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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Evaluation of Missed Energy Saving Opportunity Based on Illinois Home Performance Program Field Data: Homeowner Selected Upgrades vs. Cost-Optimized Solutions; Chicago, Illinois (Fact Sheet)

Expanding on previous research by PARR, this study compares measure packages installed during 800 Illinois Home Performance with ENERGY STAR (IHP) residential retrofits to those recommended as cost-optimal by Building Energy Optimization (BEopt) modeling software. In previous research, cost-optimal measure packages were identified for fifteen Chicagoland single family housing archetypes, called housing groups. In the present study, 800 IHP homes are first matched to one of these fifteen housing groups, and then the average measures being installed in each housing group are modeled using BEopt to estimate energy savings. For most housing groups, the differences between recommended and installed measure packages is substantial. By comparing actual IHP retrofit measures to BEopt-recommended cost-optimal measures, missed savings opportunities are identified in some housing groups; also, valuable information is obtained regarding housing groups where IHP achieves greater savings than BEopt-modeled, cost-optimal recommendations. Additionally, a measure-level sensitivity analysis conducted for one housing group reveals which measures may be contributing the most to gas and electric savings. Overall, the study finds not only that for some housing groups, the average IHP retrofit results in more energy savings than would result from cost-optimal, BEopt-recommended measure packages, but also that linking home categorization to standardized retrofit measure packages provides an opportunity to streamline the process for single family home energy retrofits and maximize both energy savings and cost-effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of Missed Energy Saving Opportunity Based on Illinois Home Performance Program Field Data: Homeowner Selected Upgrades Versus Cost-Optimized Solutions

Expanding on previous research by PARR, this study compares measure packages installed during 800 Illinois Home Performance with ENERGY STAR® (IHP) residential retrofits to those recommended as cost-optimal by Building Energy Optimization (BEopt™) modeling software. In previous research, cost-optimal measure packages were identified for fifteen Chicagoland single family housing archetypes, called housing groups. In the present study, 800 IHP homes are first matched to one of these fifteen housing groups, and then the average measures being installed in each housing group are modeled using BEopt to estimate energy savings. For most housing groups, the differences between recommended and installed measure packages is substantial. By comparing actual IHP retrofit measures to BEopt-recommended cost-optimal measures, missed savings opportunities are identified in some housing groups; also, valuable information is obtained regarding housing groups where IHP achieves greater savings than BEopt-modeled, cost-optimal recommendations. Additionally, a measure-level sensitivity analysis conducted for one housing group reveals which measures may be contributing the most to gas and electric savings. Overall, the study finds not only that for some housing groups, the average IHP retrofit results in more energy savings than would result from cost-optimal, BEopt recommended measure packages, but also that linking home categorization to standardized retrofit measure packages provides an opportunity to streamline the process for single family home energy retrofits and maximize both energy savings and cost-effectiveness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Serpent transient analyses of GIACINT geometrical change experiments

This paper simulates seven transient experiments with geometrical movements performed at the GIACINT facility of Belarus. These experiments include three slow control rods insertion in more than 25 s, one fast control rod insertion in less than 1 s, and three water moderator draining transients. In the fast control rod insertion experiment, the control rods are first pushed by a mechanical spring and then let fall by gravity in the assembly. In this experiment, the control rods speed varies because of the initial spring force, the gravitational acceleration, and the water buoyancy force. In all other transient experiments, the geometry change occurs with a constant speed. The Serpent computer program was utilized to simulate these transient experiments with geometrical changes by performing two separate computations. One time-independent computation is performed in criticality mode and the other time-dependent computation is performed in dynamic-source mode. The first computation writes the neutron population and delayed neutron precursors for starting the transient simulation. The second computation divides the transient time into several time bins, reads the two files from the first computation, and updates them at the end of each time bin. The Serpent simulation results obtained for this set of experiments are in good agreement with the time dependent experimental measurements. In addition, Serpent and MCNP simulations results show an excellent agreement for the water moderator transient

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Stochastic optimization of cellulosic biofuel supply chain incorporating feedstock yield uncertainty

The global goal to reduce dependence on fossil fuels and to mitigate greenhouse gas emissions has resulted in research focused on environment friendly and socio-economically sustainable renewable energy sources. However, commercial production of bio-energy is constrained by biomass supply uncertainty and associated costs. This study presents an integrated approach to determining the optimal biofuel supply chain considering biomass yield uncertainty. A two-stage stochastic mixed integer linear programming is utilized to minimize the expected system cost while incorporating yield uncertainty in the strategic level decisions related to biomass production and biorefinery investment. Applicability of the stochastic model is illustrated through a case study of switchgrass-based biofuel in west Tennessee.

09 BIOMASS FUELS↗

Machine Learning of In-situ Temperature Reconstruction from Metal-nanoparticle Thermometry on Transmission Electron Microscopy

Utilizing Python programming language and third-party libraries, 2D temperature fields were reconstructed from TEM images demonstratively and a GUI was created. Local temperatures can be fast read on TEM at the nanoscale based on the nanoparticle thermometry. The Artificial Intelligence technique would speed up the in-situ heating TEM research and make real-time in-situ temperature monitoring possible at nanoscale.

42 ENGINEERING↗

Note: Characteristic beam parameter for the line electron gun

We have optimized the beam parameters of line source electron gun using Stanford Linear Accelerator Centre electron beam trajectory program (EGUN), utilizing electrostatic focusing only. We measured minimum beam diameter as 0.5 mm that corresponds to power density of 68.9 kW/cm{sup 2} at 13.5 mm in the post-anode region which is more than two-fold (33 kW/cm{sup 2}), of the previously reported results. The gun was operated for the validation of the theoretical results and found in good agreement. The gun is now without any magnetic and electrostatic focusing thus much simpler and more powerful.

43 PARTICLE ACCELERATORS↗

DP-Based Optimization of BESS to Substitute RICE Reserves for Improved Economic Benefits

In regions with a significant proportion of renewable energy sources, reciprocating internal combustion engines (RICE or IC) are frequently employed as grid reserve solutions. This study suggests a scheduling technique for battery energy storage systems (BESS) that utilizes dynamic programming (DP) to replace IC units, adding versatility to the total reserve capacity and resulting in higher BESS earnings compared to traditional scheduling approaches. The capacity sweeping approach to optimize BESS’s revenue sometimes leads to operation which is counter intuitive to conventional battery sizing approaches.

25 ENERGY STORAGE↗

Urban-Scale Control of School Bus Fleet Charging and Discharging Strategies Using Single and Multi-Stage Optimization

This paper presents a dual-strategy approach to optimizing charging and discharging schedules for school bus fleets, using the limited charging infrastructure effectively. We aim to ensure that each bus is fully charged for daily operations and aids in grid stability during peak demand. The first strategy utilizes linear programming to schedule overnight charging at available station sockets and strategic discharging during peak periods, efficiently coordinating limited resources. The second strategy employs metaheuristic techniques for continuous optimization, focusing on precise power requirements and offering greater flexibility than the linear model.

Selim, Alaa↗

TH-AB-209-02: Gadolinium Measurements in Human Bone Using in Vivo K X-Ray Fluorescence (KXRF) Technique

Purpose: Improvement in an in vivo K x-ray fluorescence system, based on 109Cd source, for the detection of gadolinium (Gd) in bone has been investigated. Series of improvements to the method is described. Gd is of interest because of the extensive use of Gd-based contrast agents in MR imaging and the potential toxicity of Gd exposure. Methods: A set of seven bone equivalent phantoms with different amount of Gd concentrations (from 0–100 ppm) has been developed. Soft tissue equivalent plastic plates were used to simulate the soft tissue overlaying the tibia bone in an in vivo measurement. A new 5 GBq 109Cd source was used to improve the source activity in comparison to the previous study (0.17 GBq). An improved spectral fitting program was utilized for data analysis. Results: The previous published minimum detection limit (MDL) for Gd doped phantom measurements using KXRF system was 3.3 ppm. In this study the MDL for bare bone phantoms was found to be 0.8 ppm. Our previous study used only three layers of plastic (0.32, 0.64 and 0.96 mm) as soft tissue equivalent materials and obtained the MDL of 4–4.8 ppm. In this study the plastic plates with more realistic thicknesses to simulate the soft tissue covering tibia bone (nine thicknesses ranging from 0.61–6.13 mm) were used. The MDLs for phantoms were determined to be 1.8–3.5 ppm. Conclusion: With the improvements made to the technology (stronger source, improved data analysis algorithm, realistic soft tissue thicknesses), the MDL of the KXRF system to measure Gd in bare bone was improved by a factor of 4.1. The MDL is at the level of the bone Gd concentration reported in literature. Hence, the system is ready to be tested on human subjects to investigate the use of bone Gd as a biomarker for Gd toxicity.

60 APPLIED LIFE SCIENCES↗

Simulation of the NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} and Na{sub 2}Gd{sub 4}(MoO{sub 4}){sub 7}–Na{sub 2}Eu{sub 4}(MoO{sub 4}){sub 7} Solid Solutions by the Interatomic Potential Method

Simulation of the solid solutions in the system of double sodium–gadolinium and sodium–europium molybdates, which are promising matrices for solid state lasers and phosphors has been carried out by the method of interatomic potentials. Two types of solid solutions have been studied, one of which contains finite components corresponding to the stoichiometric NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} compositions with statistical distribution of cations in the crystal lattice. Another object is a cation-deficient Na{sub 2}Gd{sub 4}(MoO{sub 4}){sub 7}–Na{sub 2}Eu{sub 4}(MoO{sub 4}){sub 7} system, in which we have examined the variants of statistical distribution and partial ordering of cations over structural positions. Atomistic simulation has been performed using the GULP 4.0.1 software package (General Utility Lattice Program). It is shown that when we pass from sodium-gadolinium molybdate to sodium-europium molybdate, both of stoichiometric and cation-deficient compositions, an increase in the unit cell volume is observed, while the density of the crystal, the energy of interatomic interactions in the structure, the vibrational entropy and the heat capacity decrease along with increasing europium content. The energy of interatomic interactions in the structure for cation-deficient solid solutions is less than for stoichiometric ones. Other aforementioned characteristics for cation-deficient solid solutions have greater values than for stoichiometric ones. The role of cluster europium centers in concentration quenching in NaGd(MoO{sub 4}){sub 2}–NaEu(MoO{sub 4}){sub 2} solid solutions has been examined.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Energetic Substantiation of the Formation of Ytterbium Dimers in Single Forsterite Crystals

A structural computer simulation of ytterbium-containing forsterite crystals has been carried out. Atomistic simulation is performed using the GULP 4.1 software package (General Utility Lattice Program). Different mechanisms of ytterbium dissolution in forsterite crystals are considered, and the dissolution energies of isolated defects, as well as charged and neutral clusters of various configurations, are calculated. The results of the calculation manifest that the formation of ytterbium clusters with a magnesium vacancy gives a significant gain in the dissolution energy. The formation of neutral clusters (dimers) in the M1 site (Yb{sub Mg1}ν{sub Mg1}Yb{sub Mg1}) leads to an energy reduction by 1.7 eV compared with the statistical distribution of defects. As a result of simulation, it is shown the energetic substantiation of the formation of ytterbium dimers in forsterite crystals. A model of the most energetically favorable center in the M1 site is proposed—a dimer, consisting of a pair of trivalent ytterbium ions with a magnesium vacancy between them, forming a chain parallel to the crystallographic axis c.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

db, Version 0.x

A set of programs and utilities for generating and manipulating data files in TSV (tab-separated value) or JSON format.

Hash, Curtis↗

Equilipy: a python package for calculating phase equilibria

The CALPHAD (CALculation of PHAse Diagram) approach (Nigel Saunders & Miodownik, 1998) provides predictions for thermodynamically stable phases in multicomponent-multiphase materials across a wide range of temperatures. Consequently, the CALPHAD calculations became an essential tool in materials and process design (Luo, 2015). Such design tasks frequently require navigating a high-dimensional space due to multiple components involved in the system. This increasing complexity demands high-throughput CALPHAD calculations, especially in the rapidly evolving field of alloy design. In response to the need, we developed Equilipy an open-source Python package designed for calculating phase equilibria of multicomponent-multiphase systems. Equilipy is specifically tailored for high-throughput CALPHAD calculations, offering parallel computations across multiple processors and nodes with the given NPT input conditions namely elemental compositions (N), pressure (P), and temperature (T). Equilipy utilizes the program structure and Gibbs energy functions from the Fortran-based program, Thermochimica (Piro et al., 2013), with incorporating a new Gibbs energy minimization algorithm. This algorithm, originally developed by Capitani and Brown in 1987 (Capitani & Brown, 1987), has been revised and implemented to enhance the stability and performance of calculations. The Fortran codes are precompiled and interfaced with Python via F2PY, ensuring high computation speed. Benchmark tests shown in Figure 1 demonstrate that Equilipy’s computation speed is comparable to those of established commercial software, TC-Python and PanPython. This result highlights its efficiency and potential applications in various scientific and industrial fields.

97 MATHEMATICS AND COMPUTING↗

Light Water Reactor Sustainability Program: Digital Technology Business Case Methodology Guide

The Department of Energy’s (DOE’s) Light Water Reactor Sustainability Program aims to develop and deploy technologies that will make the existing U.S. nuclear fleet more efficient and competitive. The program has developed a standard methodology for determining the impact of new technologies in order to assist nuclear power plant (NPP) operators in building sound business cases. The Advanced Instrumentation, Information, and Control (II&C) Systems Technologies Pathway is part of the DOE’s Light Water Reactor Sustainability (LWRS) Program. It conducts targeted research and development (R&D) to address aging and reliability concerns with the legacy instrumentation and control and related information systems of the U.S. operating light water reactor (LWR) fleet. This work involves two major goals: (1) to ensure that legacy analog II&C systems are not life-limiting issues for the LWR fleet and (2) to implement digital II&C technology in a manner that enables broad innovation and business improvement in the NPP operating model. Resolving long-term operational concerns with the II&C systems contributes to the long-term sustainability of the LWR fleet, which is vital to the nation’s energy and environmental security. The II&C Pathway is conducting a series of pilot projects that enable the development and deployment of new II&C technologies in existing nuclear plants. Through the LWRS program, individual utilities and plants are able to participate in these projects or otherwise leverage the results of projects conducted at demonstration plants. Performance advantages of the new pilot project technologies are widely acknowledged, but it has proven difficult for utilities to derive business cases for justifying investment in these new capabilities. Lack of a business case is often cited by utilities as a barrier to pursuing wide-scale application of digital technologies to nuclear plant work activities. The decision to move forward with funding usually hinges on demonstrating actual cost reductions that can be credited to budgets and thereby truly reduce O&M or capital costs. Technology enhancements, while enhancing work methods and making work more efficient, often fail to eliminate workload such that it changes overall staffing and material cost requirements. It is critical to demonstrate cost reductions or impacts on non-cost performance objectives in order for the business case to justify investment by nuclear operators. The Business Case Methodology (BCM) addresses the “benefit” side of the analysis—as opposed to the cost side—and how the organization evaluates discretionary projects (net present value (NPV), accounting effects of taxes, discount rates, etc.). The cost and analysis side is not particularly difficult for the organization and can usually be determined with a fair amount of precision (not withstanding implementation project cost overruns). It is in determining the "benefits" side of the analysis that utilities have more difficulty in technology projects and that is the focus of this methodology.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SECARB Initial Injection Period Reservoir Modeling Report

The Southeast Carbon Sequestration Partnership Phase III Anthropogenic Test at Citronelle Field is the United States’ largest CO 2 capture and transportation, injection, storage and monitoring project using CO 2 derived from a coal-fired power station. The project represents a U.S. Department of Energy research and development initiative designed to demonstrate deep underground injection and containment of 100,000 tonnes or more of anthropogenic-source CO 2 . A series of reservoir modeling runs will be performed during the pre-injection, injection, and post-injection phases of the project and will be used to predict plume migration and areal extent. Pressure, temperature, and downhole measurements (seismic, fluid and logging), all data collected as a part of the monitoring program, are utilized as reservoir performance parameters to tune the existing geophysical and geochemical simulation models. The ability to represent site injection activities with the produced detailed simulation models lend credence to long-term forecasts of CO 2 fate and the progress of the CO 2 plume. This report provides an assessment of the simulation model results for CO 2 injection at the Citronelle Anthropogenic Test site from the period of August 20, 2012 to August 31, 2013.

01 COAL, LIGNITE, AND PEAT↗

SECARB Second Injection Period Reservoir Modeling Report

The Southeast Carbon Sequestration Partnership Phase III Anthropogenic Test at Citronelle Field is the United States’ largest CO 2 capture and transportation, injection, storage and monitoring project using CO 2 derived from a coal-fired power station. The project represents a U.S. Department of Energy research and development initiative designed to demonstrate deep underground injection and containment of 100,000 tonnes or more of anthropogenic-source CO 2 . A series of reservoir modeling runs will be performed during the pre-injection, injection, and post-injection phases of the project and will be used to predict plume migration and areal extent. Pressure, temperature, and downhole measurements (seismic, fluid and logging), all data collected as a part of the monitoring program, are utilized as reservoir performance parameters to tune the existing geophysical and geochemical simulation models.

01 COAL, LIGNITE, AND PEAT↗

Puerto Rico Demand Response Impact and Forecast Tool (PR-DRIFT) - Beta Version [Slides]

Due to high fossil fuel imports, high electricity rates, an unreliable electricity grid, and 100% renewable electricity goals, demand response can play a crucial role for the Puerto Rico electricity grid. The Puerto Rico Demand Response Impact and Forecast Tool (PR-DRIFT) is a spreadsheet-based tool in which users can estimate the potential impacts of demand response, energy efficiency, and VRE and storage adoption in Puerto Rico from 2021 through 2040. The tool includes projections for solar, wind, and battery adoption based on released RFPs and energy targets (including Act-17 2019) to generate a projected net load profile for each hour through 2040. Based on user inputs and default assumptions, the tool also projects load profile impacts of demand response and energy efficiency, and is specifically focused on highlighting projected demand response technical potential. This demand response technical potential can be used by local utilities, regulators, program administrators, or researchers to help design demand response programs for larger impact.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Facilitated Direct Liquid Fuel Cells with High Temperature Membrane Electrode Assemblies

Dimethyl ether (DME) is a liquid fuel of great potential impact due to its exceptionally high energy density. However, it has received minimal prior investigation as an alternative to either purified hydrogen or other liquid fuels, including methanol (MeOH). In the limited published literature work on direct dimethyl ether fuel cells, regardless of operating temperature, PtRu (either supported or unsupported on carbon) has been established as the standard catalyst of choice. The majority of the work in this program also utilized a Johnson Matthey (JM) HiSPEC ® 12100 PtRu/C (nominally 50% Pt, 25% Ru) while looking at electrode optimizations, beginning of life (BoL) performance, pressure- and temperature-dependent studies to look at the effect of binding affinity of DME oxidation intermediates, mass transport effects, crossover studies, and durability. However, it does also investigate some promising alternatives to PtRu/C as well, which should be investigated in more detail in further work. Those catalysts include a pair of ternary PtRuPd/C catalysts (from Los Alamos National Laboratory (LANL) and Pajarito Powder, LLC. (PP)) as well as a Pt 2 Bi Black catalyst from Professor Anastasios Angelopoulos of the University of Cincinnati (UC). This work achieved several project objectives, including an optimization of the membrane electrode assembly (MEA) process using PtRu/C anode catalyst. Additionally, these direct dimethyl ether fuel cells (DDFCs) were able to match or exceed many performance metrics for the state-of-the-art (SOA) direct methanol fuel cells (DMFCs), a primary and more evolved competitor to direct dimethyl ether fuel cells. This included peak specific power, total platinum group metal (PGM) loading, crossover current, degradation rate, start/stop cycling losses, and anode specific current.

09 BIOMASS FUELS↗