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All sources NASA NTRS DOE OSTI

DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Materials Characterization: A Primer for Solid Phase Processing Applications

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development (LDRD) Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). As a two-year LDRD investment requiring focused research, the MCPC project applied only a subset of the wide range of available destructive and nondestructive characterization methods to provide data to the predictive modeling and data analytics tasks. The purpose of this report is to review a wide range of destructive and nondestructive characterization methods that are relevant in solid-phase processing (SPP) applications, but not necessarily applied in the MCPC Project as a guide to the planning of characterization activities in future research. Particular attention is given to measured characteristics that can correlate to other material characteristics, with a particular interest in nondestructive evaluation (NDE) that can be applied to samples obtained in the MCPC Project. Destructive examinations include tensile tests, optical and electron microscopy, micro-hardness, and residual stress tests. NDE tests include surface visual inspection, eddy current examination for cracks, 4-point potential drop, ultrasound, x-ray, and computed tomography.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Development of a Reference Governor-based Control Scheme for Integrated Energy Systems

The concept of an Integrated Energy System (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. In practice what is achievable is limited by not only the inherent physical response characteristics of individual plant units but also by equipment operating limits. The inherent response characteristics are presently accounted for in the RAVEN-based HYBRID framework by dynamic models for plant units. The equipment operating limits, which are not yet addressed in HYBRID, are the subject of this report. These limits are set to achieve a design service life for a plant unit and are based on material degradation in the presence of mechanical fatigue induced by thermal cycling and by structure creep resulting from elevated temperature conditions. In general, the plant unit designer determines and specifies the allowable operating range of key process variables. It is then up to the integrated system design engineer to ensure those conditions are met. This can be accomplished through a combination of limiting the demand rates made on the plant unit and designing a control system that limits variations of key process variables. The typical control system design procedure, however, is not well suited for achieving this for complex dynamic systems such as encountered in integrated energy systems where multiple plant units must be simultaneously coordinated. This report describes how equipment operating limitations in an IES can be formally met through a control system design procedure know as the Reference Governor. The approach augments the existing controllers in a plant unit with an advance controller that modifies the issued setpoints so that selected process variables remain within limits. The design procedure is applied to the reference multi-unit system that has been the focus of Modeling and Simulation task in the Integrated Energy System program. Results describing application to the problem of limiting key process variables during operational transients for two of the plant units, the balance of plant and the gas turbine, are then presented. It is demonstrated that the Reference Governor method is an effective means for ensuring equipment operating constraints can be met in an IES. The software that implements the method has been made accessible to others on the Modeling and Simulation upload site.

42 ENGINEERING↗

DOE OSTI2025

Lightweight Metal Stamping Optimization Enabled by Artificial Intelligence

Successfully manufacturing an automotive body structure made via the sheet metal stamping process depends upon simultaneous consideration of component design, tooling design, stamping process control, and material properties. In many cases, introducing lightweight sheet materials (e.g., aluminum alloys, magnesium alloys, advanced high strength steels) holds the potential to significantly reduce vehicle weight, but challenges the stamping process by introducing materials with inherently less ductility. Successful and repeatable applications require co-developing the stamping process controls with the varying material properties, including formability. During the stamping process, as soon as the forming limit of the sheet is exceeded, the material shows localized necking which quickly leads to splits. Controlling process variability to avoid these material splits will enable deployment of less formable, lighter, and stronger materials for stamped automotive components. A typical optimization procedure for manufacturing requires an iterative process involving parameter setting, execution of computational simulations, and modifying the parameters. The entire process demands substantial computational time, making it impractical for real-time feedback towards rapid corrective actions required for in-line control for running production processes. To overcome this challenge, artificial intelligence (AI) can be leveraged to determine optimal manufacturing parameters within a single manufacturing cycle time. This research proposes an in-line optimization framework incorporating a trained AI model to predict kidney-shaped die forming. Preliminary results indicate that the AI framework can accurately predict draw-in values based on a given parameter set, a process referred to as forward prediction. Furthermore, the AI framework can also predict the optimal parameter set that leads to the desired draw-in values, referred to as inverse optimization (or backward prediction). This research has been performed in collaborations with USCAR (US Council for Automotive Research) and AutoForm. The members of USCAR are Ford, GM, and Stellantis.

36 MATERIALS SCIENCE↗

DOE OSTI2017

UV-enhanced CO sensing using Ga 2 O 3 -based nanorod arrays at elevated temperature

Monitoring and control of gaseous combustion process are critically important in advanced energy systems such as power plants, gas turbines, and automotive engines. However, very limited gas sensing solutions are available in the market for such application due to the inherent high temperature of combustion gaseous atmosphere. In this study, we fabricated and demonstrated high-performance metal oxide based nanorod array sensors assisted with ultra-violet (UV) illumination for in situ and real-time high-temperature gas detection. Without UV-illumination, it was found surface decoration of either 5 nm LSFO or 1 nm Pt nanoparticles can enhance the sensitivity over CO at 500 °C by an order of magnitude. Under the 254 nm UV illumination, CO gas-sensing performance of Ga 2 O 3 -based nanorod array sensors was further enhanced with the sensitivity boosted by 125 %, and the response time reduced by 30 % for La 0.8 Sr 0.2 FeO 3 (LSFO)-decorated sample. The UV-enhanced detecting of CO might be due to the increased population of photo-induced electron-hole pairs. While for LSFO-decorated nanorod array sensor under UV illumination, the enhancement is through a combination of sensitizing effect and photocurrent effect.

36 MATERIALS SCIENCE↗

DOE OSTI2016

BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models

BioSig3D is a computational platform for high-content screening of three-dimensional (3D) cell culture models that are imaged in full 3D volume. It provides an end-to-end solution for designing high content screening assays, based on colony organization that is derived from segmentation of nuclei in each colony. BioSig3D also enables visualization of raw and processed 3D volumetric data for quality control, and integrates advanced bioinformatics analysis. The system consists of multiple computational and annotation modules that are coupled together with a strong use of controlled vocabularies to reduce ambiguities between different users. It is a web-based system that allows users to: design an experiment by defining experimental variables, upload a large set of volumetric images into the system, analyze and visualize the dataset, and either display computed indices as a heatmap, or phenotypic subtypes for heterogeneity analysis, or download computed indices for statistical analysis or integrative biology. BioSig3D has been used to profile baseline colony formations with two experiments: (i) morphogenesis of a panel of human mammary epithelial cell lines (HMEC), and (ii) heterogeneity in colony formation using an immortalized non-transformed cell line. These experiments reveal intrinsic growth properties of well-characterized cell lines that are routinely used for biological studies. BioSig3D is being released with seed datasets and video-based documentation.

Science & Technology - Other Topics↗

DOE OSTI2023

A New Class of SiC Power MOSFETs with Record-Low Resistance

Silicon carbide (SiC) power transistors are used in the main traction inverter of electric vehicles (EVs). Tesla began installing SiC power MOSFETs in 2017, and has now produced 4.8 million EVs containing over 169 million SiC power MOSFETs. Looking ahead, the worldwide EV market is projected to exceed 50 million vehicles per year by 2030 (Reuters, Oct. 25, 2022). This will create a demand for over two billion SiC power MOSFETs per year. Our program aims to double the efficiency of today's commercial power MOSFETs. This will cut the number of MOSFETs per EV in half, reducing cost, simplifying assembly, decreasing weight, and increasing vehicle reliability through reduced parts count. Our approach is to apply innovative design and advanced processing to increase the density of current-controlling channels in SiC power MOSFET. We have developed two new MOSFET devices, each of which increases the channel density by a factor of six over today's best commercial MOSFETs. This required implementing new fabrication processes, creating new device designs, and integrating the processing steps and device designs into a manufacturable technology. In this project we have developed two innovative devices: (i) a novel three-dimensional structure, the "tri-gate MOSFET," and (ii) a deeply-scaled, fully self-aligned trench MOSFET, the "IMOSFET". Both products were experimentally demonstrated during this project and meet the program goals of increased efficiency relative to the current state-of-the art commercial products. In the process we have generated significant IP, with two US patents issued and three applications pending. We have also published three journal articles and given reports on this technology at seven international conferences. The success of this program has led to significant follow-on funding from industry. In May 2023 Purdue University signed a five-year R&D contract with GlobalFoundries to transfer our novel technology to commercial production. With headquarters in Malta, NY, Global Foundries is one of the largest pure-play silicon foundries in the world, with annual revenue of $\$$8.1B. Their SiC foundry will be built around the next-generation 200-mm diameter SiC wafers, which will double the number of die per wafer and reduce per-die production cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1967

Third annual NASA University Conference on Manual Control

This volume contains the proceedings of the Third Annual NASA-University Conference on Manual Control held from March 1 to 3, 1967, at the University of Southern California, Los Angeles, California. The program was divided into the following sessions: display, describing function models , decision processes I, computer processing of manual control records, controlled elements, decision processes 11, physiological modeling, decision processes 111, advanced modeling techniques , and applications. Both formal and informal presentations were made; all of the formal and many of the informal papers are included in this volume.

Source record↗

NASA NTRS1987

Computer Sciences and Data Systems, volume 2

Topics addressed include: data storage; information network architecture; VHSIC technology; fiber optics; laser applications; distributed processing; spaceborne optical disk controller; massively parallel processors; and advanced digital SAR processors.

Source record↗

NASA NTRS1991

Use of piloted simulation for high-angle-of-attack agility research and design criteria development

This paper reviews the use of piloted simulation at Langley Research Center as part of the NASA High-Angle-of-Attack Technology Program (HAATP) program to provide methods and concepts for the design of advanced fighter aircraft. A major focus of this program is to develop the design process required to fully exploit the benefits from advanced control concept for high-angle-of-attack agility. Important methodologies associated with the effective us of piloted simulation of the research are described, particularly those relating to the test techniques, validation of the test results, and design guidelines/criteria development.

Angle of attack↗

NASA NTRS2000

Health Monitoring System Technology Assessments: Cost Benefits Analysis

The subject of sensor-based structural health monitoring is very diverse and encompasses a wide range of activities including initiatives and innovations involving the development of advanced sensor, signal processing, data analysis, and actuation and control technologies. In addition, it embraces the consideration of the availability of low-cost, high-quality contributing technologies, computational utilities, and hardware and software resources that enable the operational realization of robust health monitoring technologies. This report presents a detailed analysis of the cost benefit and other logistics and operational considerations associated with the implementation and utilization of sensor-based technologies for use in aerospace structure health monitoring. The scope of this volume is to assess the economic impact, from an end-user perspective, implementation health monitoring technologies on three structures. It specifically focuses on evaluating the impact on maintaining and supporting these structures with and without health monitoring capability.

Kent, Renee M.↗

NASA NTRS1991

Use of Piloted Simulation for High-Angle-of-Attack Agility Research and Design Criteria Development

The use of piloted simulation at Langley Research Center as part of the NASA High-Angle-of-Attack Technology Program (HATP) to provide methods and concepts for the design of advanced fighter aircraft is discussed. A major focus is to develop the design process required to fully exploit the benefits from advanced control concepts for high-angle-of attack agility.

Ogburn, Marilyn E.↗

NASA NTRS2018

Optimization of Picosecond Laser Parameters for Surface Treatment of Composites Using a Design of Experiments (DOE) Approach

Based on guidelines from the Federal Aviation Administration, research supported by the NASA Advanced Composites Project is investigating methods to improve process control for surface preparation and pre-bond surface characterization on aerospace composite structures. The overall goal is to identify high fidelity, rapid, and reproducible surface treatments and surface characterization methods to reduce the uncertainty associated with the bonding process. The desired outcome is a more reliable bonded airframe structure, and to reduce time to achieve certification. In this work, a design of experiments (DoE) approach was conducted to determine optimum laser ablation conditions using a pulsed laser source with a nominal pulse width of 10 picoseconds. The laser power, frequency, scan speed, and number of passes (1 or 2) were varied within the laser system operating boundaries. Aerospace structural carbon fiber reinforced composites (Torayca® 3900-2/T800H) were laser treated, then characterized for contamination, and finally bonded for mechanical testing. Pre-bond characterization included water contact angle (WCA) using a handheld device, ablation depth measurement using scanning electron microscopy (SEM), and silicone contamination measurement using laser induced breakdown spectroscopy (LIBS). In order to accommodate the large number of specimens in the DoE, a rapid-screening, double cantilever beam (DCB) test specimen configuration was devised based on modifications to ASTM D5528. Specimens were tested to assess the failure modes observed under the various laser surface treatment parameters. The models obtained from this DoE indicated that results were most sensitive to variation in the average laser power. Excellent bond performance was observed with nearly 100% cohesive failure for a wide range of laser parameters. Below about 200 mW, adhesive failure was observed because contamination was left on the surface. For laser powers greater than about 600 mW, large amounts of fiber were exposed, and the failure mode was predominately fiber tear.

Palmieri, Frank L.↗

NASA NTRS2017

Sharing Telemetry across Organizations and Systems

The XTCE (XML Telemetric and Command Exchange) standard provides a way to describe space mission telemetry and command “databases” (or dictionaries) to be exchanged across centers and space agencies. Having a standard format for describing the telemetry and command formats allows for the development or adoption of compatible tools and significantly reduces the amount of custom software development often needed to ensure all system components have access to consistent format definitions. The main objective of this paper is to show how powerful XTCE is in terms of interoperability across organizations. This paper summarizes work which entailed converting the mission telemetry database for a current NASA mission, in XTCE format, into several target mission operation databases associated with different telemetry and command toolchains, and then, comparing the results of the telemetry processing and display. The target toolchains selected were Ball Aerospace/COSMOS, NASA-GSFC/ITOS (Goddard Space Flight Center/Integrated Test and Operations System), and NASA-AMMOS/AMPCS (Advanced Multi-Mission Operations System/Mission Data Processing and Control System) – all real-time telemetry and command processing systems.

Jones, Ron↗

NASA NTRS2020

Geostar – a ‘Shovel Ready’ Geostationary Microwave Sounder

A geostationary microwave sounder, capable of providing temperature, water vapor, clouds, precipitation, and wind in the presence of clouds, convection and precipitation, will add tremendously to our ability to observe dynamic atmospheric phenomena, such as hurricanes and severe storms, monsoonal moisture flow, atmospheric rivers, etc. Such a sensor is now feasible, enabled by technology that has been developed under NASA’s Instrument Incubator Program at the Jet Propulsion Laboratory. The Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR) is essentially an “AMSU in GEO”, i.e. it has similar capabilities as AMSU would have if it were operating on a geostationary satellite, but with similar spatial resolution. GEO orbits are almost 50 times higher than the LEO orbits that current AMSUs operate from, and the corresponding scaling of aperture size required to maintain spatial resolution has stymied the development of such a sensor for many decades. The aperture synthesis approach implemented with GeoSTAR finally overcomes that obstacle, and the large number of microwave receivers and associated electronics required is made possible with new technology that has now been developed. A low-cost mission operating as a hosted payload on a commercial communications satellite has been designed and is “shovel-ready”. The objectives of such a mission could be to advance our understanding and modeling of storm processes that control rapid or explosive intensification of hurricanes, mesoscale convective systems, and extratropical cyclones, or it could be to support operational weather forecasting and nowcasting. Retrieval of temperature and water vapor profiles is possible even in the presence of moderate precipitation, and with the ability to derive horizontal wind vectors by tracking water vapor features, a rich set of parameters measuring the thermodynamics, dynamics and convection and sampled every 15 minutes, will enable significant progress in storm science and forecasting.

Lambrigtsen, Bjorn H↗

DOE OSTI2024

Hydrogen Detection Strategies to Support H2@SCALE - The NREL Sensor Laboratory

Hydrogen represents a major pathway to decarbonize and stabilize the national and international energy industry and select manufacturing markets. To facilitate the development of hydrogen markets, the US Department of Energy initiated H2@Scale to bring together stakeholders to advance affordable hydrogen production, transport, storage, and utilization to increase revenue opportunities in multiple energy sectors. One major impediment to hydrogen implementation is cost. To expedite the use of hydrogen in energy and other markets, the United States announced in 2021 the Hydrogen Shot, which seeks to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). As the cost of hydrogen drops, new applications will emerge that will require unique configurations of existing equipment and infrastructure, and eventually lead to advances in the generation and utilization of hydrogen. As the hydrogen economy expands, sensors and detection methods will need to adapt to changing infrastructure demands to address the primary targets of health & safety, emissions monitoring, and process control. The NREL Sensor Laboratory is playing a pivotal role in advancing the use of hydrogen sensors and detection methodologies in each of these categories to support DOE's mission for safe and efficient utilization in emerging markets. Health & safety monitors are required to ensure that operators and facilities can react to unintended hydrogen releases, either as GH2, LH2, or as a constituent of blends (e.g., natural gas or ammonia). Current detection methodologies focus on safety applications to detect near its lower flammable limit (4 vol %), and typically include point sensors in applications such as fixed or mobile detectors (e.g., personal gas monitors). Methodologies amenable for area detection include acoustic, emerging optical imaging methods, and flame detectors. Comparable detection strategies can be utilized for emissions monitoring and quantization, however few methods can simultaneously cover both low (emissions) and high (health & safety) levels. Deployment of emission level detectors will be required to 1) reduce product loss through small but potentially significant leaks from an environmental or cost perspective, 2) reduce downtime of high demand systems by early identification of eminent system failures (leaks through pump or compressor seals indicative of impending failure), and 3) address potential emission monitoring requirements that may be set by regulating bodies. The first two points should be adopted by industry to reduce the cost-of-goods-sold. The third main category for hydrogen detection relates to process control and may be advantageous for many existing applications. Two main applications are emerging. For example, the purity requirements for hydrogen that is dispensed from refueling systems for hydrogen fuel cell electric vehicles (FCEV) is rigorously regulated by the Standard SAE J2719, which prescribes maximum allowable levels of multiple impurities in the hydrogen fuel and must be verified by a regulatory body. Hydrogen contaminant detectors (HCD) integrated to the fueling station can assure this compliance. HCDs must be able operate in 100% H2 backgrounds and be able to distinguish between multiple contaminants at low ppm to low ppb levels. Secondly, as a strategy to decarbonize the natural gas grid, there are proposals to blend hydrogen with natural gas. This blending will affect transport applications (pipeline infrastructure), stationary combustion systems (turbines), and consumer and commercial appliances. In the short-term, hydrogen levels up to 20% are proposed. Variations in the hydrogen level can have dramatic impact on the combustion process and on the potential response of safety sensors. These mixtures may be regulated so that the concentration at a delivery point must be monitored with high precision. However, routine maintenance may introduce background gases such as ambient air (with water) or maintenance gases (introduced with welding processes or adhesive outgassing.) Therefore, the detection methodology must be robust enough to recover or respond to various contaminants. Several reviews can be found in literature addressing sensing and detection technologies, including their limitations and applications. However, for most applications, limitations can be alleviated by combining various detection techniques either through system integration or implementation of machine learning methods (artificial intelligence). In this presentation, we will discuss several applications, highlight their current approach for hydrogen detection, and suggest detection strategies to supplement their limitations.

ENERGY STORAGE,HYDROGEN↗

DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Bench-scale Development of an Advanced Solid Sorbent-based CO 2 Capture Process for Coal-fired Power Plants

It is increasingly clear that CO 2 capture and sequestration (CCS) must play a critical role in curbing worldwide CO 2 emissions to the atmosphere. Development of these technologies to cost-effectively remove CO 2 from coal-fired power plants is very important to mitigating the impact these power plants have within the world’s power generation portfolio. Currently, conventional CO 2 capture technologies, such as aqueous-monoethanolamine based solvent systems, are prohibitively expensive and if implemented could result in a 75 to 100% increase in the cost of electricity for consumers worldwide. Solid sorbent CO 2 capture processes – such as RTI’s Advanced Solid Sorbent CO 2 , Capture Process – are promising alternatives to conventional, liquid solvents. Supported amine sorbents – of the nature RTI has developed – are particularly attractive due to their high CO 2 loadings, low heat capacities, reduced corrosivity/volatility and the potential to reduce the regeneration energy needed to carry out CO 2 capture. Previous work in this area has failed to adequately address various technology challenges such as sorbent stability and regenerability, sorbent scale-up, improved physical strength and attrition-resistance, proper heat management and temperature control, proper solids handling and circulation control, as well as the proper coupling of process engineering advancements that are tailored for a promising sorbent technology. The remaining challenges for these sorbent processes have provided the framework for the project team’s research and development and target for advancing the technology beyond lab- and bench-scale testing. Under a cooperative agreement with the US Department of Energy, and part of NETL’s CO 2 Capture Program, RTI has led an effort to address and mitigate the challenges associated with solid sorbent CO 2 capture. The overall objective of this project was to mitigate the technical and economic risks associated with the scale-up of solid sorbent-based CO 2 capture processes, enabling subsequent larger pilot demonstrations and ultimately commercial deployment. An integrated development approach has been a key focus of this project in which process development, sorbent development, and economic analyses have informed each of the other development processes. Development efforts have focused on improving the performance stability of sorbent candidates, refining process engineering and design, and evaluating the viability of the technology through detailed economic analyses. Sorbent advancements have led to a next generation, commercially-viable CO 2 capture sorbent exhibiting performance stability in various gas environments and a physically strong fluidizable form. The team has reduced sorbent production costs and optimized the production process and scale-up of PEI-impregnated, fluidizable sorbents. Refinement of the process engineering and design, as well as the construction and operation of a bench-scale research unit has demonstrated promising CO 2 capture performance under simulated coal-fired flue gas conditions. Parametric testing has shown how CO 2 capture performance is impacted by changing process variables, such as Adsorber temperature, Regenerator temperature, superficial flue gas velocity, solids circulation rate, CO 2 partial pressure in the Regenerator, and many others. Long-term testing has generated data for the project team to set the process conditions needed to operate a solids-based system for optimal performance, with continuous 90% CO 2 capture, and no operational interruptions. Data collected from all phases of testing has been used to develop a detailed techno-economic assessment of RTI’s technology. These detailed analyses show that RTI’s technology has significant economic advantages over current amine scrubbing and potential to achieve the DOE’s Carbon Capture Program’s goal of >90% CO 2 capture rate at a cost of < $40/T-CO 2 captured by 2025. Through this integrated technology development approach, the project team has advanced RTI’s CO 2 capture technology to TRL-4 (nearly TRL-5, with the missing variable being testing on actual, coal-fired flue gas), according to the DOE/FE definitions for Technology Readiness Levels. At a broader level, this project has advanced the whole of the solid sorbent CO 2 capture field, with advancements in process engineering and design, technical risk mitigation, sorbent scale-up optimization, and an understanding of the commercial viability and applicability of solid sorbent CO 2 capture technologies for the U.S. existing fleet of coal-fired power plants.

01 COAL, LIGNITE, AND PEAT↗