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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 OSTI2022

Advanced Integrated Reticular Sorbent-Coated System to Capture CO 2 from the Atmosphere (AIR2CO2)

GE Research Center (GRC) and the University of California, Berkeley (UCB) executed an 15-month, $1.0 MM program to develop a lab-scale material system to extract CO 2 from ambient air using UCB’s pioneering sorbent technology and GRC’s composite coating expertise. The primary objective of this project was to develop an “Advanced Integrated Reticular Sorbent-Coated System to Capture CO 2 from the Atmosphere (AIR2CO2)” at a Technology Readiness Level (TRL) of 3. The AIR2CO2 concept relies on two key innovations: 1) advanced sorbent architectures with high capacity and rapid sorption kinetics that enable effective CO 2 capture at low concentrations, and 2) tailored MOF-binder slurry formulations and coating processes that enable sorbent integration into a novel additively-manufactured contactor.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A fast reduced model for a shell-and-tube based latent heat thermal energy storage heat exchanger and its application for cost optimal design by nonlinear programming

Numerical simulation of latent heat thermal energy storage (LHTES) systems plays a fundamental role in studying the physical process and guiding the engineering design. Discretization of the PDEs describing the nonlinear solidification/melting process of phase change materials (PCMs) leads to a large-scale complex dynamics system, where the system behavior depends on a set of parameters. In a design setting, repeated model evaluations are required over the set of parameters results in significant computational burden. In this paper, an explicit analytic solution was built for the propagation of the solidification front in a cylindrical coordinate. The analytic solution approach is further employed to develop a low computational reduced model (RM) as a module for a shell-and-tube based LHTES heat exchanger. The levelized Cost of Energy (LCOE) is used as a design metric and the RM model is used to apply system-level constraints in the nonlinear programming formulation that facilitates efficient global optimal design of the PCM properties, flow conditions and tube geometries. The use of LCOE as the design metric prevents over design of the heat transfer rate and also establishes a fair ground for evaluation of different thermal storage technologies and their integrated applications with other systems. Optimal results showed that a higher effectiveness results in a higher LCOE; the velocity of the HTF and the length of the channel are highly correlated with each other; both larger PCM latent energy and conductivity result in lower LCOE.

25 ENERGY STORAGE↗
DOE OSTI2020

PINE: Photonic Integrated Networked Energy efficient datacenters

We review the motivation, goals, and achievements of the Photonic Integrated Networked Energy efficient datacenter (PINE) project, which is part of the Advanced Research Projects Agency–Energy (ARPA-E) ENergy-efficient Light-wave Integrated Technology Enabling Networks that Enhance Dataprocessing (ENLITENED) program. Here, the PINE program leverages the unique features of photonic technologies to enable alternative mega-datacenters and high-performance computing (HPC) system architectures that deliver more substantial energy efficiency improvements than can be achieved through link energy efficiency alone. In phase 1 of the program, the PINE system architecture demonstrated an average factor of 2.2× improvement in transactions/joule across a diverse set of HPC and datacenter applications. In phase 2, PINE will demonstrate an aggressive 1.0 pJ/bit total link budget with high-bandwidth-density dense wavelength-division multiplexing (DWDM) links to enable additional 2.5× or more efficiency gains through deep resource disaggregation.

42 ENGINEERING↗
DOE OSTI2019

SimCCS: An open-source tool for optimizing CO 2 capture, transport, and storage infrastructure

Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO 2 distribution pipelines are selected in a robust and cost-effective manner. Presented in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS 2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS 2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO 2 source, sink, and transportation data, SimCCS 2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is further solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS 2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS 2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.

42 ENGINEERING↗
DOE OSTI2025

DistOPF: Advanced Solutions for Distribution Optimal Power Flow Analysis - DistOPF v0.2 Documentation

To achieve an affordable and reliable energy system, research on power distribution system is often focused on integration of distributed generators, energy storage solution, EV charging, smart meters, and other advanced assets that may benefit from or require more advanced control and optimization techniques. Despite this focus on advanced distribution system topics, early researchers and grid scientists often start from scratch when developing optimization programs for power distribution systems. This report introduces DistOPF, a Python package that consolidates years of research into a versatile and modular tool. DistOPF provides researchers with essential capabilities to solve distribution system Optimal Power Flow (OPF) problems using standard network models. Additionally, it offers a platform to benchmark both new and existing algorithms against established test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Enhancing Monte Carlo Workflows for Nuclear Reactor Analysis with Metamodel-Driven Modeling

Monte Carlo codes are essential components of many reactor physics simulation workflows as high-fidelity continuous-energy neutron transport solvers. Among Monte Carlo radiation transport codes, MCNP is particularly notable due to its diverse simulation capabilities, large user base, and long validation history. Despite being a powerful simulation tool, MCNP provides limited capabilities to allow automated execution, model transformation, or support for user-defined logic and abstractions that limit its compatibility with modern workflows. Here, to better integrate MCNP into a modern scientific workflow, we have developed an intuitive yet full-featured MCNP Application Program Interface (API) in Python, named MCNPy, which provides a specialized set of classes for MCNP input development. Moreover, to guarantee that our reading, writing, and modeling capabilities remain self-consistent (and to render the huge scope of the MCNP API manageable), we have adopted a strategy of model-driven software development in which a generalized model of the MCNP input format has been created. From this generalized model, or “metamodel,” problem-specific implementations such as an engine for input validation or a codebase for programmatic operations may be automatically generated. Since MCNPy primarily acts as a Python front-end to the underlying Java API that directly interfaces with the metamodel, it is intrinsically linked to the metamodel and thus remains maintainable. With MCNPy, users can programmatically read, write, and modify any syntactically valid MCNP input file regardless of its origin. These capabilities allow users to automate complicated tasks like design optimization and model translation for nuclear systems. As examples, this work demonstrates the use of MCNPy to find the critical radius of a plutonium sphere and to translate a 9000+ line MCNP input file into a corresponding OpenMC model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Photovoltaic Manufacturing Consortium (PVMC) – Enabling America’s Solar Revolution

The U.S. Photovoltaic Manufacturing Consortium (US-PVMC) is an industry-led consortium which was created with the mission to accelerate the research, development, manufacturing, field testing, commercialization, and deployment of next-generation solar photovoltaic technologies. Formed as part of the U.S. Department of Energy's (DOE) SunShot initiative, and headquartered in New York State, PVMC is managed by the State University of New York Polytechnic Institute (SUNY Poly) at the Colleges of Nanoscale Science and Engineering. PVMC is a hybrid of industry-led consortium and manufacturing development facility, with capabilities for collaborative and proprietary industry engagement. Through its technology development programs, advanced manufacturing development facilities, system demonstrations, and reliability and testing capabilities, PVMC has demonstrated itself to be a recognized proving ground for innovative solar technologies and system designs. PVMC comprises multiple locations, with the core manufacturing and deployment support activities conducted at the Solar Energy Development Center (SEDC), and the core Si wafering and metrology technologies being headed out of the University of Central Florida. The SEDC provides a pilot line for proof-of-concept prototyping, offering critical opportunities to demonstrate emerging concepts in PV manufacturing, such as evaluations of innovative materials, system components, and PV system designs. The facility, located in Halfmoon NY, encompasses 40,000 square feet of dedicated PV development space. The infrastructure and capabilities housed at PVMC includes PV system level testing at the Prototype Demonstration Facility (PDF), manufacturing scale cell & module fabrication at the Manufacturing Development Facility (MDF), cell and module testing, reliability equipment on its PV pilot line, all integrated with a PV performance database and analytical characterizations for PVMC and its partners test and commercial arrays. Additional development and deployment support are also housed at the SEDC, such as cost modeling and cost model based development activities for PV and thin film modules, components, and system level designs for reduced LCOE through lower installation hardware costs, labor reductions, soft costs and reduced operations and maintenance costs. The progression of the consortium activities started with infrastructure and capabilities build out focused on CIGS thin film photovoltaics, with a particular focus on flexible cell and module production. As marketplace changes and partners objectives shifted, the consortium shifted heavily towards deployment and market pull activities including Balance of System, cost modeling, and installation cost reduction efforts along with impacts to performance and DER operational costs. The consortium consisted of a wide array of PV supply chain companies from equipment and component suppliers through national developers and installers with a particular focus on commercial scale deployments (typically 25 to 2MW installations). With DOE funding ending after the fifth budget period, the advantages and disadvantages of such a consortium is detailed along with potential avenues for self-sustainability is reviewed.

14 SOLAR ENERGY↗
DOE OSTI2025

Synopsis of NREL's Automated Mobility District (AMD) Research Program and Associated Publications

An automated mobility district (AMD) envisions a system of integrated mobility options that serves major activity centers such as campuses, central business districts, and large medical facilities. The National Renewable Energy Laboratory (NREL) has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings. This document provides a synopsis of findings revealed over the last three phases of work, which have yielded insights into the creation and management of AMDs anticipated to use automated vehicle (AV) technology over the next decade. Phase I and Phase II tracked the deployment and lessons learned from 10 early-stage demonstrations of automated shuttle deployments, and their associated insights into the challenges for automated driving systems to achieve safe operations within district-scale deployments. Phase III began in-depth investigations of critical subsystem components, as automation, electrification, and on-demand service continue to converge within initial AMD operations. These directed studies focus on elements of electrification, curbfront/station management, the role of infrastructure sensing, and overall integration of AMD safety management in central, simultaneous coordination of multiple AMD fleets. Future research in AMDs includes systems engineering methodology (more frequently referred to as "digital twins") for planning, design, testing, and ongoing operation of AMDs; location (or co-location) of management functions; and human supervision and passenger communications for safety and security in unattended vehicles. The synopsis references the foundational research products (papers and presentations) that have been published through conference proceedings, journal articles, and NREL reports.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Cyber-Informed Engineering

A continuing challenge for engineers who utilize digital systems is to understand the impact of cyber-attacks across the entire product and program lifecycle. This is a challenge due to the evolving nature of cyber threats that may impact the design, development, deployment, and operational phases of all systems. Cyber Informed Engineering is the process by which engineers are made aware of both how to use their engineering knowledge to positively impact the cyber security in the processes by which they architect and design components and the services and security of the components themselves.

42 ENGINEERING↗
DOE OSTI2018

INSPIRE Phase I Development

Sandia National Laboratories (Sandia) and Makel Engineering, Inc developed a pathway towards an advanced multi-modal sensor system suitable for in-situ analysis of exhaled volatile organic compounds (VOCs) for pilots, divers and field patients. Our proposed In-Mask Sensors for Physiological Investigation of Respiratory Exhalation - INSPIRE, will combine micro-gas chromatograph (microGC) and miniature ion mobility spectrometer (IMS) for detection of trace amounts of exhaled breath VOCs with miniature solid state sensors for inorganic compounds found in breath such as oxygen, carbon dioxide, moisture and the inert gases nitrogen, argon and helium. To develop clear developmental pathway towards that goal Sandia demonstrated a new version of its ion-mobility spectrometer detection technology for VOC detection, while Makel demonstrated detection of inorganics and concepts for mask integration. Sandia demonstrated detection of many compounds from the EPA TO-15 Test Mixture, which is representative of many classes of compounds found in air, and can be purchased as a gas standard from a variety of suppliers. The work demonstrated for phase I was sufficient to move the team into phase II of the program, where a full prototype unit will be developed. This CRADA provided clear value to the taxpayer by allowing a US small business to continue to phase II of a competitive STTR proposal for the Air Force. This process will help to transition Sandia’s technology into the marketplace to address a clear DoD requirement.

Moorman, Matthew↗
DOE OSTI2017

2017 DOE Vehicle Technologies Office Annual Merit Review

The 2017 U.S. Department of Energy (DOE) Hydrogen and Fuel Cells Program and Vehicle Technologies Office (VTO) Annual Merit Review and Peer Evaluation Meeting (AMR) was held June 5-9, 2017, in Washington, DC. The review encompassed work done by the Hydrogen and Fuel Cells Program and VTO: 263 individual activities were reviewed for VTO by 191 reviewers. Exactly 1,241 individual review responses were received for the VTO technical reviews. The objective of the meeting was to review the accomplishments and plans for VTO over the previous 12 months, and provide an opportunity for industry, government, and academia to give inputs to DOE with a structured and formal methodology. The meeting also provided attendees with a forum for interaction and technology information transfer.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Acoustic Travel-Time Tomography for Wind Energy

New remote sensing technologies for direct observation of the atmospheric flow in the proximity of operating wind turbines are necessary for the advancement of wind turbine design, wind plant control, and the validation of high-fidelity numerical models; fundamental goals of the DOE Wind Energy Technology Office's (WETO's) A2e program. Modern remote sensing technologies for commercial and research applications rely on the backscatter of light or sound waves, which limits spatial and temporal resolution and cannot produce reliable flow estimates near solid bodies or reflective surfaces. Acoustic tomography (AT) is an innovative sensing technology based on fundamental thermodynamic properties of the atmosphere and an inverse algorithm that can reconstruct both velocity and temperature fields within a network of acoustic transducers. AT relies on the direct travel path of acoustic signals between speakers and microphones in the network and can achieve much higher resolutions than conventional backscatter technologies. For wind energy R&D applications, AT represents an extremely economical option over other remote sensing technologies, integrating mature and commonly available acoustic and signal processing hardware. This report is intended as an update on the development of the AT array on the NREL Flatirons Campus (FC) and includes a brief review of the instrumentation, the calibration of equipment, signal processing, and resulting flow field estimates. Designs for future AT systems and applications are detailed in this report, including summaries of new capabilities, engineering and theoretical challenges, and anticipated costs help to outline future directions for AT technology R\&D. The potential for application of AT to utility-scale turbines is also discussed. Investing in the development of the proposed instrument will establish AT as a transformational RS technique that represents a significant advance in measurement instrumentation, enabling new fundamental insights into the structure of the atmospheric boundary layer and supporting applications for wind energy, pollution transport, and resource characterization. AT is also an extremely economical option over other RS instruments, integrating mature and commonly available acoustic and signal processing hardware.

17 WIND ENERGY↗
DOE OSTI2016

Grizzly: A Multi-scale and Multi-Physics Tool to Model Aging of Nuclear Power Plant Components

Grizzly is a multi-scale multi-physics tool being developed at Idaho National Laboratory (INL) as part of the US Department of Energy's Light Water Reactor Sustainability program to provide improved safety assessments of systems, components, and structures in nuclear power plants subjected to age-related degradation. Its goal is to provide an improved scientific basis for decisions surrounding license renewal, which would permit operation of commercial nuclear power plants beyond 60 years. Grizzly is based on INL's MOOSE framework, which enables multi-physics simulations in a massively parallel computing environment. The reactor pressure vessel (RPV) has been chosen as the initial application for Grizzly. The primary concern for the RPV is that it becomes increasingly susceptible to fracture initiation at the sites of pre-existing flaws over time. This is because exposure to irradiation and high temperatures embrittles the steel. Assessing the safety of an RPV under transient conditions involves simulations at multiple scales. At the engineering scale, strongly coupled equations of heat conduction and solid mechanics are solved to simulate the global response of the RPV to accident conditions. Sub-models are used to represent regions with pre-existing flaws and the stress intensity factors are evaluated from the domain integrals. Crack propagation is then determined using a model that provides the temperature and neutron fluence dependent fracture toughness of the RPV steel. The ability of Grizzly to provide accurate engineering scale estimates of RPV safety beyond 60 years of operation strongly relies on the predictability of the embrittlement model. Multiple models for embrittlement have been proposed, and the physically based empirical model is implemented in Grizzly. However, the formation of late blooming phases greatly reduces the confidence on the extrapolated values obtained from embrittlement model, which is further exacerbated by the absence of real field data for validation. Experimentally validated lower length scale models can significantly improve the predictability of the embrittlement model beyond the calibrated range and the development of such models is another ongoing effort in Grizzly. The modeling activity in Grizzly spans across different length scales, and can be divided into: (i) Irradiation induced microstructure evolution at the atomistic and single crystal length scale using molecular dynamics, atomistic kinetic Monte-Carlo, phase-field and rate theory; (ii) Effect of the irradiation induced defects on the flow stress and fracture processes at the polycrystalline scale using crystal plasticity. Subsequently, the prediction from these models can be used to obtain irradiation induced ductile-to-brittle transition temperature (DBTT) shifts from specimen-scale simulations; (iii) Global thermo-mechanical response of the RPV under normal and accident scenarios, and probabilistic risk analyses at the engineering scale using the DBTT shifts obtained from the lower length scale models. The item (i) has been discussed in a previous report. In this extended abstract an overview of items (ii) and (iii) is provided. The extended abstract summarizes the current status of the modeling effort under Grizzly. At the engineering scale, reduced order model development is underway using the statistical tool RAVEN. This will allow probabilistic analysis considering a wide range of flaw topologies in a computationally efficient manner. Coupling the irradiation induced defect growth predictions to crystal plasticity is also in progress. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2010

Introduction to the Buildings Sector Module of SEDS

SEDS is a stochastic engineering-economics model that forecasts economy-wide energy consumption in the U.S. to 2050. It is the product of multi-laboratory collaboration among the National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), Argonne National Laboratory (ANL), Lawrence Berkeley National Laboratory (LBNL), and Lumina Decision Systems. Among national energy models, SEDS is unique, as it is the only model written to explicitly incorporate uncertainty in its inputs and outputs. The primary purpose of SEDS is to estimate the impact of various US Department of Energy (DOE)R&D and policy programs on the performance and subsequent adoption rates of technologies relating to every energy consuming sector of the economy (shown below). It has previously been used to assist DOE in complying with the Government Performance and Results Act of 1993 (GPRA). The focus of LBNL research has been exclusively on develop the buildings model (SBEAM), which is capable of running as a stand-alone forecasting model, or as a part of SEDS as a whole. The full version of SEDS, containing all sectors and interaction is also called the 'integrated' version and is managed by NREL. Forecasts from SEDS are often compared to those coming from National Energy Modeling System (NEMS). The intention of this document is to present new users and developers with a general description of the purpose, functionality and structure of the buildings module within the Stochastic Energy Deployment System (SEDS). The Buildings module, which is capable of running as a standalone model, is also called the Stochastic Buildings Energy and Adoption Model (SBEAM). This document will focus exclusively on SBEAM and its interaction with other major sector modules present within SEDS. The methodologies and major assumptions employed in SBEAM will also be discussed. The organization of this report will parallel the organization of the model itself, being divided into major submodules. As the description progresses, the nature of modules will change from broad, easily understood concepts to lower-level data manipulation. Because SBEAM contains dozens of submodules and hundreds of variables, it would not be relevant or useful to describe each and every one. Rather, the investigation will focus more generally on the operations performed throughout the model. This manual is by no means a complete description of SBEAM; however it should provide the foundation for an introductory understanding of the model. The manual assumes a basic level of understating of Analytica{reg_sign}, the platform on which SEDS and SBEAM have been developed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Framework Application for Core Edge Transport Simulations (FACETS) Performance Analysis (Final Report)

The goal of the FACETS project (Framework Application for Core-Edge Transport Simulations) was to provide a multiphysics, parallel framework application (FACETS) that will enable whole-device modeling for the U.S. fusion program, to provide the modeling infrastructure needed for ITER, the next step fusion confinement device. Through use of modern computational methods, including component technology and object oriented design, FACETS is able to switch from one model to another for a given aspect of the physics in a flexible manner. This enables use of simplified models for rapid turnaround or high-fidelity models that can take advantage of the largest supercomputer hardware. FACETS does so in a heterogeneous parallel context, where different parts of the application execute in parallel by utilizing task farming, domain decomposition, and/or pipelining as needed and applicable. ParaTools, Inc. was tasked with supporting the performance analysis and tuning of the FACETS components and framework in order to achieve the parallel scaling goals of the project. The TAU Performance System® was used for instrumentation, measurement, archiving, and profile / tracing analysis. ParaTools, Inc. also assisted in FACETS performance engineering efforts. Through the use of the TAU Performance System, ParaTools provided instrumentation, measurement, analysis and archival support for the FACETS project. Performance optimization of key components has yielded significant performance speedups. TAU was integrated into the FACETS build for both the full coupled application and the UEDGE component. The performance database provided archival storage of the performance regression testing data generated by the project, and helped to track improvements in the software development.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

SISGR: Chemomechanics of Far-From-Equilibrium Interfaces (COFFEI)

Portable, reliable, and deployable devices for energy storage and conversion require fundamental changes in design of solid-state composites comprising ceramics and metals. These materials comprise the electrodes and electrolytes of next-generation solid-oxide fuel cells and all solid-state batteries, forming solid-state functional composites. The advent of solid-state batteries – which replace liquid electrolytes with solid electrolytes capable of lithium ion transport for reliable energy storage in portable batteries – and the increased demand space for all solid-state fuel cells capable of oxygen reduction at intermediate temperatures remain important challenges for improved material stability and decreased system cost. However, little is understood about three fundamental facets of materials that enable such solid-state energy applications. First, how do such materials deform, fracture, or delaminate under operando conditions? Second, how does such mechanical deformation limit or facilitate electronic and ionic transport within and across such material interfaces? Third, how we can predictably design interface-rich composites to engineer both structural and electrochemical stability? This COFFEI Group comprised expertise from Materials Science & Engineering and Nuclear Science & Engineering to integrate unique in situ experiments, simulations, and fabricated interfaces that address these fundamental questions in solid-state interfaces of nanoscale composites that will guide solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric materials that enable such applications. In particular, we built on COFFEI’s understanding of chemomechanical coupling among defect concentrations, ionic transport, electron transport, and stored elastic energy that is particularly acute in the far-from-equilibrium conditions typical of energy device applications. By tailoring our focus to solid-state interfaces, we addressed these important issues by (a) developing and applying advanced in situ and ex situ characterization tools to characterize model materials and interfaces synthesized with molecular-level control, under both laboratory-controlled and extreme environments representative of energy device operation; and (b) employing computational modeling and simulation frameworks to predict transport mechanisms, reactivity and stability of these model materials and interfaces under significant chemical strains typical of energy device operation. Recent progress provided insights to additional materials systems and electrochemomechanical fatigue and fracture that were not fully envisioned when the program was initiated. Specifically, in the final three years of COFFEI we pursued two integrated thrusts, with complementary focus. Thrust I focused on failure-resistant electrochemomechanical composites, while Thrust II focused on strain-modulated conductivity and reactivity across interfaces. In contrast to our initial COFFEI focus, these thrusts concentrated wholly on solid-state material interfacial interactions and included greater integration of multiscale visualization including in situ electron microscopy of strained structures/interactions and mesoscale simulations. Successful development of functionally superior and long-lived battery and fuel cell systems and stress adaptable oxides requires a deeper, fundamental understanding of the coupling among the historically important subfields of solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric metal oxide electrodes. In this program, the understanding and the application of chemomechanical coupling of defect concentrations, ionic transport, electro-catalytic activity and stored elastic energy, particularly acute in the far-from-equilibrium conditions typical of energy device applications, are being refined and implications for device operation clarified, including for miniaturized solid-state batteries and fuel cells.

36 MATERIALS SCIENCE↗
DOE OSTI2019

LGFCS Prototype System Testing (Final Report)

In the project, LGFCS assembled and tested its modular SOFC Power System that incorporates all critical technology improvements identified for its “product-like” demonstration. This product demonstrator is expected to meet customer and LGFCS performance expectations for operation, availability, durability and serviceability. The principal technology improvements are aimed at increasing the fuel cell power output and reducing the stack degradation rate. Improvements were also made for added system robustness and increased reliability. The objective of this program is to test a 250kWe thermally self-sustaining modular solid oxide fuel cell (SOFC) Power System for a minimum of 5,000 hours while advancing this commercial prototype product demonstrator to a Technical Readiness Level (TRL) 7. The SOFC system was tested on a site provided by Stark State College in North Canton, Ohio. System performance and degradation as well as cost estimates were compared to established SOFC Program performance metrics to assess progress. The major achievements were to assemble, and QA qualify 70 fuel cell strips for 12 integrated blocks into a fuel cell vessel and install it into a generator module with the fuel and power electronics modules on the test site. Performance to date included over 1800 hours on load at 250 KWAC to the grid with a DC efficiency of 61% and AC efficiency of 55%. Power degradation was less than 0.4% per 1000 hours and NOx emissions met standards. The LGFCS SOFC Prototype System (GEN0) was demonstrated in an operational environment and therefore achieving Technical Readiness Level 7. The work presented here represents the efforts of all the employees of LG Fuel Cell Systems. Their dedication and hard work made GEN0 possible and successful.

03 NATURAL GAS↗
DOE OSTI2023

Adaptive Cyber-Physical Resilience for Building Control Systems

The main goal of the project is to develop an AI-based process layer cybersecurity suite for detection, isolation and mitigation of cyber-attack effects on operation of building energy management systems (BEMS). The following constituent key technologies were developed under the program towards fulfilling the program objectives: (1) developed a high fidelity BEMS testbed for generation of training data and validation of developed technologies; (2) developed a physics informed ML based attack detection and localization module (ADL) capable of detecting high impact stealthy attacks (HISA - attacks causing 30% energy utilization but no immediate visible impact otherwise) with 98% accuracy; (3) developed a methodology to determine ’representative days’ to limit the data required for training; (4) developed a virtual sensing system that can reconstruct affected sensors with 10% error for the same HISA set; (5) developed a resilient model predictive control system that can continue operation of the BEMS without jeopardizing stability for the HISA set; and (6) integrated and deployed all the constituent modules and demonstrated the efficacy of the technology in real-time in a hardware in loop simulation.

42 ENGINEERING↗