approach similar to the widely-used FRAM software. SAPPY provides a flexible framework with rigorous uncertainty analysis for both microcalorimeter and high purity germanium (HPGe) data, allowing direct comparison. Here, we present current results from the SOFIA instrument, preliminary isotopic analysis using SAPPY, and describe how the technology is being used to explore uncertainty limits of nondestructive isotopic characterization, inform safeguards models, and extract improved nuclear data including gamma-ray branching ratios.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Real-Time Optimization Workflow Status Update

Economically optimal and safe operation of integrated energy systems (IES) requires optimization at many different time scales. A real-time optimization (RTO) workflow will attempt to maximize revenue and minimize operational costs on a time scale of minutes to hours. Such a workflow requires the use of a digital twin (DT), which is a virtual representation of a physical system. The DT is updated using real-time data from the physical system, and serves as a model in an optimization framework. The optimization results are then sent back to the physical system to complete the loop. This report details the progress made in developing building blocks for a DT/RTO framework. The Risk Analysis Virtual Environment (RAVEN) platform within the Framework for Optimization of Resources and Economics (FORCE) tool suite can perform many of the tasks required for building a DT and performing RTO. The first item of this report details RAVEN enhancements that enable RAVEN workflows to be run in various environments. Data communication between the physical system and its DT is essential for successful RTO. This includes preprocessing real-time data, loading data into a data warehouse, and querying the stored data. The second section of this report describes the progress made in implementing an adapter in Python in order for Deep Lynx to handle the data communication. Typical dispatch optimization frameworks are built on linear programming (LP). The prototype RTO workflow developed in this report uses an LP problem as a part of a receding-horizon- or economic model predictive control (EMPC) based optimization. The third section of this report details the framework of an RTO workflow in which the system consists of a simple electrical storage device. A DT can be built from a reduced-order model (ROM). Integrating a ROM into a typical LP optimization framework has been challenging because most optimization packages require the user to write algebraic expressions for the system model. The final section of this report shows how an externally built RAVEN ROM can be integrated in an RTO framework by using the Python package Pyomo. This demonstrates the RTO workflow capability from a software-only perspective and is an important step in demonstrating the capability to implement an RTO workflow for a physical system.

97 MATHEMATICS AND COMPUTING↗

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advancing the STS Neutron Moderator Design with an Automated Optimization Workflow and Unstructured Mesh Modeling

With the Second Target Station approaching its final design phase, a detailed neutronics evaluation of its critical components is necessary. Optimizing the dimensions of the two cold-source moderators that are at the heart of this facility presents a multi-objective optimization problem for which an accurate geometric description is crucial. We have applied a fully automated optimization workflow in which a detailed unstructured mesh geometry is automatically generated with Attila4MC, starting from a parametrized CREO geometry followed by preprocessing with SpaceClaim. With this geometry, a MCNP run is performed to calculate the brightness metrics, which are subsequently provided to the optimization algorithm in DAKOTA that provides new parameters and drives the optimization loop until convergence. In this paper, we show the results of the analysis that are used for the final design of the cylindrical and tube moderator. The optimization simulations provide a refinement to and confirmation of the conclusions of the previous design iteration. Additional to the optimization, a sensitivity study is performed to study the effect of minor geometry changes, which is important for the final engineering design. In conclusion, with these studies, we demonstrate that the automated workflow and high-fidelity unstructured mesh modeling are efficient tools for a thorough design evaluation.

DAKOTA↗

A Modeling Tool to Analyze the Performance of Industrial Cooling Towers

Energy efficiency and energy savings have become an important factor as industries look for ways to save energy and minimize their energy consumption while reducing their carbon footprint. Cooling towers are utilized significantly in industries for either serving chillers or process cooling. Depending on the size of the cooling tower, it can use a surprising amount of energy and water, which is why it is crucial to make sure that the facility has optimized their cooling tower.A modeling tool has been developed to perform a thorough analysis of a cooling tower and its various operations to ensure that the facility has optimized its cooling tower. This model analyzes an annual base case in comparison with the revised case of a cooling tower operation. This modeling tool simulates 8,760 hourly calculations for fan power for various fan controls, water consumption, and pumping energy consumption and demand based on the user’s location and its corresponding Typical Meteorological Year 3 (TMY3) weather data. This model is capable to simulate up to five cooling tower cells as one large tower utilizing one pump or parallel pumping. The successful validated cooling tower model should assist industry to save energy at their facility through their cooling tower, whether they use it for process cooling or heating, ventilation and air conditioning (HVAC) applications. The entering/leaving water temperatures based on a monthly operating schedule or a wet-bulb temperature schedule will be used as inputs, and the model can calculate savings in energy for various conditions including variable-frequency drive (VFD) on the fan/pump, drift eliminators, number of cycles of concentration, reduced water flow rate, etc.

Hooper, Josh↗

A lab-based ambient pressure x-ray photoelectron spectrometer with exchangeable analysis chambers

Ambient pressure X-ray photoelectron spectroscopy (APXPS) is a powerful spectroscopy tool that is inherently surface sensitive, elemental, and chemical specific, with the ability to probe sample surfaces under Torr level pressures. Herein, we describe the design of a new lab-based APXPS system with the ability to swap small volume analysis chambers. Ag 3d(5/2) analyses of a silver foil were carried out at room temperature to determine the optimal sample-to-aperture distance, x-ray photoelectron spectroscopy analysis spot size, relative peak intensities, and peak full width at half maximum of three different electrostatic lens modes: acceleration, transmission, and angular. Ag 3d(5/2) peak areas, differential pumping pressures, and pump performance were assessed under varying N{sub 2}(g) analysis chamber pressures up to 20 Torr. The commissioning of this instrument allows for the investigation of molecular level interfacial processes under ambient vapor conditions in energy and environmental research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

MEASURING RISK IMPORTANCE IN A DYNAMIC PRA FRAMEWORK

Risk importance measures are indexes that are used to rank systems, structures and components (SSCs) using risk-informed methods. The most used/known measures are: Risk Reduction Worth (RRW), Risk Achievement Worth (RAW), Birnbaum (B) and Fussell-Vesely (FV). Once obtained from classical Probabilistic Risk Analysis (PRA) analyses, these risk measures can be effectively employed to optimize component testing and maintenance. In contrast to classical PRA methods, Dynamic PRA methods couple stochastic methods with safety analysis codes to determine risk associate to complex systems such as nuclear plants. Compared to classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the accident progression. The objective of this paper is to present a series of algorithms that can be used to determine classical risk importance measures (RRW, RAW, B and FV) along with newly developed ones from a Dynamic PRA analysis.

97 MATHEMATICS AND COMPUTING↗

Spatially Resolved Raman Spectroscopic Investigation of Uranyl Fluoride: A Case Study in the Importance of Instrument Optimization

Raman spectroscopy is an emerging technique for rapid and nondestructive analysis of nuclear materials for forensic and nonproliferation applications as it is a powerful tool for distinguishing multiple chemical forms of materials with similar stoichiometries. Recent developments in spectroscopic software have enabled rapid data collection with high-speed Raman spectroscopic mapping capabilities. However, some uranium-rich materials are susceptible to degradation in humid air and/or laser-induced phase transformations. To mitigate environmental or measurement-related sample degradation of potential samples of interest, we have taken a systematic approach to define optimized data collection parameters for high-throughput measurements of uranyl fluoride (UO 2 F 2 ), which is an important intermediate material in the nuclear fuel cycle. First, we systematically describe the influence of optical magnification (5× to 100×), laser power, and exposure time on obtained signal for identical particles of UO 2 F 2 and find that at low laser power and exposure times, comparable signal is obtained regardless of optical magnification. Second, we ensure sample integrity during data collection, and third, collect spectroscopic maps that employ optimized parameters to reduce the time required to obtain spatially resolved spectroscopic information. Reductions of 90% and 99% in measurement times are discussed as they relate to differences in resolving spectroscopic features of particles in identical mapping areas. Finally, during this work, we found that additional data processing options were needed and thus developed a customized Python script for importing, processing, analyzing, and visualizing Raman spectroscopic map data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Are We Appropriately Selecting Therapy For Patients With Cervical Cancer? Longitudinal Patterns-of-Care Analysis for Stage IB-IIB Cervical Cancer

Purpose: We performed a patterns-of-care analysis evaluating the effects of newer technology and recent research findings on treatment decisions over 26 years to determine whether patients with cervical cancer are being appropriately selected for treatment to optimize the therapeutic ratio. Methods and Materials: A retrospective analysis was conducted using the Surveillance, Epidemiology and End Results (SEER) program from 1983 to 2009. We identified 10,933 women with stage IB-IIB cervical carcinoma. Results: Of the 10,933 subjects identified, 40.1% received surgery, 26.8% received radiation (RT), and 33.1% received surgery plus RT. RT use increased after 2000 compared to prior to 2000, with a corresponding decrease in surgery and surgery plus RT. Among patients with risk factors including tumor size >4 cm, positive parametria, and positive lymph nodes, declining use of surgery plus RT was observed. However, 23% of patients with tumors >4 cm, 20% of patients with positive parametria, and 55% of node-positive patients continued to receive surgery plus RT as of 2009. Factors associated with increased use of surgery plus RT included patient age <50 and node-positive status. Conclusions: In this largest patterns-of-care analysis to date for patients with locally advanced cervical cancer, we found a substantial proportion of patients continue to undergo surgery followed by radiation, despite randomized data supporting the use of definitive radiation therapy, with lower morbidity than surgery and radiation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Regarding the optimization of O1-mode ECRH and the feasibility of EBW startup on NSTX-U

Recently published scenarios for fully non-inductive startup and operation on the National SphericalTorus eXperiment Upgrade (NSTX-U) (Menard et al 2012 Nucl. Fusion 52 083015) show ElectronCyclotron Resonance Heating (ECRH) as an important component in preparing a target plasma forefficient High Harmonic Fast Wave and Neutral Beam heating. The modeling of the propagation andabsorption of EC waves in the evolving plasma is required to define the most effective window ofoperation, and to optimize the launcher geometry for maximal heating and current drive during thiswindow. Here, we extend a previous optimization of O1-mode ECRH on NSTX-U to account for thefull time-dependent performance of the ECRH using simulations performed with TRANSP. We findthat the evolution of the density profile has a prominent role in the optimization by defining the timewindow of operation, which in certain cases may be a more important metric to compare launcherperformance than the average power absorption. This feature cannot be captured by analysis on staticprofiles, and should be accounted for when optimizing ECRH on any device that operates near thecutoff density. Additionally, the utility of the electron Bernstein wave (EBW) in driving current andgenerating closed flux surfaces in the early startup phase has been demonstrated on a number ofdevices. Using standalone GENRAY simulations, we find that efficient EBW current drive ispossible on NSTX-U if the injection angle is shifted below the midplane and aimed towards the tophalf of the vacuum vessel. However, collisional damping of the EBW is projected to be significant, insome cases accounting for up to 97% of the absorbed EBW power

Electron Bernstein wave↗

BLEECAM™ (Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials) [SWR-25-125]

The National Laboratory of the Rockies' (NLR) Benchmarking Life Cycle Environmental, Economic, and Social Metrics for Critical and Advanced Minerals and Materials (BLEECAM™) is an open-source, integrated decision-support tool for evaluating the impacts, risks, and trade-offs across U.S. and global materials supply chains. Funded by the U.S. Department of Energy, BLEECAM supports supply chain and market analysis. The tool integrates multi-objective supply chain optimization, system dynamics, network design, lifecycle assessment, techno-economic modeling, and social impact assessment methods to evaluate how supply chains evolve over time, geography, and deployment scenarios. BLEECAM also supports analysis related to energy infrastructure, data centers and digital infrastructure, advanced manufacturing, and other sectors that depend on critical materials.

Khalifa, SherifA. [National Laboratory of the Rock↗

Feedstock Supply Chain Analysis

Addressing the challenge of biomass feedstock variability that affects the optimization of processing and conversion processes, the project's goal is to maximize biorefinery economics by improving the process quality control of feedstock, which will lead to greater plant availability and predictable yields of high value biofuels and co-products.

09 BIOMASS FUELS↗

Criticality safety evaluation for the Advanced Test Reactor enhanced low enriched uranium fuel elements

The Global Threat Reduction Initiative (GTRI) convert program is developing a high uranium density fuel based on a low enriched uranium (LEU) uranium-molybdenum alloy. Testing of prototypic GTRI fuel elements is necessary to demonstrate integrated fuel performance behavior and scale-up of fabrication techniques. GTRI Enhanced LEU Fuel (ELF) elements based on the ATR-Standard Size elements (all plates fueled) are to be fabricated for testing in the Advanced Test Reactor (ATR). While a specific ELF element design will eventually be provided for detailed analyses and in-core testing, this criticality safety evaluation (CSE) is intended to evaluate a hypothetical ELF element design for criticality safety purposes. Existing criticality analyses have analyzed Standard (HEU) ATR elements from which controls have been derived. This CSE documents analysis that determines the reactivity of the hypothetical ELF fuel elements relative to HEU ATR elements and whether the existing HEU ATR element controls bound the ELF element. The initial calculations presented in this CSE analyzed the original ELF design, now referred to as Mod 0.1. In addition, as part of a fuel meat thickness optimization effort for reactor performance, other designs have been evaluated. As of early 2014 the most current conceptual designs are Mk1A and Mk1B, that were previously referred to as conceptual designs Mod 0.10 and Mod 0.11, respectively. Revision 1 evaluates the reactivity of the ATR HEU Mark IV elements for a comparison with the Mark VII elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗