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DOE OSTI2021

Gasoline Compression Ignition on a Light-Duty Multi-Cylinder Engine Using a Wide Range of Fuel Reactivities and Heavy Fuel Stratification

Many research studies have focused on utilizing gasoline in modern compression ignition engines to reduce emissions and improve efficiency. Collectively, this combustion mode has become kn+own as gasoline compression ignition (GCI). One of the biggest challenges with GCI operation is maintaining control over the combustion process through the fuel injection strategy, such that the engine can be controlled on a cycle-by-cycle basis. Research studies have investigated a wide variety of GCI injection strategies (i.e., fuel stratification levels) to maintain control over the heat release rate while achieving low-temperature combustion (LTC). This work shows that at loads relevant to light-duty engines, partial fuel stratification (PFS) with gasoline provides very little controllability over the timing of combustion. On the contrary, heavy fuel stratification (HFS) provides very linear and pronounced control over the timing of combustion. However, the HFS strategy has challenges achieving LTC operation due to the air handling burdens associated with the high exhaust gas recirculation (EGR) rates that are required to reduce NOx emissions to near zero levels. In this work, a wide variety of gasoline fuel reactivities (octane numbers ranging from <40 to 87) were investigated to understand the engine performance and emissions of HFS-GCI operation on a multi-cylinder light-duty engine. Overall, the results indicate that over an EGR sweep at 4 bar brake mean effective pressure (BMEP), the gasoline fuels can achieve LTC operation with ultra-low NO x and soot emissions, while conventional diesel combustion (CDC) is unable to simultaneously achieve low NO x and soot. At 10 bar BMEP, all the gasoline fuels were compared to diesel, but using mixing controlled combustion and not LTC.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

DPC Direct Disposal Postclosure Thermal Modeling

Performance of geologic radioactive waste repositories depends on near-field and far-field processes, including km-scale flow and transport in engineered and natural barriers, that may require simulations of up to 1 M years of regulatory period. For a relatively short time span (less than 1000 years), the thermohydro-mechanical-chemical (THMC) coupled processes caused by heat from the waste package will influence near-field multiphase flow, chemical/reactive transport, and mechanical behaviors in the repository system. This study integrates the heat-driven perturbations in thermo-hydro-mechanical characteristics into thermo-hydro-chemical simulations using PFLOTRAN to reduce dimensionality and improve computational efficiency by implementing functions of stress-dependent permeability and saturation-temperature-dependent thermal conductivity. These process couplings are developed for spent nuclear fuel in dual-purpose canisters in two different hypothetical repositories: a shale repository and a salt repository.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Data for Discovery, Characterization, and Application of Chromosomal Integration Sites for Stable Heterologous Gene Expression in Rhodotorula toruloides

Rhodotorula toruloides is a non-model, oleaginous yeast uniquely suited to produce acetyl-CoA-derived chemicals. However, the lack of well-characterized genomic integration sites has impeded the metabolic engineering of this organism. Here we report a set of computationally predicted and experimentally validated chromosomal integration sites in R. toruloides . We first implemented an in silico platform by integrating essential gene information and transcriptomic data to identify candidate sites that meet stringent criteria. We then conducted a full experimental characterization of these sites, assessing integration efficiency, gene expression levels, impact on cell growth, and long-term expression stability. Among the identified sites, 12 exhibited integration efficiencies of 50% or higher, making them sufficient for most metabolic engineering applications. Using selected high-efficiency sites, we achieved simultaneous double and triple integrations and efficiently integrated long functional pathways (up to 14.7 kb). Additionally, we developed a new inducible marker recycling system that allows multiple rounds of integration at our characterized sites. We validated this system by performing five sequential rounds of GFP integration and three sequential rounds of MaFAR integration for fatty alcohol production, demonstrating, for the first time, precise gene copy number tuning in R. toruloides . These characterized integration sites should significantly advance metabolic engineering efforts and future genetic tool development in R. toruloides .

Conversion↗

DOE OSTI2025

Low-Cost Sulfur Thermal Storage for Solar Industrial Process Heat Applications

Industrial process heat (IPH) is one of the largest energy demands in U.S., representing about 10% of all domestic energy consumption. Fuel costs to generate this industrial process heat are generally a top three cost for industry, a major component in American manufacturing competitiveness. Roughly 60% of US IPH demand (about 6,500 TBtu annually) falls in the medium-temperature range of 100–250 °C. While concentrated solar thermal (CST) technologies can provide a cost-effective source of heat in this temperature range, solar intermittency limits their adoption in industries that operate 24/7. Element 16 Technologies, Inc. developed a low-cost sulfur thermal energy storage (TES) technology to bridge this gap by capturing excess solar heat during the day and dispatching it reliably during non-solar hours. The core innovation is the use of sulfur, an abundant, industrial waste byproduct that costs ten times less than molten salt used in commercial TES systems. The overall goal of the project was to advance the design and development of molten sulfur TES to a manufacturing-relevant prototype stage for solar industrial process heat applications, while establishing and validating a realistic pathway to commercial success. Key tasks included corrosion and mechanical durability testing to identify cost-effective materials, design investigations using physics-based simulation tools, techno-economic evaluations of system lifetime costs, and pilot-scale testing for performance verification. Corrosion testing of steel alloys under cyclic molten sulfur conditions showed that austenitic stainless steels in the 300 series performed particularly well, with no structural degradation of welds or joints. Thermal cyclic testing of pilot sulfur TES units up to 1.5 MWh quantified charge/discharge rates, heat losses, round-trip efficiency and validated the system's capability to operate effectively under intermittent charging conditions. A techno-economic model, informed by sulfur TES performance model validated using pilot test data, showed that hybrid solar+sulfur TES+NG boiler systems are economically competitive with incumbent natural gas boilers for multiple locations in the southwest US. In summary, this project established molten sulfur TES as a technically viable pathway to improve economic competitiveness of American manufacturing by lowering the cost of solar industrial process heat.

14 SOLAR ENERGY↗

DOE OSTI2024

A data-driven multiscale model for reactive wetting simulations

Here, we describe a data-driven, multiscale technique to model reactive wetting of a silver–aluminum alloy on a Kovar™ (Fe-Ni-Co alloy) surface. We employ molecular dynamics simulations to elucidate the dependence of surface tension and wetting angle on the drop’s composition and temperature. A design of computational experiments is used to efficiently generate training data of surface tension and wetting angle from a limited number of molecular dynamics simulations. The simulation results are used to parameterize models of the material’s wetting properties and compute the uncertainty in the models due to limited data. The data-driven models are incorporated into an engineering-scale (continuum) model of a silver–aluminum sessile drop on a Kovar™ substrate. Model predictions of the wetting angle are compared with experiments of pure silver spreading on Kovar™ to quantify the model-form errors introduced by the limited training data versus the simplifications inherent in the molecular dynamics simulations. The paper presents innovations in the determination of “convergence” of noisy MD simulations before they are used to extract the wetting angle and surface tension, and the construction of their models which approximate physio-chemical processes that are left unresolved by the engineering-scale model. Together, these constitute a multiscale approach that integrates molecular-scale information into continuum scale models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

One Earth Energy FEED Process Design Basis

This report establishes the process design basis for the front-end engineering design (FEED) of a carbon capture and injection facility at One Earth Energy's (OEE) ethanol production plant in Gibson City, Illinois, developed as part of the Illinois Storage Corridor CarbonSAFE Phase III project. The facility is designed to compress and dehydrate up to approximately 458,000 metric tonnes of CO 2 per year, sourced directly from OEE's ethanol fermenters, for permanent injection into a saline aquifer approximately four miles from the plant. At normal operating conditions, the system will process 1,290 metric tonnes of CO 2 per day, assuming 355 operating days per year and an ethanol production rate of 160 million gallons per year. The proposed process trains a multistage centrifugal blower with a five-stage reciprocating compressor, delivering CO 2 to the injection wellhead at up to 1,500 psig. Triethylene glycol (TEG) dehydration, applied after the fourth compression stage, reduces water content to a target of 10 lb/MMscf, well within the 30 lb/MMscf injection limit. Beyond dehydration, no additional treatment is required; trace impurities including oxygen and nitrogen will remain in the injected stream. Key design considerations include the absence of spare cooling tower capacity at the site, necessitating new cooling infrastructure, and the need for a new electrical substation to support large motor loads. The facility is designed for continuous, largely unattended operation, monitored around the clock by existing OEE operations staff. This document serves as the foundational reference for all subsequent detailed engineering activities associated with the OEE CO 2 injection facility.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Challenges and Opportunities in the Enzymatic Recycling of Nylons

Enzymatic depolymerization has the potential to contribute to nylon waste recycling. However, the implementation of a viable industrial process still lags far behind progress in enzymatic polyester recycling. Here we review the current biocatalytic nylon recycling landscape, highlighting biochemical, structural, and materials science barriers that currently limit depolymerization extents. We detail efforts to identify, engineer, and characterize new nylon depolymerases, where currently even the best biocatalysts rarely exceed ~1 wt% conversion of solid polymer to products. Based on our analyses, we suggest that limited substrate accessibility due to substrate crystallinity and hydrogen bonding, rather than intrinsic enzyme inefficiency or instability, is the primary bottleneck to enhanced depolymerization. Guided by successes in polyester enzymatic recycling, we outline a research roadmap combining nylonase engineering with polymer pretreatment, chemo-enzymatic cascades, and process analyses to accelerate development of viable enzymatic nylon recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Initial Engineering Design of a Post-Combustion CO 2 Capture (PCC) System for Duke Energy’s East Bend Station Using Membrane-Based Technology

The Electric Power Research Institute (EPRI) led a U.S. Department of Energy (DOE) funded study for a membrane-based post-combustion CO 2 capture (PCC) system retrofit to an existing U.S. coal power plant. EPRI teamed with technology suppliers, Membrane Technology and Research (MTR), engineering consultants Nexant, Trimeric Corporation and Bechtel Power Corporation, to develop a first-of-a-kind initial design and cost estimate for a PCC system at Duke Energy’s East Bend Station (EBS) in Kentucky. This project provides a comprehensive overview of the plant design proposed and develops estimated costs to within +/- 30% accuracy for retrofitting the existing EBS coal-fired power plant with the latest MTR’s second-generation Polaris™ membrane technology for CO 2 flue gas removal. The projects primary objective was to develop a design for Duke Energy that will require “minimally invasive surgery” on their existing 600-MWe coal-fired power plant, located on the Ohio River in Boone County, Kentucky. Unlike the current commercially available solvent-based capture systems that require a reliable source of steam to operate, the MTR membrane-based capture system is driven primarily by electric power. This direct, bolt-on approach to retrofitting carbon capture could potentially reduce the impact on the existing power plant, by minimal disruption of the existing facility’s infrastructure and operating procedures. This may also reduce the amount of retrofit downtime before the power plant can resume normal operations. A second objective was to reduce the cost of each ton of captured CO 2 while maintaining the existing 600 MW net output of the East Bend Station. With this aim in mind, various options to provide the necessary auxiliary power for the capture system were evaluated for the site. The full report describes in detail the overall design, layout and components of the entire EBS membrane capture system. The equipment and sizes, the capital cost estimate encompassing both engineering design and construction for the carbon capture process and balance of plant systems is presented. A detailed techno-economic analysis is also undertaken to examine the business case for capture.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Scale-up Testing of Advanced Polaris Membrane in CO2 Capture Technology

This final technical report describes work conducted by Membrane Technology and Research, Inc. (MTR) for the U.S. Department of Energy (DOE), National Energy Technology Lab (NETL) on the scale-up and testing of advanced Polaris™ membrane CO2 capture technology at the Technology Centre Mongstad (TCM) under award number DE-FE0031591. The work was performed from August 1, 2018 through January 31, 2023. The overall goal of this project was to design, build and operate an advanced Polaris membrane CO2 capture system at TCM. MTR was assisted in this project by Trimeric Corporation (Trimeric), an engineering design services company, the Carbon Capture Simulation for Industry Impact (CCSI2), a partnership among national laboratories, industry, and academic institutions, and the Technology Centre Mongstad (TCM), who provided the host site for the slipstream field test. This report details the work conducted to scale-up MTR’s second-generation (Gen-2) Polaris membrane and advanced planar membrane modules to a final form factor optimized for commercial use; validate their performance in an engineering-scale field test at TCM; and to show the potential of the MTR process to meet DOE CO2 capture targets from large source point emitters. Work for this project included membrane optimization and scale-up, advanced planar module design and fabrication, design and fabrication of an engineering-scale field test membrane skid, operation of the field test skid processing Residue Fluid Catalytic Cracker (RFCC) industrial flue gas at TCM, and a detailed techno-economic analysis (TEA) of the MTR membrane post-combustion process for CO2 capture. This project validated recent membrane technology advancements at the engineering-scale, moves the MTR advanced post-combustion capture technology to TRL-6, and mitigates risk in future Large Pilot or Demonstration scale-up activities.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Experimental Study of Instabilities in Hydrogen-Air Fueled Rotating Detonation Combustion Presentation

Conventional gas turbine engines rely on an idealized constant pressure combustion process that in reality produces a pressure decrease as a result of viscous and other non-reversible losses. An alternative approach is rotating detonation combustion (RDC) which is a form of pressure gain combustion in which one or more detonation waves propagate an annular channel resulting in an increase in pressure across, subsequently providing greater work availability compared to deflagration ultimately leading to opportunities for greater thermodynamic efficiency when used in gas turbine engines that conventionally relies on constant. Modern gas turbine engines often rely on pre-mixed reactants to limit NOx emissions, although this may result in greater susceptibility to instabilities such as flashback and thermoacoustic oscillation, particularly for applications that utilize hydrogen as the fuel. Research in RDC has focused on non-premixed reactants thus limiting the occurrence of flashback, and high frequency detonation wave propagation (kHz) may interfere with the occurrence of thermoacoustic oscillations. Thermal NOx emissions are controlled through rapid combustion and sudden expansion of the working fluid. Although RDC may not be susceptible to instabilities encountered in conventional state of the art gas turbine engine combustion, there may be other mechanisms occurring that support instabilities that could be detrimental to performance.

Weber, Justin↗

DOE OSTI2024

Colorado State University Extension Industrial Assessment Center

Since its inception in 1984, the Colorado State University Industrial Assessment Center has performed industrial assessments at more than 720 manufacturing facilities in Colorado, Montana, Nebraska, Nevada, New Mexico, North Dakota, South Dakota, Utah, and Wyoming. From 2017 to 2019 there was a funding gap and the IAC shutdown. In 2020 through DOE extension funding the University relaunched the IAC as an extension center in order to provide assessments to underserved areas. Under this award, the CSU Industrial Assessment Center (IAC) was rebuilt with the help of student employees and the director. The CSU team experienced difficulty as the program was in the process of being restarted right as the 2020 pandemic hit. Nonetheless, the CSU IAC was instrumental in providing energy assessments to manufacturers in Colorado and Wyoming during the period of performance of 09/2019 – 12/2022. The Department of Energy's Industrial Assessment Centers (IACs) provide a valuable service to small and medium-sized manufacturers seeking to optimize their operations. These university-based centers offer no-cost, on-site assessments conducted by engineering faculty and students, analyzing energy consumption, production processes, and waste streams. They utilize advanced data acquisition systems to record operational data, and then use the data to create assessment recommendations. These recommendations form the foundation of the comprehensive energy report. The comprehensive report delivers actionable recommendations for enhancing energy efficiency, reducing waste, and reducing greenhouse gas emissions and improving productivity, often identifying significant cost savings. Furthermore, IACs facilitate access to implementation grants, enabling the businesses to readily adopt these improvements. This program not only strengthens individual businesses but also contributes to national goals of training the next generation of energy experts, as well as increasing industrial competitiveness and reduced environmental impact.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

[Challenges and Opportunities in] Process Modeling of Intensified Chemical Processes

Before the benefits of process intensification can be fully realized, a multitude of advances in process modeling will be necessary. Process intensification (PI) has the potential to speed development of chemical engineering innovations. Among its many benefits, PI can increase the driving forces (physical and/or chemical) for transport phenomena, separations, and/or reactions in chemical processes, and inspire novel process configurations with major technical and economic benefits. Examples of PI applications include integrated process units such as heat exchange networks, sorption- or membrane-enhanced reactors, and dividing-wall distillation columns, among others [AIChE(2017)].

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine

03 NATURAL GAS↗

DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data (Final Report)

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Plan for Developing TRISO Fuel Processing Technologies

This Plan demonstrates the availability of technologies for processing TRISO used nuclear fuel for waste management and actinide recovery purposes. These technologies are judged to be at a very low level of technology readiness and as such they constitute a fertile research area for the DOE-NE’s Office of Materials and Chemical Technologies. Strategies to mature the technologies to a point where they can reasonably be considered in engineering alternatives analyses typically involve laboratory-scale tests using fuel simulant to characterize process streams and demonstrate key engineering features. Several criteria are available to help selecting candidate technologies for further maturation

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Models implemented in the methodological approach to design the initial STEP first wall contour

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is managing the loads on the first wall within acceptable limits. Therefore, the conceptual design development of the STEP Prototype Power plant needs to be based on load estimates derived using legitimate plasma physics assumptions through dynamic and flexible tools. The current design foresees the STEP main chamber first wall to withstand steady-state heat loads of up to ~1 MW/m 2 , excluding critical regions expected to receive higher heat loads such as the baffle regions approaching the divertors. These critical areas will require ad hoc assessments and will be designed with the presence of limiters. This article focuses on the models and methodology adopted for designing the 2-D poloidal contour of the STEP first wall, based on the anticipated charged particle and radiation heat loads during normal operation. Firstly, the models adopted for calculating the charged particle and radiation heat loads are introduced. The first model is validated through benchmarking against the particle tracing code SMARDDA, while the second model is verified by comparing it with data from the MAST-U experiment. Secondly, the model used to design the 2-D first wall contour according to the heat loads is explained. We acknowledge that this preliminary design stage assumes certain simplifications, notably an axisymmetric geometry, for computational efficiency and clarity in presentation. It is understood that subsequent design phases will address the complexities of real-world engineering, including non-axisymmetric effects, transient plasma scenarios, and the impact of disruptions on the first wall design. Finally, an automatic procedure based on these models is presented for defining the 2-D poloidal contour of the STEP first wall to minimize heat loads, taking into account the need to radiate most of the alpha-particle and auxiliary heating power. Here, by providing an overview of the models, methodology, and an automatic procedure, this paper contributes to the design process of the STEP first wall, addressing the engineering challenges associated with fusion power plant development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Cyber-Informed Engineering

Briefings provided to Duke Energy during their visit to INL on January 25, 2023. This is following the process to release the slides to Duke Energy.

42 ENGINEERING↗

DOE OSTI2022

Solvent-driven fractional crystallization for atom-efficient separation of metal salts from permanent magnet leachates

Abstract This work reports a dimethyl ether-driven fractional crystallization process for separating rare earth elements and transition metals. The process has been successfully applied in the treatment of rare earth element-bearing permanent magnet leachates as an atom-efficient, reagent-free separation method. Using ~5 bar pressure, the solvent was dissolved into the aqueous system to displace the contained metal salts as solid precipitates. Treatments at distinct temperatures ranging from 20–31 °C enable crystallization of either lanthanide-rich or transition metal-rich products, with single-stage solute recovery of up to 95.9% and a separation factor as high as 704. Separation factors increase with solution purity, suggesting feasibility for eco-friendly solution treatments in series and parallel to purify aqueous material streams. Staged treatments are demonstrated as capable of further improving the separation factor and purity of crystallized products. Upon completion of a crystallization, the solvent can be recovered with high efficiency at ambient pressure. This separation process involves low energy and reagent requirements and does not contribute to waste generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗