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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction

TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with a Transcription Factor (TF)-gene regulatory network (TRN), which is modeled via a Bayesian network (BN). In this paper, we focus on sensitivity analysis of metabolic flux prediction for uncertainty quantification of BN structures for TRN modeling in TRIMER. We propose a computational strategy to construct the uncertainty class of TRN models based on the inferred regulatory order uncertainty given transcriptomic expression data. With that, we analyze the prediction sensitivity of the TRIMER pipeline for the metabolite yields of interest. The obtained sensitivity analyses can guide Optimal Experimental Design (OED) to help acquire new data that can enhance TRN modeling and achieve specific metabolic engineering objectives, including metabolite yield alterations. Here we have performed small- and large-scale simulated experiments, demonstrating the effectiveness of our developed sensitivity analysis strategy for BN structure learning to quantify the edge importance in terms of metabolic flux prediction uncertainty reduction and its potential to effectively guide OED.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Anomalous density and elastic properties of basalt at high pressure: Reevaluating of the effect of melt fraction on seismic velocity in the Earth's crust and upper mantle

Independent measurements of the volumetric and elastic properties of Columbia River basalt glass were made up to 5.5 GPa by high-pressure X-ray microtomography and GHz-ultrasonic interferometry, respectively. The Columbia River basalt displays P and S wave velocity minima at 4.5 and 5 GPa, respectively, violating Birch’s law. These data constrain the pressure dependence of the density and elastic moduli at high pressure, which cannot be modeled through usual equations of state nor determined by stepwise integrating the bulk sound velocity as is common practice. We propose a systematic variation in compression behavior of silicate glasses that is dependent on the degree of polymerization and arises from the flexibility of the aluminosilicate network. Likewise, this behavior likely persists into the liquid state for basaltic melts resulting in weak pressure dependence for P wave velocities perhaps to depths of the transition zone. By modeling the effect of partial melt on P wave velocity reductions it is suggested that melt fraction determined by seismic velocity variations may be significantly overestimated in the crust and upper mantle.

58 GEOSCIENCES↗
DOE OSTI2021

Mediated electrochemistry for redox-based biological targeting: entangling sensing and actuation for maximizing information transfer

Biology and electronics are both expert at receiving, analyzing, and responding to information, yet they use entirely different information processing paradigms. Biology processes information using networks that are intrinsically molecular while electronics process information through circuits that control the flow of electrons. There is great interest in coupling the molecular logic of biology with the electronic logic of technology, and we suggest that redox (reduction-oxidation) is a uniquely-suited modality for interfacing biology with electronics. Specifically, redox is a native biological modality and is accessible to electronics through electrodes. Here, we summarize recent advances in mediated electrochemistry to direct information transfer into biological systems intentionally altering function, exposing it for more advanced interpretation, which can dramatically expand the biotechnological toolbox.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Digital Twin-Enabled Adaptive Control for Hydroelectric Systems: Turbine Governor and Voltage Regulation

This paper presents a comprehensive digital twin (DT) framework for hydroelectric systems that enables adaptive control of turbine governors and excitation systems without requiring detailed manufacturer specifications. The proposed framework integrates neural network-based system identification with stabilizing adaptive control laws for the installed turbine controller and middle-branch adaptive tuning for the installed voltage regulator. Using real operational data from Unit C-8 at Rocky Reach Dam (1,349 MW capacity), highfidelity neural network models are developed to capture turbine and generator dynamics without requiring detailed manufacturer specifications. The DT enables safe controller synthesis and validation in simulation before deployment. For turbine control, the proposed method achieves a 79.9% mean square error (MSE) reduction compared with that of an optimal controller. For voltage regulation, the adaptive excitation controller achieves approximately 42.6% MSE reduction while preserving installed protection logic. The results demonstrate that DT technology provides a practical pathway for modernizing hydropower control systems with minimal operational disruption.

Gui, Yonghao [ORNL] (ORCID:0000000250435534)↗
DOE OSTI2020

Multicarrier Energy Systems: Shaping Our Energy Future

Multicarrier energy systems (MCESs) are characterized by strong coordination in operation and planning across multiple energy vectors and/or sectors to deliver reliable, cost-effective energy services to end users/customers with minimal impact on the environment. They have efficiency and flexibility benefits and are deployed in large and small scales on the supply and demand sides and at the network level but are more complex to control and manage. Here, MCESs are reviewed in the context of future low carbon energy systems based on electrification and very high variable renewable energy penetrations. Fully exploiting these systems requires some cost reductions, more sophisticated operations enabled by standardized communications and control capabilities detailed planning paradigms, and addressing their corresponding economic challenges. All these point toward the direction of analysis, markets, and technology research and development coupled with better policy and regulatory frameworks. One futuristic vision of a very low carbon energy system is proposed that illustrates potential pathways to an MCES-dominated energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Global Data Re-allocation via Communication Aggregation in Chapel

Chapel is a parallel programming language designed to improve the productivity and ease of use of conventional and parallel computers. This language currently delivers sub optimal performance when executing codes that perform global data re-allocation operations on distributed memory architectures. This is mainly due to data communication that is done without aggregation (one message for each remote array element). In this work, we analyze Chapel's standard Block and Cyclic distribution modules and optimize the communication routines for array assignments by performing aggregation. Thanks to the expressive power of Chapel, the compiler and runtime have enough information to do communication aggregation without user intervention. The runtime relies on the low-level GAS Net networking layer, whose versions of one-sided bulk put/get routines that support strides are particularly useful for us. Experimental results conducted on Hector (a Cray XE6) and Jaguar (Cray XK6)reveal that the implemented techniques can lead to significant reductions in communication time.

Sanz, Alberto↗
DOE OSTI2017

Small Scale Field Test Demonstrating CO 2 Sequestration In Arbuckle Saline Aquifer And By CO 2 -Eor At Wellington Field, Sumner County, Kansas

The objectives of this project are to understand the processes that occur when a maximum of 70,000 metric tonnes of CO 2 are injected into two different formations to evaluate the response in different lithofacies and depositional environments. The evaluation will be accomplished through the use of both in situ and indirect MVA (monitoring, verification, and accounting) technologies. The project will optimize for carbon storage accounting for 99% of the CO 2 using lab and field testing and comprehensive characterization and modeling techniques. Site characterization and CO 2 injection should demonstrate state-of-the-art MVA tools and techniques to monitor and visualize the injected CO 2 plume and to refine geomodels developed using nearly continuous core, exhaustive wireline logs, and well tests and a multi-component 3-D seismic survey. Reservoir simulation studies will map the injected CO 2 plume and estimate tonnage of CO 2 stored in solution, as residual gas, and by mineralization and integrate MVA results and reservoir models shall be used to evaluate CO 2 leakage. A rapid-response mitigation plan was developed to minimize CO 2 leakage and provide a comprehensive risk management strategy. The CO 2 was intended to be supplied from a reliable facility and have an adequate delivery and quality of CO 2 . However, several unforeseen circumstances complicated this plan: (1) the initially negotiated CO 2 supply facility went offline and contracts associated with CO 2 supply had to be renegotiated, (2) a UIC Class VI permit proved to be difficult to obtain due to the experimental nature of the project. Both subjects are detailed in separate deliverables attached to this report. The CO 2 enhanced oil recovery (EOR) and geologic storage in Mississippian carbonate reservoir was sucessully deployed. Approximately 20,000 metric tons of CO 2 was injected in the upper part of the Mississippian reservoir to verify CO 2 EOR viability in carbonate reservoirs and evaluate a potential of transitioning to geologic CO 2 storage through EOR. A total of 1,101 truckloads, 19,803 metric tons—an average of 120 tonnes per day—were delivered over the course of injection that lasted from January 9 to June 21, 2016. After cessation of CO 2 injection, the KGS 2-32 well was converted to water injector and continues to operate. CO 2 EOR progression in the field was monitored weekly with fluid level, temperature, and production recording and formation fluid composition sampling. It is important to note that normally, CO 2 EOR pilots are less efficient than commercial operations due to lack of directional and precise well control, lack of surface facilities for CO 2 recycling, and other factors. As a result of this pilot CO 2 injection, the observed incremental average oil production increase was ~68% with only ~18% of injected CO 2 produced back. Decline curve analysis forecasts of additional cumulative oil produced were 32.44M STB to the end of 2027. Wellington Mississippian pilot efficiency by the end of forecast calculations is 11 MCF per barrel of produced oil. Using 32M STB oil production and $1,964,063 cost of CO 2 , CO 2 EOR cost per barrel of oil production is ~$60. Simple but robust monitoring technologies proved to be very efficient in detecting and locating CO 2 . High CO 2 reservoir retentions with low yields within an actively producing field could help to estimate real-world risks of CO 2 geological storage for future projects. The Wellington Field CO 2 EOR was executed in a controlled environment with high efficiency. This case study proves that CO 2 EOR could be successfully applied in Kansas carbonate reservoirs if CO 2 sources and associated infrastructure are available. Recent developments in unconventional resources development in Mid-Continent USA and associated large volume disposal of backflow water and the resulting seismic activity have brought more focus and attention to the Arbuckle Group in southern Kansas. Despite the commercial interest, limited essential information about reservoir properties and structural elements has impeded the management and regulation of disposal, an issue brought to the forefront by recent seismicity in and near areas of large volumes and rates of brine disposal. The Kansas Geological Survey (KGS) collected, compiled, and analyzed available data, including well logs, core data, step rate tests, drill stem tests, 2-D and 3-D seismic data, water level measurements, and others types of data. Several exploratory wells were drilled and core was collected and modern suites of logs were analyzed. Reservoir properties were populated into several site-specific geological models. The geological models illustrate the highly heterogeneous nature of the Arbuckle Group. Vertical and horizontal variability results in several distinct hydro-stratigraphic units that are the result of both depositional and diagenetic processes. During the course of this project, it has been demonstrated that advanced seismic interpretation methods can be used successfully for characterization of the Mississippian reservoir and Arbuckle saline aquifer. Analysis of post-stack 3-D seismic data at the Mississippian reservoir showed the response of a gradational velocity transition. Pre-stack gather analysis showed that porosity zones of the Mississippian and Arbuckle reservoirs exhibit characteristic amplitude versus offset (AVO) response. Simultaneous AVO inversion estimated P- and S-impedances. The 3-D survey gather azimuthal anisotropy analysis (AVAZ) provided information about the fault and fracture network and showed good agreement to the regional stress field and well data. Mississippian reservoir porosity and fracture predictions agreed well with the observed mobility of injected CO 2 in KGS well 2-32. Fluid substitution modeling predicted acoustic impedance reduction in the Mississippian carbonate reservoir introduced by the presence of CO 2 . Seismicity in the United States midcontinent has increased by orders of magnitude over the past decade. Spatiotemporal correlations of seismicity to wastewater injection operations have suggested that injection-related pore fluid pressure increases are inducing the earthquakes. In this investigation, we examine earthquake occurrence in southern Kansas and northern Oklahoma and its relation to the change in pore pressure. The main source of data comes from the Wellington Array in the Wellington oil field, in Sumner County, Kansas, which has monitored for earthquakes in central Sumner County, Kansas, since early 2015. The seismometer array was established to monitor CO 2 injection operations at Wellington Field. Although no seismicity was detected in association with the spring 2016 Mississippian CO 2 injection, the array has recorded more than 2,500 earthquakes in the region and is providing valuable understanding to induced seismicity. A catalog of earthquakes was built from this data and was analyzed for spatial and temporal changes, stress information, and anisotropy information. The region of seismic concern has been shown to be expanding through use of the Wellington earthquake catalog, which has revealed a northward progression of earthquake activity reaching the metropolitan area of Wichita. The stress orientation was also calculated from this earthquake catalog through focal mechanism inversion. The calculated stress orientation was confirmed through comparison to other stress measurements from well data and previous earthquake studies in the region. With this knowledge of the stress orientation, the anisotropy in the basement could be understood. This allowed for the anisotropy measurements to be correlated to pore pressure increases. The increase in pore pressure was monitored through time-lapse shear-wave anisotropy analysis. Since the onset of the observation period in 2010, the orientation of the fast shear wave has rotated 90°, indicating a change associated with critical pore pressure build up. The time delay between fast and slow shear wave arrivals has increased, indicating a corresponding increase in anisotropy induced by pore pressure rise. In-situ near-basement fluid pressure measurements corroborate the continuous pore pressure increase revealed by the shear-wave anisotropy analysis over the earthquake monitoring period. This research is the first to identify a change in pore fluid pressure in the basement using seismological data and it was recently published in the AAAS journal Science Advances (Nolte et al., 2017). The shear-wave splitting analysis is a novel application of the technique, which can be used in other regions to identify an increase in pore pressure. This increasing pore fluid pressure has become more regionally extensive as earthquakes are occurring in southern Kansas, where they previously were absent. These monitoring techniques and analyses provide new insight into mitigating induced seismicity’s impact on society.

02 PETROLEUM↗
DOE OSTI2024

Non-Rare Earth Magnesium Bumper Beams

Magna will team with the Pacific Northwest National Laboratory (PNNL) to develop Shear Assisted Processing and Extrusion (ShAPE™) of rectangular and multi-zoned extrusion profiles using non-RE Mg. It is envisioned that the ShAPE™ process, developed during this project for non-circular profiles, will serve as the foundation for fabrication of full-scale bumper beams of the future where near net-shapes are extruded directly from castings in a single step, without the need for costly rare earth additives. In this project, the ShAPE™ process will be developed for a rectangular profile measuring 1” x 2” with a 0.06” wall thickness. Successful extrusion of rectangular cross sections is a critical step along the path toward profiles with multiple zones. With the process established for a rectangular profile, the project will then make advancements toward multi-zoned cross sections. A magnesium alloy bumper beam offers a 35% weight savings compared to aluminum alloys and 60% compared to high strength steels. The bumper beam was chosen as the first component to target because the geometry can have a fairly simple 0.6-0.12 inch wall/web thickness, generally compatible with PNNL’s knowledge base and equipment capability surrounding ShAPE™. The bumper component offers commercial value by providing mass reduction in the front of the vehicle along with ride and handling benefit. PNNL has demonstrated the ability to ShAPE™ process non-RE Mg tubing with high strength, ductility and energy absorption. It has been shown that ShAPE™ extruded ZK60 and Mg2Si tubing with 0.30 inch diameter and 0.03 inch wall thickness have similar energy absorption to AA6061-T6. This is due to significant grain refinement, breakdown and dispersion of second phases, and the ability to eliminate anisotropy in compressive/tensile strength by aligning texture 45 degrees to the extrusion axis. Scalability of the ShAPE™ process has been demonstrated in ZK60 by fabricating 2.0 inch diameter tubing with 0.06 and 0.12 inch wall thicknesses having concentricity as tight as 1.3%. These tubes exhibit an ultimate tensile strength of 260-300 MPa and room temperature ductility of >20% parallel, perpendicular and 45 degrees to the extrusion axis. Aluminum bumpers represent approximately 54% of the NA light vehicle market. If the research effort is successful, providing a 30% mass reduction at equal cost relative to aluminum bumpers, it is anticipated that 25% market penetration would be realized over the next 5 year and 50% market share by 2030. 100% of the aluminum automotive bumpers are sourced from the tier network, providing resourcing opportunity based on equal performance, reduced mass and cost equivalent lower than aluminum bumpers. Due to the relatively low vehicle content, magnesium components are currently shredded and 100% recycled with aluminum content in the US, presenting a positive life cycle impact.

42 ENGINEERING↗
DOE OSTI2025

Uncovering Structure–Conductivity Relationships in Anion Exchange Membranes (AEMs) Using Interpretable Machine Learning

Anion exchange membranes (AEMs) play a vital role in the performance of water electrolyzers and fuel cells, yet their discovery and optimization remain challenging due to the complexity of structure–property relationships. In this study, we introduce a machine learning framework that leverages conditional graph neural networks (cGNNs) and descriptor-based models and a hybrid graph neural network (HGARE) to predict and interpret ionic conductivity. The descriptor-based pipeline employs principal component analysis (PCA), ablation, and SHAP analysis to identify factors governing anion conductivity, revealing electronic, topological, and compositional descriptors as key contributors. Beyond prediction, dimensionality reduction and clustering are performed by employing t-SNE and KMeans as well as SOM, which reveal distinct membranes clusters, some of which were enriched with high anion conductivity. Among graph-based approaches, the graph convolutional (GCN) achieved strong predictive performance, while the Hybrid Graph Autoencoder-Regressor Ensemble (HGARE) achieved the highest accuracy. Additionally, atom-level saliency maps from GCN provide spatial explanations for conductive behavior, revealing the importance of polarizable and flexible regions. This work contributes to the accelerated and data-driven design of high-performance AEMs.

Naghshnejad, Pegah [Department of Chemical Enginee↗
DOE OSTI2014

Assessment of the Effect of Air Pollution Controls on Trends in Shortwave Radiation over the United States from 1995 through 2010 from Multiple Observation Networks

Long term datasets of total (all-sky) and clear-sky downwelling shortwave (SW) radiation, cloud cover fraction (cloudiness) and aerosol optical depth (AOD) are analyzed together with aerosol concentration from several networks (e.g. SURFRAD, CASTNET, IMPROVE and ARM) in the United States (US). Seven states with varying climatology are selected to better understand the effect of aerosols and clouds on SW radiation. This analysis aims to test the hypothesis that the reductions in anthropogenic aerosol burden resulting from substantial reductions in emissions of sulfur dioxide and nitrogen oxides over the past 15 years across the US has caused an increase in surface SW radiation. We show that the total and clear-sky downwelling SW radiation from seven sites have increasing trends except Penn State which shows no tendency in clear-sky SW radiation. After investigating several confounding factors, the causes can be due to the geography of the site, aerosol distribution, heavy air traffic and increasing cloudiness. Moreover, we assess the relationship between total column AOD with surface aerosol concentration to test our hypothesis. In our findings, the trends of clear-sky SW radiation, AOD, and aerosol concentration from the sites in eastern US agree well with our hypothesis. However, the sites in western US demonstrate increasing AOD associated with mostly increasing trends in surface aerosol concentration. At these sites, the changes in aerosol burden and/or direct aerosol effects alone cannot explain the observed changes in SW radiation, but other factors need to be considered such as cloudiness, aerosol vertical profiles and elevated plumes.

1995-2010↗
NASA NTRS1973

Exhaust pressure and density of various pulsed MPD-Arc thruster systems

Exhaust flow in a new 155-cm-i.d. vacuum facility is compared with earlier measurements in a small (15.2-cm-i.d.) duct. Reductions in post-transient impact pressure are about 5:1 in the larger facility. Corresponding reduced electron number densities (about 2 x 10 to the 13th power per cu cm) are noted. A new 125-microsec pulse-forming network power source produced no major differences in impact pressure compared to the crowbarred condenser bank used earlier. Comparing a puff gas feed of the arc chamber with a new 10-msec steady gas feed also shows no major difference in impact pressure for 125-microsec powering.

Michels, C. J.↗
NASA NTRS1993

Microinstruments for a Low Power, Low Mass Weather Station

Advances in electronics and instrument technology over the past thirty years have enabled a new concept for NASA missions, an evolution from large Voyager-class spacecraft to smaller, less costly Discovery and Explorer missions. By taking advantage of micromachining and micro-instrumentation, this reduction in size can be accomplished without requiring a sacrifice in performance. In some cases, the small payload will enable new types of missions which would be otherwise inconceivable. A microweather station is envisioned as an enabling technology for a network of weather stations on Mars for measuring wind, temperature, pressure, humidity, and aerosol concentration in the Martian planetary boundary layer...

Hoenk, M. E.↗
DOE OSTI2023

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗
DOE OSTI2013

In situ fabrication and characterization of cobalt ferrite nanorods/graphene composites

Cobalt ferrite nanorods/graphene composites were prepared by a one-step hydrothermal process using NaHSO{sub 3} as the reducing agent and 1-propyl-3-hexadecylimidazolium bromide as the structure growth-directing template. The reduction of graphene oxide and the in situ formation of cobalt ferrite nanorods were accomplished in a one-step reaction. The structure and morphology of as-obtained composites were characterized by field emission scanning electron microscopy, transmission electron microscopy, high resolution transmission electron microscopy, atomic force microscope, X-ray diffractometer, Fourier transform infrared spectra, X-ray photoelectron spectroscopy and Raman spectroscopy. Uniform rod-like cobalt ferrites with diameters of about 100 nm and length of about 800 nm were homogeneously distributed on the graphene sheets. The hybrid materials showed a saturation magnetization of 42.5 emu/g and coercivity of 495.1 Oe at room temperature. The electromagnetic parameters were measured using a vector network analyzer. A minimum reflection loss (RL) of − 25.8 dB was observed at 16.1 GHz for the cobalt ferrite nanorods/graphene composites with a thickness of 2 mm, and the effective absorption frequency (RL < − 10 dB) ranged from 13.5 to 18.0 GHz. The composites exhibited better absorbing properties than the cobalt ferrite nanorods and the mixture of cobalt ferrite nanorods and graphene. - Highlights: • Reduction of GO and formation of ferrites were accomplished in a one-step reaction. • Ionic liquid was used to control 1D growth of ferrite nanorods for the first time. • Cobalt ferrite nanorods/graphene composites showed dielectric and magnetic loss. • Cobalt ferrite nanorods/graphene composites exhibited better absorbing properties.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Investigation of Error Patterns in Geographical Databases

The objective of the research conducted in this project is to develop a methodology to investigate the accuracy of Airport Safety Modeling Data (ASMD) using statistical, visualization, and Artificial Neural Network (ANN) techniques. Such a methodology can contribute to answering the following research questions: Over a representative sampling of ASMD databases, can statistical error analysis techniques be accurately learned and replicated by ANN modeling techniques? This representative ASMD sample should include numerous airports and a variety of terrain characterizations. Is it possible to identify and automate the recognition of patterns of error related to geographical features? Do such patterns of error relate to specific geographical features, such as elevation or terrain slope? Is it possible to combine the errors in small regions into an error prediction for a larger region? What are the data density reduction implications of this work? ASMD may be used as the source of terrain data for a synthetic visual system to be used in the cockpit of aircraft when visual reference to ground features is not possible during conditions of marginal weather or reduced visibility. In this research, United States Geologic Survey (USGS) digital elevation model (DEM) data has been selected as the benchmark. Artificial Neural Networks (ANNS) have been used and tested as alternate methods in place of the statistical methods in similar problems. They often perform better in pattern recognition, prediction and classification and categorization problems. Many studies show that when the data is complex and noisy, the accuracy of ANN models is generally higher than those of comparable traditional methods.

Dryer, David↗
DOE OSTI2022

Universal Solvent Viscosity Reduction via Hydrogen Bonding Disruptors

Liquid Ion Solutions LLC (DBA RoCo Global) in partnership with Carnegie Mellon University and Carbon Capture Scientific LLC, has performed lab-scale development and evaluation of novel additives that lower the viscosity of water-lean amine solvents for post-combustion carbon dioxide capture. This project focuses on developing additives that minimize the formation of long-range electrostatic and hydrogen bonding (HB) networks, decreasing the solvent viscosity, improving diffusion, and improving the process economics. The project objectives included: 1) performing computer simulation to understand the molecular interactions of the additive molecules in water-lean CO 2 capture solvents, 2) design and synthesis of HB disruptors additives, 3) performance testing with additive molecules on model amine solvents, and 4) demonstration of the effectiveness of the optimized additives in the presence of synthetic flue gas. To meet the abovementioned objectives, the project team utilized a holistic approach that combines molecular simulation, experimental testing, and economic analysis studies. The project team developed ab initio molecular model and then perform computer simulation to develop relationship between hydrogen bonding, viscosity, and performed quantitative analysis of additive on the viscosity of the solvent. The team completed computational comparative study on a range of organic functional groups such as ethers, esters, cyclic carbonates, alkanes, and ammonium salts for their effect on viscosity gaining key insights into molecular interactions and the impact of various functional groups and molecular shapes on viscosity. Assisted with molecular simulation insights, the project team conducted additive synthesis and testing, including a proof-of-concept study, additive screening, optimization, and synthetic flue gas testing. The experimental proof-of-concept study proved that the hydrogen bonding acceptors result in significant decrease of viscosities. Detailed additive screening (exploring various functionalities and molecular structures) has been performed. Several promising additives showed excellent reduction in viscosity (30-41%) at 5% additive loading, and over 50% viscosity reduction at 10% additive loading for the model solvents. The team also performed complex screening studies on additive loadings and mixing effect among additives using the design of experiments. Based on multiple screening experiments, one additive-solvent candidate was down-selected for synthetic flue gas testing. A 100-hour continuous absorption/desorption study was conducted under simulated flue gas using a lab-scale continuous capture and separation system. No degradation (for both solvent and additive) was observed based on the GC results of the solvent samples collected from the continuous study. The team conducted preliminary engineering analyses and cost-benefit analyses to quantify the potential economic benefits of the additive approach for solvent viscosity reduction. Based on the experimental data, CO 2 capture cost savings from the capital and operating cost savings are estimated at $\$$4.7/tonne and $\$$0.3/tonne CO 2 captured, respectively. Considering the additive cost, the net benefit is estimated to be between $\$$4.32~$\$$4.86/tonne CO 2 captured.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Optimization of the deep neural network parameters for generating homogenized fuel assembly data for nodal codes

Homogenized fuel assembly (FA) data is a typical input data for nodal codes. Generating that data, however, could be time-consuming. One of promising ways to mitigate the computational burden of generating macroscopic cross-sections is to use trained artificial neural network (ANN) models for predicting nuclear data. However, there is a challenge to make the model support variable FA geometry. In this work, two most common types of FA were combined in one ANN model. Since there could be multiple ways of converting 2-dimensional FA data into 1-dimensional input vector for ANN, three different approaches of data flattening were evaluated. The input parameters included each fuel pin enrichment, fuel temperature, moderator temperature and boron concentration. The output parameters were 2-group macroscopic cross-sections (XS) and pin power distribution (HFF). A fully connected deep neural network (DNN) model was trained and tested using pre-generated data obtained with lattice physics code STREAM. The results of this study showed no statistically significant difference in the accuracy of XS and HFF generation for all 3 tested input vector orders. This means that fully connected DNN for XS generation demonstrated input sequence invariance. Results of comparing predicted XS data with reference solutions were found sufficiently close considering the reduction of computation time offered by ANN. Mean relative difference (MRD) for all output XS parameters was found below 0.7%, while HFF MRD was found higher compared to XS values, in some cases slightly exceeding 1%, mostly near guide tube locations. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗