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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Human N -acetylglucosaminyltransferase II substrate recognition uses a modular architecture that includes a convergent exosite

Asn-linked oligosaccharides are extensively modified during transit through the secretory pathway, first by trimming of the nascent glycan chains and subsequently by initiating and extending multiple oligosaccharide branches from the trimannosyl glycan core. Trimming and branching pathway steps are highly ordered and hierarchal based on the precise substrate specificities of the individual biosynthetic enzymes. A key committed step in the synthesis of complex-type glycans is catalyzed by N-acetylglucosaminyltransferase II (MGAT2), an enzyme that generates the second GlcNAcβ1,2- branch from the trimannosyl glycan core using UDP-GlcNAc as the sugar donor. We determined the structure of human MGAT2 as a Mn 2+ -UDP donor analog complex and as a GlcNAcMan 3 GlcNAc 2 -Asn acceptor complex to reveal the structural basis for substrate recognition and catalysis. The enzyme exhibits a GT-A Rossmann-like fold that employs conserved divalent cation-dependent substrate interactions with the UDP-GlcNAc donor. MGAT2 interactions with the extended glycan acceptor are distinct from other related glycosyltransferases. These interactions are composed of a catalytic subsite that binds the Man-α1,6- monosaccharide acceptor and a distal exosite pocket that binds the GlcNAc-β1,2Man-α1,3Manβ- substrate “recognition arm.” Recognition arm interactions are similar to the enzyme–substrate interactions for Golgi α-mannosidase II, a glycoside hydrolase that acts just before MGAT2 in the Asn-linked glycan biosynthetic pathway. Here, these data suggest that substrate binding by MGAT2 employs both conserved and convergent catalytic subsite modules to provide substrate selectivity and catalysis. More broadly, the MGAT2 active-site architecture demonstrates how glycosyltransferases create complementary modular templates for regiospecific extension of glycan structures in mammalian cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Numerical Simulation of Isothermal Flow Across Slant Five-Tube Bundle with Spectral Element Method Code Nek5000

The helical coil steam generator (HCSG) is a specific type of shell-and-tube heat exchanger known for having a higher heat transfer coefficient than many other designs. For this reason, they are considered in small modular reactor and high temperature reactor designs. Investigation of flow behavior in HCSGs is important for better design. In this paper we present our study for modeling the coolant flow in the primary side of the HCSG. We used Nek5000, an open source, high-order spectral element computational fluid dynamics code developed in Argonne National Laboratory. Nek5000 accepts only hexahedral mesh, which makes the meshing process for the complicated HCSG geometry very challenging. A tetrahedral-to-hexahedral meshing strategy was applied to bypass the geometric complexities. In this study large eddy simulation (LES) was performed at the Reynolds number of 9000 based on the inlet velocity and the tube diameter. The employed subgrid-scale model for LES relies on explicit filtering. First- and second-order statistics were compared to available experimental data. We report overall velocity and turbulent kinetic energy showed good agreement with particle image velocimetry data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

SHAD: the Scalable High-performance Algorithms and Data-structures Library

The unprecedented amount of data that needs to be processed in emerging data analytics applications poses novel challenges to industry and academia. Scalability and high performance become more than a desirable feature because, due to the scale and the nature of the problems, they draw the line between what is achievable and what is unfeasible. In this paper, we propose SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD adopts a modular design that confines low level details and promotes reuse. SHAD's core is built on an Abstract Runtime Interface which enhances portability and identifies the minimal set of features of the underlying system required by the framework. The core library includes common data-structures such as: Array, Vector, Map and Set. These are designed to accommodate significant amount of data which can be accessed in massively parallel environments, and used as building blocks for SHAD extensions, i.e. higher level software libraries. We have validated and evaluated our design with a performance and scalability study of the core components of the library. We have validated the design flexibility by proposing a Graph Library as an example of SHAD extension, which implements two different graph data-structures; we evaluate their performance with a set of graph applications. Experimental results show that the approach is promising in terms of both performance and scalability. On a distributed system with 320 cores, SHAD Arrays are able to sustain a throughput of 65 billion operations per second, while SHAD Maps sustain 1 billion of operations per second. Algorithms implemented using the Graph Library exhibit performance and scalability comparable to a custom solution, but with smaller development effort.

Castellana, Vito G.↗
DOE OSTI2024

Securing Small Modular Reactors in Urban Environments

Current small modular reactor (SMR) deployment use cases consider both rural and urban deployments, depending on the operational in-country needs for clean and reliable sources of energy. Many studies have been conducted analyzing security in rural and remote deployment locations, but this study looks at the physical security implications of an SMR placed in an urban environment and its uses for electricity production, district heating, and process heating. SMRs used for electricity production, district heating, and process heating may be key sources of both energy infrastructure and commercial infrastructure within a city and a State. As a result, long-term shutdowns could have a serious impact on a State’s overall energy or commercial production. Therefore, operators may consider further security applications to protect an SMR plant from physical attacks against both radiological sabotage and sabotage acts that could result in the SMR facility being offline for a significant amount of time. In this study, the team designed and analyzed a physical protection system (PPS) for securing an urban SMR facility against acts of radiological sabotage and sabotage acts that could disrupt the facility’s long-term operation. Additionally, this work analyzed the nuanced security issues related to siting an SMR near an urban environment (versus in a rural environment). The result of these analyses includes recommendations for PPSs for urban SMR facilities used for energy production, district heating, and process heating.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

SynthNotes: A Generator Framework for High-volume, High-fidelity Synthetic Mental Health Notes

One of the key, emerging challenges that connects the "Big Data" and the AI domain is the availability of sufficient volumes of training data for AI/Machine Learning tasks. SynthNotes is a framework for generating standards-compliant, realistic mental health progress report notes at the very large, population-level scale, and in a strict privacy-preserving manner. Our framework, inspired by the needs to explore, evaluate, and train computational methods for the emerging mental health crisis in the US, is useful for benchmarking, optimization, and training of biomedical natural language processing, information extraction, and machine learning systems intended to operate at "Big Data" scale (billions of notes). The free text notes generated by SynthNotes are based on the literature and public statistical models allowing for realistic, natural language representation of a patient, and his or her mental health characteristics. Additionally, SynthNotes can partially simulate stylistic, grammatical, and expressive characteristics of a licensed mental health professional. SynthNotes is modular and flexible, allowing for representation of variety of conditions, incorporation of alternative foundational models, and parametrization of the variability of the structure, content, and size of the synthetically generated corpus. In this paper, we report on the initial use and performance characteristics of our SynthNotes framework and on the ongoing work for inclusion of content planning and deep learning-based generative methods trained on real data.

Begoli, Edmon↗
DOE OSTI2025

A Fortran–Python interface for integrating machine learning parameterization into earth system models

Abstract. Parameterizations in earth system models (ESMs) are subject to biases and uncertainties arising from subjective empirical assumptions and incomplete understanding of the underlying physical processes. Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. Specifically, ML-based parameterizations have been developed to represent convection, radiation, and microphysics processes in ESMs by learning from observations or high-resolution simulations, which have the potential to improve the accuracies and alleviate the uncertainties. Previous works have developed some surrogate models for these processes using ML. These surrogate models need to be coupled with the dynamical core of ESMs to investigate the effectiveness and their performance in a coupled system. In this study, we present a novel Fortran–Python interface designed to seamlessly integrate ML parameterizations into ESMs. This interface showcases high versatility by supporting popular ML frameworks like PyTorch, TensorFlow, and scikit-learn. We demonstrate the interface's modularity and reusability through two cases: an ML trigger function for convection parameterization and an ML wildfire model. We conduct a comprehensive evaluation of memory usage and computational overhead resulting from the integration of Python codes into the Fortran ESMs. By leveraging this flexible interface, ML parameterizations can be effectively developed, tested, and integrated into ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

NewLife Nuclear - An Environmentally and Economically Minded Solution for Fusion Energy Waste Handling

Energy demand is rising as a result of innovative and increasingly more energy intensive processes coming to fruition, particularly through the recent interest in the development of AI data centers as well as manufacturing with the push towards increasing domestic manufacturing interest. Fusion energy can provide virtually limitless energy to support this increase in energy demand. Fusion energy concepts, largely classified as magnetic fusion energy (MFE) and inertial fusion energy (IFE) are being pursued, each having unique challenges to overcome before the successful deployment of electricity to the grid. Achieving fusion ignition on the National Ignition Facility, first in December 2022, and eight times since, has demonstrated the scientific viability of the IFE approach. Meanwhile, MFE test stands continue to improve confinement times, making meaningful strides in progressing towards experimental scientific viability. In each of these approaches, an emphasis is placed on generating more power out of the system than what is required to power the system. An under-researched area applicable to both IFE and MFE is handling activated waste coming out of fusion energy systems, both in the course of normal daily operations, as well as in intermittent periods as structural materials may need to be replaced. In the context of an IFE plant system, commonly discussed plant designs suggest targets are ignited within a chamber at a rate of up to one million targets per day. Between each shot, the chamber housing the ignition event will clear a portion of the chamber – resulting in a mixture of vaporized target gas, target debris, and other materials being expelled from the chamber [source]. Additionally, IFE system concepts typically discuss the modularization of plant designs, which are expected to be replaced periodically as the components degrade over time. This would result in the irradiated chamber structure materials, likely metals and alloys, needing to be removed and safely stored. In MFE plant systems, while targets are not ignited at a repetition rate with the frequent chamber clearing as is expected in IFE plant systems, it is anticipated that portions of the confinement area interfacing with the hot plasma will need to be replaced periodically. In each system, without additional investment and research into alternative processing and recycling methods, the result is storing irradiated materials, and other elements in a safe containment area until they are no longer activated. – resulting in significant waste both economic and environmental.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Structured interactions drive abrupt transitions in the spatial organization of microbial communities

Bacteria possess diverse mechanisms to regulate their motility in response to environmental and physiological signals, enabling them to navigate complex habitats and adapt their behavior. Some of these mechanisms are species specific and enable cells to modulate their movement based on the ecological identity of neighboring species. Here, we introduce a model in which bacteria interact via local signals that either enhance or suppress the motility of neighboring cells depending on species type. Through large-scale simulations and a coarse-grained stochastic model, we demonstrate the emergence of a sharp transition driven by nucleation processes: increasing the density of motility-suppressing interactions drives the system from a fully mixed, motile phase to a state characterized by large, stationary bacterial clusters. Remarkably, in systems with a large number of interacting species, this transition can be triggered solely by altering the structure of the motility-regulation interaction matrix while maintaining species and interaction densities constant. In particular, we find that heterogeneous and modular interactions promote the transition more readily than homogeneous random ones. These findings add a dimension to the theory of motility-induced phase separation and contribute to the ongoing effort to understand microbial interactions, suggesting that structured, nonrandom ones may be key to reproducing commonly observed spatial patterns in microbial communities.

bacterial communities↗
DOE OSTI2025

Preliminary System Interface Failure Mode Analysis for Two Advanced Reactors

This study explores two distinct Balance of Plant (BOP) configurations: the Rankine cycle for a sodium-cooled fast reactor (SFR) and the Brayton cycle for a gas-cooled reactor (GCR). As representative designs, the Power Reactor Innovative Small Module (PRISM) by GE Hitachi Nuclear Energy was selected for the SFR, while the Gas Turbine Modular Helium Reactor (GT MHR) by General Atomics was chosen for the gas-cooled reactor. Both configurations were adapted to deliver high-quality heat for industrial applications. A Failure Modes and Effects Analysis (FMEA) was conducted for each system to identify critical failure modes affecting key components. This study marks the first phase of a two-step design optimization approach, integrating FMEA into the design process. Based on the analysis, design modifications and mitigation strategies were proposed to enhance system resilience. The second phase, to be detailed in a subsequent report, will focus on the role of the control system in mitigating these failures. The FMEA serves as a foundation for defining the control topology, ensuring system resilience against component failures that could compromise essential functions, such as electricity and heat production.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A Fortran-Python Interface for Integrating Machine Learning Parameterization into Earth System Models

Parameterizations in Earth System Models (ESMs) are subject to biases and uncertainties arising from subjective empirical assumptions and incomplete understanding of the underlying physical processes. Recently, the growing representational capability of machine learning (ML) in solving complex problems has spawned immense interests in climate science applications. Specifically, ML-based parameterizations have been developed to represent convection, radiation and microphysics processes in ESMs by learning from observations or high-resolution simulations, which have the potential to improve the accuracies and alleviate the uncertainties. Previous works have developed some surrogate models for these processes using ML. These surrogate models need to be coupled with the dynamical core of ESMs to investigate the effectiveness and their performance in a coupled system. In this study, we present a novel Fortran-Python interface designed to seamlessly integrate ML parameterizations into ESMs. This interface showcases high versatility by supporting popular ML frameworks like PyTorch, TensorFlow, and Scikit-learn. We demonstrate the interface's modularity and reusability through two cases: a ML trigger function for convection parameterization and a ML wildfire model. We conduct a comprehensive evaluation of memory usage and computational overhead resulting from the integration of Python codes into the Fortran ESMs. By leveraging this flexible interface, ML parameterizations can be effectively developed, tested, and integrated into ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Techno-economic analysis of advanced small modular nuclear reactors

Here, small modular nuclear reactors (SMRs) represent a robust opportunity to develop low-carbon and reliable power with the potential to meet cost parity with conventional power systems. This study presents a detailed, bottom-up economic evaluation of a 12 × 77 MW e (924 MW e total) light-water SMR (LW-SMR) plant, a 4 × 262 MW e (1,048 MW e ) gas-cooled SMR (GC-SMR) plant, and a 5 × 200 MW e (1,000 MW e total) molten salt SMR (MS-SMR) plant. Cost estimates are derived from equipment costs, labor hours, material inputs, and process-engineering models. The advanced SMRs are compared to natural gas combined cycle plants with and without post-combustion carbon capture and a conventional large nuclear reactor. Overnight capital cost (OCC) and levelized cost of energy (LCOE) estimates are developed. The OCC of the LW-SMR, GC-SMR, and MS-SMR are found to be $\$4,844$/kW, $\$4,355$/kW, and $\$3,985$/kW respectively. The LCOE of the LW-SMR, GC-SMR, and MS-SMR are found to be $\$89.6$/MWh, $\$81.5$/MWh, and $\$80.6$/MWh respectively. A Monte Carlo analysis is performed, for which the OCC and construction time of the LW-SMR is found to have a lower mean and standard deviation than a conventional large reactor. The LW-SMR OCC is found to have a mean of $\$5,233$/kW with a standard deviation of $\$658$/kW and a 90 % probability of remaining between $\$4,254$/kW and $\$6,399$/kW, while the construction duration is found to have a mean of 4.5 years with a standard deviation of 0.8 years and a 90 % probability of remaining between 3.4 and 6.0 years. The economic impact of economies of scale, simplification, modularization, and construction time for SMRs are discussed. Additionally, policy implications for direct SMR capital subsidies and the impact of a carbon tax on natural gas emissions are explored.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Modular Controllable Transformers (MCT)

Large Power Transformers (LPTs) are at the heart of the electricity infrastructure and are critical pieces in today’s grid. Aging assets, long turn-around times, transportation delays and dependence on foreign manufacturing for these components have created conditions for points of failure across the system. Moreover, there is no available dynamic control on these passive sections of the grid. For all the automation embedded on the low voltage side of the low voltage side of the system there is absolutely no flexibility on the high voltage side. Changes in power flow patterns are brought about by altering dispatch patterns for generators which requires a coordinated effort and is often time consuming. Traditional FACTS based approaches such as UPFC or HVDC light involve massive modifications to the existing infrastructure. Recent instances of physical attacks on LPTs and the slow recovery process associated with fixing or replacing these damaged units has created an increased awareness for this issue. LPT designs are highly customized owing to specific field requirements. Long lead times coupled with transportation delays make procuring and installing LPTs a lengthy process. In an attempt to minimize the recovery time following an LPT failure, transformer manufacturers have developed mobile transformer units. These units typically consist of either a single-phase or three-phase transformer mounted on a truck and characterized by compact form factors. By reducing the assembly time and transport time these units offer a fast and temporary solution to LPT failures. Several efforts led by DOE, Edison Electric Company (EEI) and North American Electric Reliability Corporation (NERC) have led to the RecX program. RecX transformers consist of single phase transformers transported on specialized assemblies to enable fast restoration and minimal installation time. NERC and EEI have instituted transformer sharing programs like Spare Equipment Database (SED) as well as Spare Transformer Equipment Database (STEP) which encourage utilities to maintain and share a fleet of LPTs. Mobile transformers are typically limited to less than 100 MVA to enable transportation on a trailer. Also, the efficiency of mobile transformer units and RecX transformers is lower since they are temporary solutions. The ideal replacement solution would be one that could utilize a set of standardized transformers while incorporating flexibility to influence metrics like power flow, apparent impedance and voltage profiles. In view of these issues the team at Georgia Tech proposed a concept called Modular Controllable Transformers (MCTs). This project was commissioned as a part of DOE’s Transformer Resiliency and Advance Component (TRAC) program. The approach consists of splitting one large unit rated upwards of 100 MVA with smaller modular, standardized units. Each of these smaller units are augmented with a converter to add power flow, voltage and impedance control. Splitting the power level into multiple units has two important implications. By making smaller units, the transportation times can be reduced drastically. Moreover, even though these units have very specific impedance and other parameters, the augmented converters can make it emulate the unit being replaced. Thus, faster replacement times and added controls are achieved making this an extremely resilient approach. In the event of one modular units failure, the other two controllable units can operate in the most resilient fashion keeping the net system overloads to a minimum. Moreover, for the same probability of failure only a fraction of the system capacity is lost. The converter is augmented on to the tertiary winding of the transformer making it retrofittable in the field without massive modifications to the system. The material proposed in this report highlights design considerations to minimize recovery time as well as results displaying overall improvement in resiliency. The cost analysis of this approach shows significant savings compared to UPFC and HVDC lite based approaches. Extensive analysis was conducted on numerous aspects of this project over the course of this project. Simulation studies were conducted to prove the 5MVA converter design. Challenging BIL constraints and transient issues were addressed over the course of this project. Simulations on EMTP platform presented in consequent sections were used to finely tune the control for the same. A final design for a back-to-back 5MVA neutral-point-clamped (NPC) converter was completed in this project. Furthermore, switching components like high power IGBTs from IXYS Westcode Press-Pack series and ABB Stackpack series were identified for this application. These devices exhibit a blocking voltage of 6.5 kV and a nominal collector current of 900 A. Potential housing options as well as existing commercial option were identified for this converter design. A 56 MVA modular transformer unit was designed with Delta Star Inc. with consultation and inputs from all project members. The transformer cooling systems were chosen to be Oil Natural Air Forced (ONAF) to optimize ease of transport. A full Product Requirement Document (PRD) for the converter and the transformer was generated. The team also investigated key aspects of resiliency and how to quantify the same. A metric was developed to analyze resiliency and numerous simulation cases were presented. Increased (N-1) resiliency and outage resistance was showcased through simulation on the Texas Large scale power system. Dynamic control capabilities were also showcased on numerous system level simulations. An IEEE 30 bus system was used to show the ability of the MCT approach to reduce line congestion. Power flow control; a part of the MCTs abilities, showcased a 29% reduction in transformer loading on the same system. Full control over tie line flows was demonstrated on a modified IEEE 13 bus system. Dynamic LTC capabilities were shown through simulation and were compared to traditional LTCs. Furthermore, the ability of the MCTs to alter apparent transformer impedance was simulated to promote standardization of modular transformer units while retaining the ability to emulate a varied range of impedance characteristics. Thus granular control over power flow, voltages, impedances and was presented. Regulatory analysis conducted by Oak Ridge National Laboratory (ORNL) further bolstered the efficacy of the MCT approach and verified the added resiliency achieved due to this approach. As a conclusion, it was proved that the resilience improvement obtained from using the MCT approach is justified by just one failure in a 30-year period. This means that the benefits obtained from using the MCT approach far outweigh the cost of setting this approach up. As a part of the future efforts, the team is proposing building a (12.47-24) kV/400 kVA scaled down unit to control 5MVA of power flows. Emphasis would be laid on using commercial components to speed up the build of these units. Further the actual transport of the modular transformer unit would be a part of this operation and would provide insight into transportation issues. The approach shows much promise and adds key dynamic control on passive sub transmission and transmission sectors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Exploring Hydrologic Model Process Connectivity at the Continental Scale Through an Information Theory Approach

Exploring water fluxes between hydrological model (HM) components is essential to assess and improve model realism. Many classical metrics for HM diagnosis rely solely on streamflow and hence provide limited insights into model performance across processes. This study applies an information theory measure known as “transfer entropy” (TE) to systematically quantify the transfer of information among major HM components. To test and demonstrate the benefits of TE, we use the Framework for Understanding Structural Errors (FUSE) model to mimic and compare four commonly used HM structures, VIC, PRMS, SACRAMENTO, and TOPMODEL, across 671 catchments spanning a variety of hydrologic regimes in the conterminous United States. We explore connections between HM components and catchment landscape characteristics (e.g., climate, topography, soil, and vegetation) and characterize their nonlinear associations using distance correlation and Spearman correlation coefficients. Our results indicate that while the information transferred from precipitation to runoff is similar across model structures (likely as a result of calibration), the information transferred among other components can vary significantly from a FUSE structure to another. We find that aridity, precipitation duration and frequency, snow fraction, mean elevation, forest area, and leaf area index are often significantly associated with TE between the main HM components. Here, we propose that the presence of meaningful nonlinear associations can be used to diagnose process representation in HMs. Our results highlight the necessity to enhance the conventional streamflow-only calibration approach for a more realistic representation of water dynamics in the models.

large-sample hydrology↗
DOE OSTI2018

The LAMP instrument at the Linac Coherent Light Source free-electron laser

The Laser Applications in Materials Processing (LAMP) instrument is a new end-station for soft X-ray imaging, high-field physics, and ultrafast X-ray science experiments that is available to users at the Linac Coherent Light Source (LCLS) free-electron laser. While the instrument resides in the Atomic, Molecular and Optical science hutch, its components can be used at any LCLS beamline. The end-station has a modular design that provides high flexibility in order to meet user-defined experimental requirements and specifications. The ultra-high-vacuum environment supports different sample delivery systems, including pulsed and continuous atomic, molecular, and cluster jets; liquid and aerosols jets; and effusive metal vapor beams. It also houses movable, large-format, high-speed pnCCD X-ray detectors for detecting scattered and fluorescent photons. Multiple charged-particle spectrometer options are compatible with the LAMP chamber, including a double-sided spectrometer for simultaneous and even coincident measurements of electrons, ions, and photons produced by the interaction of the high-intensity X-ray beam with the various samples. Here in this paper we describe the design and capabilities of the spectrometers along with some general aspects of the LAMP chamber and show some results from the initial instrument commissioning.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Atomic-scale oxygen-vacancy engineering in Sub-2 nm thin Al 2 O 3 /MgO memristors

Ultrathin (sub-2 nm) Al 2 O 3 /MgO memristors were recently developed using an in vacuo atomic layer deposition (ALD) process that minimizes unintended defects and prevents undesirable leakage current. These memristors provide a unique platform that allows oxygen vacancies (V O ) to be inserted into the memristor with atomic precision and study how this affects the formation and rupture of conductive filaments (CFs) during memristive switching. Herein, we present a systematic study on three sets of ultrathin Al 2 O 3 /MgO memristors with V O -doping via modular MgO atomic layer insertion into an otherwise pristine insulating Al 2 O 3 atomic layer stack (ALS) using an in vacuo ALD. At a fixed memristor thickness of 17 Al 2 O 3 /MgO atomic layers (~1.9 nm), the properties of the memristors were found to be affected by the number and stacking pattern of the MgO atomic layers in the Al 2 O 3 /MgO ALS. Importantly, the trend of reduced low-state resistance and the increasing appearance of multi-step switches with an increasing number of MgO atomic layers suggests a direct correlation between the dimension and dynamic evolution of the conducting filaments and the V O concentration and distribution. Understanding such a correlation is critical to an atomic-scale control of the switching behavior of ultrathin memristors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Industry Facing PV Degradation Prediction Tool and Database to Enable a 50-Year Life Module

The Photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 years. Furthermore, research efforts aim for up to 50 years of service life while keeping performance degradation at a minimum for decades of outdoor weathering - putting additional pressure on improving the accuracy of long-term durability and reliability assessments. Here there is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. A graphical user interface will aid in the understanding of the results. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. We use an integration pipeline approach that allows us to leverage weather data from the National Solar Radiation Database to perform geospatial degradation analysis in the US and worldwide. Our repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors. We hope to become a repository that can be used for weathering and degradation analysis for various applications beyond the PV industry.

degradation↗
DOE OSTI2022

Zero Energy Ready Out of the Box

In this conference paper for the ASHRAE Buildings XV conference, December 2022, PNNL staff share key metrics for companies who are combining off site construction with certification to the U.S. Department of Energy’s Zero Energy Ready Home program to create homes that are both cost effective to construct and high performance to live in. Key performance metrics and measures for modular, panelized, and SIP homes are compared against all homes in the DOE Zero Energy Ready Home program and against new homes built to code. These metrics show that off-site construction homes got similar or better energy performance to site-built homes, and in the case of modular and panelized, at considerably lower average cost than site-built homes. The paper also highlights the experiences of two DOE Zero Energy Ready Home builders who employ offsite construction methods. One builder constructs production homes using pre-assembled panels. The other builder designs and ships kit homes all over the United States. The paper will focus on the optimum value engineering aspects of the panelized construction processes used by each builder to identify management and production practices employed by the builders to operate profitably while meeting high energy performance goals, despite a year marked by skyrocketing materials costs and supply chain and labor shortages. Cost and labor savings methods will be discussed in the context of these two unique business models.

U.S. Department of Energy Building Technologies Pr↗
DOE OSTI2022

Coupled Heat Power Operation of Smart Buildings via Modular Pumped Hydro Storage

In the United States, building sector is responsible for around 40% of total energy consumption and contributes about 40% of carbon emissions since 2012. Within the past several years, various optimization models and control strategies have been studied to improve buildings’ energy efficiency and reduce operational expenses under the constraints of satisfying occupants’ comfort requirements. However, the majority of these studies consider building electricity demand and thermal load being satisfied by unidirectional electricity flow from the power grid or on-site renewable energy generation to electrical and thermal home appliances. Opportunities for leveraging low-grade heat for electricity have largely been overlooked due to impracticality at small scale. In 2016, a modular pumped hydro storage technology was invented in Oak Ridge National Laboratory, named Ground Level Integrated Diverse Energy Storage (GLIDES). In GLIDES, employing high-efficiency hydraulic machinery instead of gas compressor/turbine, liquid is pumped to compress gas inside high-pressure vessel creating head on ground level. This unique design eliminates the geographical limitation associated with the existing state-of-the-art energy storage technologies. It is easy to be scaled for building level, community level, and grid level applications. By using this novel hydro-pneumatic storage technology, opportunities for leveraging low-grade heat in building can be economical. In this research, the potential of utilizing low-grade thermal energy to augment electricity generation of GLIDES is investigated. Since GLIDES relies on gas expansion in the discharge process and the gas temperature drops during this non-isothermal process, available thermal energy, e.g., from thermal storage, combined cooling, heat and power system (CCHP), can be utilized by GLIDES to counter the cooling effect of the expansion process and elevate the gas temperature and pressure and boost the roundtrip efficiency. Here, several groups of comparison experiments have been conducted, and the experimental results show that a maximum 12.9% cost saving could be achieved with unlimited heat source for GLIDES, and a moderate 3.8% cost improvement can be expected when operated coordinately with CCHP and thermal energy storage in a smart building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗